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https://github.com/mikeroyal/IoT-Guide
IoT Guide
https://github.com/mikeroyal/IoT-Guide
List: IoT-Guide
automation awesome awesome-iot awesome-list awesome-readme awesome-resources cloud cloud-native home-assistant home-automation iot iot-application iot-platform networking storage
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JSON representation
IoT Guide
- Host: GitHub
- URL: https://github.com/mikeroyal/IoT-Guide
- Owner: mikeroyal
- Created: 2021-04-02T20:11:25.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-02-06T20:13:11.000Z (over 2 years ago)
- Last Synced: 2024-05-23T07:14:25.418Z (5 months ago)
- Topics: automation, awesome, awesome-iot, awesome-list, awesome-readme, awesome-resources, cloud, cloud-native, home-assistant, home-automation, iot, iot-application, iot-platform, networking, storage
- Language: Shell
- Homepage:
- Size: 518 KB
- Stars: 13
- Watchers: 4
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
IoT Guide
#### A guide for getting started with IoT devices including software and hardware that will make you a better and more efficient IoT developer.
**Note: You can easily convert this markdown file to a PDF in [VSCode](https://code.visualstudio.com/) using this handy extension [Markdown PDF](https://marketplace.visualstudio.com/items?itemName=yzane.markdown-pdf).**
# Table of Contents
1. [IoT Learning Resources](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#iot-learning-resources)
2. [IoT Tools](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#iot-tools)
3. [Networking](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#networking)
4. [Databases](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#databases)
5. [Telco 5G](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#telco-5g)
6. [Open Source Security](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#open-source-security)
7. [Differential Privacy](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#differential-privacy)
8. [Kubernetes](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#kubernetes)
9. [Machine Learning](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#machine-learning)
10. [IoT Protocols](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#iot-protocols)
11. [Operating systems (OS)](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#operating-systems)
12. [Middleware](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#middleware)
13. [Node Flow editors](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#node-flow-editors)
14. [Toolkits](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#toolkits)
15. [Data visualization](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#data-visualization)
16. [Search](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#search)
17. [Hardware](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#hardware)
18. [In-memory data grids](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#in-memory-data-grids)
19. [Home automation](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#home-automation)
20. [Robotics](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#robotics)
21. [Mesh networks](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#mesh-networks)
22. [Node.js Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#nodejs-development)
23. [Java Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#java-development)
24. [Python Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#python-development)
25. [Rust Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#rust-development)
26. [Swift Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#swift-development)
# IoT Learning Resources
[Microsoft Certified: Azure IoT Developer Specialty](https://docs.microsoft.com/en-us/learn/certifications/azure-iot-developer-specialty)
[AWS Internet of Things Foundation Series Training](https://www.aws.training/Details/Curriculum?id=27289)
[Google’s Internet of Things (IoT)](https://developers.google.com/iot/)
[Internet Of Things Courses from Udemy](https://www.udemy.com/topic/internet-of-things/)
[IoT (Internet of Things) Courses from edX](https://www.edx.org/learn/iot-internet-of-things)
[IoT (Internet of Things) Courses from Coursera](https://www.coursera.org/courses?languages=en&query=iot)
# IoT Tools
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Azure IoT Tools](https://developer.microsoft.com/en-us/windows/iot/) is a collection of Microsoft-managed cloud services that connect, monitor, and control billions of IoT assets. In simpler terms, an IoT solution is made up of one or more IoT devices that communicate with one or more back-end services hosted in the cloud.
[AWS IoT Tools](https://aws.amazon.com/iot/) has broad and deep IoT services, from the edge to the cloud. Along with IoT analytics that enables you to apply machine learning to your IoT data with hosted Jupyter Notebooks. You can directly connect your IoT data to the notebook and build, train, and execute models right from the AWS IoT Analytics console without having to manage any of the underlying infrastructure.
[Google Cloud IoT](https://cloud.google.com/solutions/iot/) is a complete set of tools to connect, process, store, and analyze data both at the edge and in the cloud.
[DeviceHive](https://www.devicehive.com) is a free, highly scalable open-source IoT platform for data collection, processing and analysis, visualization, and device management with the broad range of integration options.
[Distributed Services Architecture (DSA)](https://github.com/IOT-DSA) is an open source IoT platform that facilitates device inter-communication, logic and applications at every layer of the Internet of Things infrastructure. The objective is to unify the disparate devices, services and applications into a structured and adaptable real-time data model.
[IoTivity](https://iotivity.org) is an open source software framework enabling seamless device-to-device connectivity to address the emerging needs of the Internet of Things.
[InfluxDB](https://www.influxdata.com) is an open source time series database, purpose-built by InfluxData for monitoring metrics and events, provides real-time visibility into stacks, sensors, and systems. Use InfluxDB to capture, analyze, and store millions of points per second, meet demanding SLA's, and chart a path to automation.
[Eclipse IoT Project](https://projects.eclipse.org/projects/iot) provides open source technology that will be used to build IoT solutions for industry and consumers.
[M2MLabs MainSpring](http://www.m2mlabs.com/) is an application framework for building machine-to-machine applications like vehicle tracking or machine remote montoring. In such applications typically a remote device equipped with sensors (e.g. gps, temperature, pressure) and actors communicates with a server application that is running the device communication protocol, device configuration, storage of data sent by the devices as well as the application business logic and the presentation layer.
[EdgeX Foundry](https://www.edgexfoundry.org) is a vendor-neutral project under the Linux Foundation. The initiative is aligned around a common goal: the simplification and standardization of the foundation for edge computing architectures in the Industrial IoT market, while still allowing the ecosystem to add significant value.
[The Open Connectivity Foundation](https://openconnectivity.org) is dedicated to ensuring secure interoperability for consumers, businesses and industries by delivering a standard communications platform, a bridging specification, an open source implementation and a certification program allowing devices to communicate regardless of form factor, operating system, service provider, transport technology or ecosystem.
[Eclipse Foundation](https://www.eclipse.org) provides our global community of individuals and organizations with a mature, scalable and commercially-friendly environment for open source software collaboration and innovation.
[Open Source Hardware Association (OSHWA)](https://www.oshwa.org) is a non-profit organization that advocates for open-source hardware. It aims to act as a hub of open source hardware activity of all types while actively cooperating with other initiatives such as the TAPR Open Hardware License, open-source development groups at CERN, and the Open Source Initiative (OSI).
# Networking
[Back to the Top](https://github.com/mikeroyal/IoT-Guide#table-of-contents)
## Networking Tools & Concepts
[cURL](https://curl.se/) is a computer software project providing a library and command-line tool for transferring data using various network protocols(HTTP, HTTPS, FTP, FTPS, SCP, SFTP, TFTP, DICT, TELNET, LDAP LDAPS, MQTT, POP3, POP3S, RTMP, RTMPS, RTSP, SCP, SFTP, SMB, SMBS, SMTP or SMTPS). cURL is also used in cars, television sets, routers, printers, audio equipment, mobile phones, tablets, settop boxes, media players and is the Internet transfer engine for thousands of software applications in over ten billion installations.
[cURL Fuzzer](https://github.com/curl/curl-fuzzer) is a quality assurance testing for the curl project.
[DoH](https://github.com/curl/doh) is a stand-alone application for DoH (DNS-over-HTTPS) name resolves and lookups.
[Authelia](https://www.authelia.com/) is an open-source highly-available authentication server providing single sign-on capability and two-factor authentication to applications running behind [NGINX](https://nginx.org/en/).
[nginx(engine x)](https://nginx.org/en/) is an HTTP and reverse proxy server, a mail proxy server, and a generic TCP/UDP proxy server, originally written by Igor Sysoev.
[Proxmox Virtual Environment(VE)](https://www.proxmox.com/en/) is a complete open-source platform for enterprise virtualization. It inlcudes a built-in web interface that you can easily manage VMs and containers, software-defined storage and networking, high-availability clustering, and multiple out-of-the-box tools on a single solution.
[Wireshark](https://www.wireshark.org/) is a very popular network protocol analyzer that is commonly used for network troubleshooting, analysis, and communications protocol development. Learn more about the other useful [Wireshark Tools](https://wiki.wireshark.org/Tools) available.
[HTTPie](https://github.com/httpie/httpie) is a command-line HTTP client. Its goal is to make CLI interaction with web services as human-friendly as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers.
[HTTPStat](https://github.com/reorx/httpstat) is a tool that visualizes curl statistics in a simple layout.
[Wuzz](https://github.com/asciimoo/wuzz) is an interactive cli tool for HTTP inspection. It can be used to inspect/modify requests copied from the browser's network inspector with the "copy as cURL" feature.
[Websocat](https://github.com/vi/websocat) is a ommand-line client for WebSockets, like netcat (or curl) for ws:// with advanced socat-like functions.
• Connection: In networking, a connection refers to pieces of related information that are transferred through a network. This generally infers that a connection is built before the data transfer (by following the procedures laid out in a protocol) and then is deconstructed at the at the end of the data transfer.
• Packet: A packet is, generally speaking, the most basic unit that is transferred over a network. When communicating over a network, packets are the envelopes that carry your data (in pieces) from one end point to the other.
Packets have a header portion that contains information about the packet including the source and destination, timestamps, network hops. The main portion of a packet contains the actual data being transferred. It is sometimes called the body or the payload.
• Network Interface: A network interface can refer to any kind of software interface to networking hardware. For instance, if you have two network cards in your computer, you can control and configure each network interface associated with them individually.
A network interface may be associated with a physical device, or it may be a representation of a virtual interface. The "loop-back" device, which is a virtual interface to the local machine, is an example of this.
• LAN: LAN stands for "local area network". It refers to a network or a portion of a network that is not publicly accessible to the greater internet. A home or office network is an example of a LAN.
• WAN: WAN stands for "wide area network". It means a network that is much more extensive than a LAN. While WAN is the relevant term to use to describe large, dispersed networks in general, it is usually meant to mean the internet, as a whole.
If an interface is connected to the WAN, it is generally assumed that it is reachable through the internet.
• Protocol: A protocol is a set of rules and standards that basically define a language that devices can use to communicate. There are a great number of protocols in use extensively in networking, and they are often implemented in different layers.
Some low level protocols are TCP, UDP, IP, and ICMP. Some familiar examples of application layer protocols, built on these lower protocols, are HTTP (for accessing web content), SSH, TLS/SSL, and FTP.
• Port: A port is an address on a single machine that can be tied to a specific piece of software. It is not a physical interface or location, but it allows your server to be able to communicate using more than one application.
• Firewall: A firewall is a program that decides whether traffic coming into a server or going out should be allowed. A firewall usually works by creating rules for which type of traffic is acceptable on which ports. Generally, firewalls block ports that are not used by a specific application on a server.
• NAT: Network address translation is a way to translate requests that are incoming into a routing server to the relevant devices or servers that it knows about in the LAN. This is usually implemented in physical LANs as a way to route requests through one IP address to the necessary backend servers.
• VPN: Virtual private network is a means of connecting separate LANs through the internet, while maintaining privacy. This is used as a means of connecting remote systems as if they were on a local network, often for security reasons.
## Network Layers
While networking is often discussed in terms of topology in a horizontal way, between hosts, its implementation is layered in a vertical fashion throughout a computer or network. This means is that there are multiple technologies and protocols that are built on top of each other in order for communication to function more easily. Each successive, higher layer abstracts the raw data a little bit more, and makes it simpler to use for applications and users. It also allows you to leverage lower layers in new ways without having to invest the time and energy to develop the protocols and applications that handle those types of traffic.
As data is sent out of one machine, it begins at the top of the stack and filters downwards. At the lowest level, actual transmission to another machine takes place. At this point, the data travels back up through the layers of the other computer. Each layer has the ability to add its own "wrapper" around the data that it receives from the adjacent layer, which will help the layers that come after decide what to do with the data when it is passed off.
One method of talking about the different layers of network communication is the OSI model. OSI stands for Open Systems Interconnect.This model defines seven separate layers. The layers in this model are:
• Application: The application layer is the layer that the users and user-applications most often interact with. Network communication is discussed in terms of availability of resources, partners to communicate with, and data synchronization.
• Presentation: The presentation layer is responsible for mapping resources and creating context. It is used to translate lower level networking data into data that applications expect to see.
• Session: The session layer is a connection handler. It creates, maintains, and destroys connections between nodes in a persistent way.
• Transport: The transport layer is responsible for handing the layers above it a reliable connection. In this context, reliable refers to the ability to verify that a piece of data was received intact at the other end of the connection. This layer can resend information that has been dropped or corrupted and can acknowledge the receipt of data to remote computers.
• Network: The network layer is used to route data between different nodes on the network. It uses addresses to be able to tell which computer to send information to. This layer can also break apart larger messages into smaller chunks to be reassembled on the opposite end.
• Data Link: This layer is implemented as a method of establishing and maintaining reliable links between different nodes or devices on a network using existing physical connections.
• Physical: The physical layer is responsible for handling the actual physical devices that are used to make a connection. This layer involves the bare software that manages physical connections as well as the hardware itself (like Ethernet).
The TCP/IP model, more commonly known as the Internet protocol suite, is another layering model that is simpler and has been widely adopted.It defines the four separate layers, some of which overlap with the OSI model:
• Application: In this model, the application layer is responsible for creating and transmitting user data between applications. The applications can be on remote systems, and should appear to operate as if locally to the end user.
The communication takes place between peers network.
• Transport: The transport layer is responsible for communication between processes. This level of networking utilizes ports to address different services. It can build up unreliable or reliable connections depending on the type of protocol used.
• Internet: The internet layer is used to transport data from node to node in a network. This layer is aware of the endpoints of the connections, but does not worry about the actual connection needed to get from one place to another. IP addresses are defined in this layer as a way of reaching remote systems in an addressable manner.
• Link: The link layer implements the actual topology of the local network that allows the internet layer to present an addressable interface. It establishes connections between neighboring nodes to send data.
### Interfaces
**Interfaces** are networking communication points for your computer. Each interface is associated with a physical or virtual networking device. Typically, your server will have one configurable network interface for each Ethernet or wireless internet card you have. In addition, it will define a virtual network interface called the "loopback" or localhost interface. This is used as an interface to connect applications and processes on a single computer to other applications and processes. You can see this referenced as the "lo" interface in many tools.
## Network Protocols
Networking works by piggybacks on a number of different protocols on top of each other. In this way, one piece of data can be transmitted using multiple protocols encapsulated within one another.
**Media Access Control(MAC)** is a communications protocol that is used to distinguish specific devices. Each device is supposed to get a unique MAC address during the manufacturing process that differentiates it from every other device on the internet. Addressing hardware by the MAC address allows you to reference a device by a unique value even when the software on top may change the name for that specific device during operation. Media access control is one of the only protocols from the link layer that you are likely to interact with on a regular basis.
**The IP protocol** is one of the fundamental protocols that allow the internet to work. IP addresses are unique on each network and they allow machines to address each other across a network. It is implemented on the internet layer in the IP/TCP model. Networks can be linked together, but traffic must be routed when crossing network boundaries. This protocol assumes an unreliable network and multiple paths to the same destination that it can dynamically change between. There are a number of different implementations of the protocol. The most common implementation today is IPv4, although IPv6 is growing in popularity as an alternative due to the scarcity of IPv4 addresses available and improvements in the protocols capabilities.
**ICMP: internet control message protocol** is used to send messages between devices to indicate the availability or error conditions. These packets are used in a variety of network diagnostic tools, such as ping and traceroute. Usually ICMP packets are transmitted when a packet of a different kind meets some kind of a problem. Basically, they are used as a feedback mechanism for network communications.
**TCP: Transmission control protocol** is implemented in the transport layer of the IP/TCP model and is used to establish reliable connections. TCP is one of the protocols that encapsulates data into packets. It then transfers these to the remote end of the connection using the methods available on the lower layers. On the other end, it can check for errors, request certain pieces to be resent, and reassemble the information into one logical piece to send to the application layer. The protocol builds up a connection prior to data transfer using a system called a three-way handshake. This is a way for the two ends of the communication to acknowledge the request and agree upon a method of ensuring data reliability. After the data has been sent, the connection is torn down using a similar four-way handshake. TCP is the protocol of choice for many of the most popular uses for the internet, including WWW, FTP, SSH, and email. It is safe to say that the internet we know today would not be here without TCP.
**UDP: User datagram protocol** is a popular companion protocol to TCP and is also implemented in the transport layer. The fundamental difference between UDP and TCP is that UDP offers unreliable data transfer. It does not verify that data has been received on the other end of the connection. This might sound like a bad thing, and for many purposes, it is. However, it is also extremely important for some functions. It’s not required to wait for confirmation that the data was received and forced to resend data, UDP is much faster than TCP. It does not establish a connection with the remote host, it simply fires off the data to that host and doesn't care if it is accepted or not. Since UDP is a simple transaction, it is useful for simple communications like querying for network resources. It also doesn't maintain a state, which makes it great for transmitting data from one machine to many real-time clients. This makes it ideal for VOIP, games, and other applications that cannot afford delays.
**HTTP: Hypertext transfer protocol** is a protocol defined in the application layer that forms the basis for communication on the web. HTTP defines a number of functions that tell the remote system what you are requesting. For instance, GET, POST, and DELETE all interact with the requested data in a different way.
**FTP: File transfer protocol** is in the application layer and provides a way of transferring complete files from one host to another. It is inherently insecure, so it is not recommended for any externally facing network unless it is implemented as a public, download-only resource.
**DNS: Domain name system** is an application layer protocol used to provide a human-friendly naming mechanism for internet resources. It is what ties a domain name to an IP address and allows you to access sites by name in your browser.
**SSH: Secure shell** is an encrypted protocol implemented in the application layer that can be used to communicate with a remote server in a secure way. Many additional technologies are built around this protocol because of its end-to-end encryption and ubiquity. There are many other protocols that we haven't covered that are equally important. However, this should give you a good overview of some of the fundamental technologies that make the internet and networking possible.
[REST(REpresentational State Transfer)](https://www.codecademy.com/articles/what-is-rest) is an architectural style for providing standards between computer systems on the web, making it easier for systems to communicate with each other.
[JSON Web Token (JWT)](https://jwt.io) is a compact URL-safe means of representing claims to be transferred between two parties. The claims in a JWT are encoded as a JSON object that is digitally signed using JSON Web Signature (JWS).
[OAuth 2.0](https://oauth.net/2/) is an open source authorization framework that enables applications to obtain limited access to user accounts on an HTTP service, such as Amazon, Google, Facebook, Microsoft, Twitter GitHub, and DigitalOcean. It works by delegating user authentication to the service that hosts the user account, and authorizing third-party applications to access the user account.
# Databases
[Back to the Top](https://github.com/mikeroyal/IoT-Guide#table-of-contents)
## SQL/NoSQL Learning Resources
[SQL](https://en.wikipedia.org/wiki/SQL) is a standard language for storing, manipulating and retrieving data in relational databases.
[NoSQL](https://www.ibm.com/cloud/blog/sql-vs-nosql) is a database that is interchangeably referred to as "nonrelational, or "non-SQL" to highlight that the database can handle huge volumes of rapidly changing, unstructured data in different ways than a relational (SQL-based) database with rows and tables.
[Transact-SQL(T-SQL)](https://docs.microsoft.com/en-us/sql/t-sql/language-reference) is a Microsoft extension of SQL with all of the tools and applications communicating to a SQL database by sending T-SQL commands.
[Introduction to Transact-SQL](https://docs.microsoft.com/en-us/learn/modules/introduction-to-transact-sql/)
[SQL Tutorial by W3Schools](https://www.w3schools.com/sql/)
[Learn SQL Skills Online from Coursera](https://www.coursera.org/courses?query=sql)
[SQL Courses Online from Udemy](https://www.udemy.com/topic/sql/)
[SQL Online Training Courses from LinkedIn Learning](https://www.linkedin.com/learning/topics/sql)
[Learn SQL For Free from Codecademy](https://www.codecademy.com/learn/learn-sql)
[GitLab's SQL Style Guide](https://about.gitlab.com/handbook/business-ops/data-team/platform/sql-style-guide/)
[OracleDB SQL Style Guide Basics](https://oracle.readthedocs.io/en/latest/sql/basics/style-guide.html)
[Tableau CRM: BI Software and Tools](https://www.salesforce.com/products/crm-analytics/overview/)
[Databases on AWS](https://aws.amazon.com/products/databases/)
[Best Practices and Recommendations for SQL Server Clustering in AWS EC2.](https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/aws-sql-clustering.html)
[Connecting from Google Kubernetes Engine to a Cloud SQL instance.](https://cloud.google.com/sql/docs/mysql/connect-kubernetes-engine)
[Educational Microsoft Azure SQL resources](https://docs.microsoft.com/en-us/sql/sql-server/educational-sql-resources?view=sql-server-ver15)
[MySQL Certifications](https://www.mysql.com/certification/)
[SQL vs. NoSQL Databases: What's the Difference?](https://www.ibm.com/cloud/blog/sql-vs-nosql)
[What is NoSQL?](https://aws.amazon.com/nosql/)
## SQL/NoSQL Tools and Databases
[Netdata](https://github.com/netdata/netdata) is high-fidelity infrastructure monitoring and troubleshooting, real-time monitoring Agent collects thousands of metrics from systems, hardware, containers, and applications with zero configuration. It runs permanently on all your physical/virtual servers, containers, cloud deployments, and edge/IoT devices, and is perfectly safe to install on your systems mid-incident without any preparation.
[Azure Data Studio](https://github.com/Microsoft/azuredatastudio) is an open source data management tool that enables working with SQL Server, Azure SQL DB and SQL DW from Windows, macOS and Linux.
[Azure SQL Database](https://azure.microsoft.com/en-us/services/sql-database/) is the intelligent, scalable, relational database service built for the cloud. It’s evergreen and always up to date, with AI-powered and automated features that optimize performance and durability for you. Serverless compute and Hyperscale storage options automatically scale resources on demand, so you can focus on building new applications without worrying about storage size or resource management.
[Azure SQL Managed Instance](https://azure.microsoft.com/en-us/services/azure-sql/sql-managed-instance/) is a fully managed SQL Server Database engine instance that's hosted in Azure and placed in your network. This deployment model makes it easy to lift and shift your on-premises applications to the cloud with very few application and database changes. Managed instance has split compute and storage components.
[Azure Synapse Analytics](https://azure.microsoft.com/en-us/services/synapse-analytics/) is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources at scale. It brings together the best of the SQL technologies used in enterprise data warehousing, Spark technologies used in big data analytics, and Pipelines for data integration and ETL/ELT.
[MSSQL for Visual Studio Code](https://marketplace.visualstudio.com/items?itemName=ms-mssql.mssql) is an extension for developing Microsoft SQL Server, Azure SQL Database and SQL Data Warehouse everywhere with a rich set of functionalities.
[SQL Server Data Tools (SSDT)](https://docs.microsoft.com/en-us/sql/ssdt/download-sql-server-data-tools-ssdt) is a development tool for building SQL Server relational databases, Azure SQL Databases, Analysis Services (AS) data models, Integration Services (IS) packages, and Reporting Services (RS) reports. With SSDT, a developer can design and deploy any SQL Server content type with the same ease as they would develop an application in Visual Studio or Visual Studio Code.
[Bulk Copy Program](https://docs.microsoft.com/en-us/sql/tools/bcp-utility) is a command-line tool that comes with Microsoft SQL Server. BCP, allows you to import and export large amounts of data in and out of SQL Server databases quickly snd efficeiently.
[SQL Server Migration Assistant](https://www.microsoft.com/en-us/download/details.aspx?id=54258) is a tool from Microsoft that simplifies database migration process from Oracle to SQL Server, Azure SQL Database, Azure SQL Database Managed Instance and Azure SQL Data Warehouse.
[SQL Server Integration Services](https://docs.microsoft.com/en-us/sql/integration-services/sql-server-integration-services?view=sql-server-ver15) is a development platform for building enterprise-level data integration and data transformations solutions. Use Integration Services to solve complex business problems by copying or downloading files, loading data warehouses, cleansing and mining data, and managing SQL Server objects and data.
[SQL Server Business Intelligence(BI)](https://www.microsoft.com/en-us/sql-server/sql-business-intelligence) is a collection of tools in Microsoft's SQL Server for transforming raw data into information businesses can use to make decisions.
[Tableau](https://www.tableau.com/) is a Data Visualization software used in relational databases, cloud databases, and spreadsheets. Tableau was acquired by [Salesforce in August 2019](https://investor.salesforce.com/press-releases/press-release-details/2019/Salesforce-Completes-Acquisition-of-Tableau/default.aspx).
[DataGrip](https://www.jetbrains.com/datagrip/) is a professional DataBase IDE developed by Jet Brains that provides context-sensitive code completion, helping you to write SQL code faster. Completion is aware of the tables structure, foreign keys, and even database objects created in code you're editing.
[RStudio](https://rstudio.com/) is an integrated development environment for R and Python, with a console, syntax-highlighting editor that supports direct code execution, and tools for plotting, history, debugging and workspace management.
[MySQL](https://www.mysql.com/) is a fully managed database service to deploy cloud-native applications using the world's most popular open source database.
[PostgreSQL](https://www.postgresql.org/) is a powerful, open source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance.
[Amazon DynamoDB](https://aws.amazon.com/dynamodb/) is a key-value and document database that delivers single-digit millisecond performance at any scale. It is a fully managed, multiregion, multimaster, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications.
[Apache Cassandra™](https://cassandra.apache.org/) is an open source NoSQL distributed database trusted by thousands of companies for scalability and high availability without compromising performance. Cassandra provides linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data.
[Apache HBase™](https://hbase.apache.org/) is an open-source, NoSQL, distributed big data store. It enables random, strictly consistent, real-time access to petabytes of data. HBase is very effective for handling large, sparse datasets. HBase serves as a direct input and output to the Apache MapReduce framework for Hadoop, and works with Apache Phoenix to enable SQL-like queries over HBase tables.
[Hadoop Distributed File System (HDFS)](https://www.ibm.com/analytics/hadoop/hdfs) is a distributed file system that handles large data sets running on commodity hardware. It is used to scale a single Apache Hadoop cluster to hundreds (and even thousands) of nodes. HDFS is one of the major components of Apache Hadoop, the others being [MapReduce](https://www.ibm.com/analytics/hadoop/mapreduce) and [YARN](https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/YARN.html).
[Apache Mesos](http://mesos.apache.org/) is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other frameworks on a dynamically shared pool of nodes.
[Apache Spark](https://spark.apache.org/) is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
[ElasticSearch](https://www.elastic.co/) is a search engine based on the Lucene library. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents. Elasticsearch is developed in Java.
[Logstash](https://www.elastic.co/products/logstash) is a tool for managing events and logs. When used generically, the term encompasses a larger system of log collection, processing, storage and searching activities.
[Kibana](https://www.elastic.co/products/kibana) is an open source data visualization plugin for Elasticsearch. It provides visualization capabilities on top of the content indexed on an Elasticsearch cluster. Users can create bar, line and scatter plots, or pie charts and maps on top of large volumes of data.
[Trino](https://trino.io/) is a Distributed SQL query engine for big data. It is able to tremendously speed up [ETL processes](https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl), allow them all to use standard SQL statement, and work with numerous data sources and targets all in the same system.
[Extract, transform, and load (ETL)](https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store.
[Redis(REmote DIctionary Server)](https://redis.io/) is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. It provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
[FoundationDB](https://www.foundationdb.org/) is an open source distributed database designed to handle large volumes of structured data across clusters of commodity servers. It organizes data as an ordered key-value store and employs ACID transactions for all operations. It is especially well-suited for read/write workloads but also has excellent performance for write-intensive workloads. FoundationDB was acquired by [Apple in 2015](https://techcrunch.com/2015/03/24/apple-acquires-durable-database-company-foundationdb/).
[IBM DB2](https://www.ibm.com/analytics/db2) is a collection of hybrid data management products offering a complete suite of AI-empowered capabilities designed to help you manage both structured and unstructured data on premises as well as in private and public cloud environments. Db2 is built on an intelligent common SQL engine designed for scalability and flexibility.
[MongoDB](https://www.mongodb.com/) is a document database meaning it stores data in JSON-like documents.
[OracleDB](https://www.oracle.com/database/) is a powerful fully managed database helps developers manage business-critical data with the highest availability, reliability, and security.
[MariaDB](https://mariadb.com/) is an enterprise open source database solution for modern, mission-critical applications.
[SQLite](https://sqlite.org/index.html) is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine.SQLite is the most used database engine in the world. SQLite is built into all mobile phones and most computers and comes bundled inside countless other applications that people use every day.
[SQLite Database Browser](https://sqlitebrowser.org/) is an open source SQL tool that allows users to create, design and edits SQLite database files. It lets users show a log of all the SQL commands that have been issued by them and by the application itself.
[InfluxDB](https://www.influxdata.com/) is an open source time series platform. This includes APIs for storing and querying data, processing it in the background for [ETL](https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl) or monitoring and alerting purposes, user dashboards, Internet of Things sensor data, and visualizing and exploring the data and more. It also has support for processing data from [Graphite](http://graphiteapp.org/).
[Atlas](https://github.com/Netflix/atlas) is an in-memory dimensional [time series database](https://en.wikipedia.org/wiki/Time_series_database).
[CouchbaseDB](https://www.couchbase.com/) is an open source distributed [multi-model NoSQL document-oriented database](https://en.wikipedia.org/wiki/Multi-model_database). It creates a key-value store with managed cache for sub-millisecond data operations, with purpose-built indexers for efficient queries and a powerful query engine for executing SQL queries.
[dbWatch](https://www.dbwatch.com/) is a complete database monitoring/management solution for SQL Server, Oracle, PostgreSQL, Sybase, MySQL and Azure. Designed for proactive management and automation of routine maintenance in large scale on-premise, hybrid/cloud database environments.
[Cosmos DB Profiler](https://hibernatingrhinos.com/products/cosmosdbprof) is a real-time visual debugger allowing a development team to gain valuable insight and perspective into their usage of Cosmos DB database. It identifies over a dozen suspicious behaviors from your application’s interaction with Cosmos DB.
[Adminer](https://www.adminer.org/) is an SQL management client tool for managing databases, tables, relations, indexes, users. Adminer has support for all the popular database management systems such as MySQL, MariaDB, PostgreSQL, SQLite, MS SQL, Oracle, Firebird, SimpleDB, Elasticsearch and MongoDB.
[DBeaver](https://dbeaver.io/) is an open source database tool for developers and database administrators. It offers supports for JDBC compliant databases such as MySQL, Oracle, IBM DB2, SQL Server, Firebird, SQLite, Sybase, Teradata, Firebird, Apache Hive, Phoenix, and Presto.
[DbVisualizer](https://dbvis.com/) is a SQL management tool that allows users to manage a wide range of databases such as Oracle, Sybase, SQL Server, MySQL, H3, and SQLite.
[AppDynamics Database](https://www.appdynamics.com/supported-technologies/database) is a management product for Microsoft SQL Server. With AppDynamics you can monitor and trend key performance metrics such as resource consumption, database objects, schema statistics and more, allowing you to proactively tune and fix issues in a High-Volume Production Environment.
[Toad](https://www.quest.com/toad/) is a SQL Server DBMS toolset developed by Quest. It increases productivity by using extensive automation, intuitive workflows, and built-in expertise. This SQL management tool resolve issues, manage change and promote the highest levels of code quality for both relational and non-relational databases.
[Lepide SQL Server](https://www.lepide.com/sql-storage-manager/) is an open source storage manager utility to analyse the performance of SQL Servers. It provides a complete overview of all configuration and permission changes being made to your SQL Server environment through an easy-to-use, graphical user interface.
[Sequel Pro](https://sequelpro.com/) is a fast MacOS database management tool for working with MySQL. This SQL management tool helpful for interacting with your database by easily to adding new databases, new tables, and new rows.
# Telco 5G
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
**VMware Cloud First Approach. Source: [VMware](https://www.vmware.com/products/telco-cloud-automation.html).**
**VMware Telco Cloud Automation Components. Source: [VMware](https://www.vmware.com/products/telco-cloud-automation.html).**
## Telco Learning Resources
[HPE(Hewlett Packard Enterprise) Telco Blueprints overview](https://techhub.hpe.com/eginfolib/servers/docs/Telco/Blueprints/infocenter/index.html#GUID-9906A227-C1FB-4FD5-A3C3-F3B72EC81CAB.html)
[Network Functions Virtualization Infrastructure (NFVI) by Cisco](https://www.cisco.com/c/en/us/solutions/service-provider/network-functions-virtualization-nfv-infrastructure/index.html)
[Introduction to vCloud NFV Telco Edge from VMware](https://docs.vmware.com/en/VMware-vCloud-NFV-OpenStack-Edition/3.1/vloud-nfv-edge-reference-arch-31/GUID-744C45F1-A8D5-4523-9E5E-EAF6336EE3A0.html)
[VMware Telco Cloud Automation(TCA) Architecture Overview](https://docs.vmware.com/en/VMware-Telco-Cloud-Platform-5G-Edition/1.0/telco-cloud-platform-5G-edition-reference-architecture/GUID-C19566B3-F42D-4351-BA55-DE70D55FB0DD.html)
[5G Telco Cloud from VMware](https://telco.vmware.com/)
[Maturing OpenStack Together To Solve Telco Needs from Red Hat](https://www.redhat.com/cms/managed-files/4.Nokia%20CloudBand%20&%20Red%20Hat%20-%20Maturing%20Openstack%20together%20to%20solve%20Telco%20needs%20Ehud%20Malik,%20Senior%20PLM,%20Nokia%20CloudBand.pdf)
[Red Hat telco ecosystem program](https://connect.redhat.com/en/programs/telco-ecosystem)
[OpenStack for Telcos by Canonical](https://ubuntu.com/blog/openstack-for-telcos-by-canonical)
[Open source NFV platform for 5G from Ubuntu](https://ubuntu.com/telco)
[Understanding 5G Technology from Verizon](https://www.verizon.com/5g/)
[Verizon and Unity partner to enable 5G & MEC gaming and enterprise applications](https://www.verizon.com/about/news/verizon-unity-partner-5g-mec-gaming-enterprise)
[Understanding 5G Technology from Intel](https://www.intel.com/content/www/us/en/wireless-network/what-is-5g.html)
[Understanding 5G Technology from Qualcomm](https://www.qualcomm.com/invention/5g/what-is-5g)
[Telco Acceleration with Xilinx](https://www.xilinx.com/applications/wired-wireless/telco.html)
[VIMs on OSM Public Wiki](https://osm.etsi.org/wikipub/index.php/VIMs)
[Amazon EC2 Overview and Networking Introduction for Telecom Companies](https://docs.aws.amazon.com/whitepapers/latest/ec2-networking-for-telecom/ec2-networking-for-telecom.pdf)
[Citrix Certified Associate – Networking(CCA-N)](http://training.citrix.com/cms/index.php/certification/networking/)
[Citrix Certified Professional – Virtualization(CCP-V)](https://www.globalknowledge.com/us-en/training/certification-prep/brands/citrix/section/virtualization/citrix-certified-professional-virtualization-ccp-v/)
[CCNP Routing and Switching](https://learningnetwork.cisco.com/s/ccnp-enterprise)
[Certified Information Security Manager(CISM)](https://www.isaca.org/credentialing/cism)
[Wireshark Certified Network Analyst (WCNA)](https://www.wiresharktraining.com/certification.html)
[Juniper Networks Certification Program Enterprise (JNCP)](https://www.juniper.net/us/en/training/certification/)
[Cloud Native Computing Foundation Training and Certification Program](https://www.cncf.io/certification/training/)
## Tools
[Open Stack](https://www.openstack.org/) is an open source cloud platform, deployed as infrastructure-as-a-service (IaaS) to orchestrate data center operations on bare metal, private cloud hardware, public cloud resources, or both (hybrid/multi-cloud architecture). OpenStack includes advance use of virtualization & SDN for network traffic optimization to handle the core cloud-computing services of compute, networking, storage, identity, and image services.
[StarlingX](https://www.starlingx.io/) is a complete cloud infrastructure software stack for the edge used by the most demanding applications in industrial IOT, telecom, video delivery and other ultra-low latency use cases.
[Airship](https://www.airshipit.org/) is a collection of open source tools for automating cloud provisioning and management. Airship provides a declarative framework for defining and managing the life cycle of open infrastructure tools and the underlying hardware.
[Network functions virtualization (NFV)](https://www.vmware.com/topics/glossary/content/network-functions-virtualization-nfv) is the replacement of network appliance hardware with virtual machines. The virtual machines use a hypervisor to run networking software and processes such as routing and load balancing. NFV allows for the separation of communication services from dedicated hardware, such as routers and firewalls. This separation means network operations can provide new services dynamically and without installing new hardware. Deploying network components with network functions virtualization only takes hours compared to months like with traditional networking solutions.
[Software Defined Networking (SDN)](https://www.vmware.com/topics/glossary/content/software-defined-networking) is an approach to networking that uses software-based controllers or application programming interfaces (APIs) to communicate with underlying hardware infrastructure and direct traffic on a network. This model differs from that of traditional networks, which use dedicated hardware devices (routers and switches) to control network traffic.
[Virtualized Infrastructure Manager (VIM)](https://www.cisco.com/c/en/us/td/docs/net_mgmt/network_function_virtualization_Infrastructure/3_2_2/install_guide/Cisco_VIM_Install_Guide_3_2_2/Cisco_VIM_Install_Guide_3_2_2_chapter_00.html) is a service delivery and reduce costs with high performance lifecycle management Manage the full lifecycle of the software and hardware comprising your NFV infrastructure (NFVI), and maintaining a live inventory and allocation plan of both physical and virtual resources.
[Management and Orchestration(MANO)](https://www.etsi.org/technologies/open-source-mano) is an ETSI-hosted initiative to develop an Open Source NFV Management and Orchestration (MANO) software stack aligned with ETSI NFV. Two of the key components of the ETSI NFV architectural framework are the NFV Orchestrator and VNF Manager, known as NFV MANO.
[Magma](https://www.magmacore.org/) is an open source software platform that gives network operators an open, flexible and extendable mobile core network solution. Their mission is to connect the world to a faster network by enabling service providers to build cost-effective and extensible carrier-grade networks. Magma is 3GPP generation (2G, 3G, 4G or upcoming 5G networks) and access network agnostic (cellular or WiFi). It can flexibly support a radio access network with minimal development and deployment effort.
[OpenRAN](https://open-ran.org/) is an intelligent Radio Access Network(RAN) integrated on general purpose platforms with open interface between software defined functions. Open RANecosystem enables enormous flexibility and interoperability with a complete openess to multi-vendor deployments.
[Open vSwitch(OVS)](https://www.openvswitch.org/)is an open source production quality, multilayer virtual switch licensed under the open source Apache 2.0 license. It is designed to enable massive network automation through programmatic extension, while still supporting standard management interfaces and protocols (NetFlow, sFlow, IPFIX, RSPAN, CLI, LACP, 802.1ag).
[Edge](https://www.ibm.com/cloud/what-is-edge-computing) is a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers. This proximity to data at its source can deliver strong business benefits, including faster insights, improved response times and better bandwidth availability.
[Multi-access edge computing (MEC)](https://www.etsi.org/technologies/multi-access-edge-computing) is an Industry Specification Group (ISG) within ETSI to create a standardized, open environment which will allow the efficient and seamless integration of applications from vendors, service providers, and third-parties across multi-vendor Multi-access Edge Computing platforms.
[Virtualized network functions(VNFs)](https://www.juniper.net/documentation/en_US/cso4.1/topics/concept/nsd-vnf-overview.html) is a software application used in a Network Functions Virtualization (NFV) implementation that has well defined interfaces, and provides one or more component networking functions in a defined way. For example, a security VNF provides Network Address Translation (NAT) and firewall component functions.
[Cloud-Native Network Functions(CNF)](https://www.cncf.io/announcements/2020/11/18/cloud-native-network-functions-conformance-launched-by-cncf/) is a network function designed and implemented to run inside containers. CNFs inherit all the cloud native architectural and operational principles including Kubernetes(K8s) lifecycle management, agility, resilience, and observability.
[Physical Network Function(PNF)](https://www.mpirical.com/glossary/pnf-physical-network-function) is a physical network node which has not undergone virtualization. Both PNFs and VNFs (Virtualized Network Functions) can be used to form an overall Network Service.
[Network functions virtualization infrastructure(NFVI)](https://docs.vmware.com/en/VMware-vCloud-NFV/2.0/vmware-vcloud-nfv-reference-architecture-20/GUID-FBEA6C6B-54D8-4A37-87B1-D825F9E0DBC7.html) is the foundation of the overall NFV architecture. It provides the physical compute, storage, and networking hardware that hosts the VNFs. Each NFVI block can be thought of as an NFVI node and many nodes can be deployed and controlled geographically.
# Open Source Security
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Open Source Security Foundation (OpenSSF)](https://openssf.org/) is a cross-industry collaboration that brings together leaders to improve the security of open source software by building a broader community, targeted initiatives, and best practices. The OpenSSF brings together open source security initiatives under one foundation to accelerate work through cross-industry support. Along with the Core Infrastructure Initiative and the Open Source Security Coalition, and will include new working groups that address vulnerability disclosures, security tooling and more.
## Security Standards, Frameworks and Benchmarks
[STIGs Benchmarks - Security Technical Implementation Guides](https://public.cyber.mil/stigs/)
[CIS Benchmarks - CIS Center for Internet Security](https://www.cisecurity.org/cis-benchmarks/)
[NIST - Current FIPS](https://www.nist.gov/itl/current-fips)
[ISO Standards Catalogue](https://www.iso.org/standards.html)
[Common Criteria for Information Technology Security Evaluation (CC)](https://www.commoncriteriaportal.org/cc/) is an international standard (ISO / IEC 15408) for computer security. It allows an objective evaluation to validate that a particular product satisfies a defined set of security requirements.
[ISO 22301](https://www.iso.org/en/contents/data/standard/07/51/75106.html) is the international standard that provides a best-practice framework for implementing an optimised BCMS (business continuity management system).
[ISO27001](https://www.iso.org/isoiec-27001-information-security.html) is the international standard that describes the requirements for an ISMS (information security management system). The framework is designed to help organizations manage their security practices in one place, consistently and cost-effectively.
[ISO 27701](https://www.iso.org/en/contents/data/standard/07/16/71670.html) specifies the requirements for a PIMS (privacy information management system) based on the requirements of ISO 27001.
It is extended by a set of privacy-specific requirements, control objectives and controls. Companies that have implemented ISO 27001 will be able to use ISO 27701 to extend their security efforts to cover privacy management.
[EU GDPR (General Data Protection Regulation)](https://gdpr.eu/) is a privacy and data protection law that supersedes existing national data protection laws across the EU, bringing uniformity by introducing just one main data protection law for companies/organizations to comply with.
[CCPA (California Consumer Privacy Act)](https://www.oag.ca.gov/privacy/ccpa) is a data privacy law that took effect on January 1, 2020 in the State of California. It applies to businesses that collect California residents’ personal information, and its privacy requirements are similar to those of the EU’s GDPR (General Data Protection Regulation).
[Payment Card Industry (PCI) Data Security Standards (DSS)](https://docs.microsoft.com/en-us/microsoft-365/compliance/offering-pci-dss) is a global information security standard designed to prevent fraud through increased control of credit card data.
[SOC 2](https://www.aicpa.org/interestareas/frc/assuranceadvisoryservices/aicpasoc2report.html) is an auditing procedure that ensures your service providers securely manage your data to protect the interests of your comapny/organization and the privacy of their clients.
[NIST CSF](https://www.nist.gov/national-security-standards) is a voluntary framework primarily intended for critical infrastructure organizations to manage and mitigate cybersecurity risk based on existing best practice.
## Security Tools
[SELinux](https://github.com/SELinuxProject/selinux) is a security enhancement to Linux which allows users and administrators more control over access control. Access can be constrained on such variables as which users and applications can access which resources. These resources may take the form of files. Standard Linux access controls, such as file modes (-rwxr-xr-x) are modifiable by the user and the applications which the user runs. Conversely, SELinux access controls are determined by a policy loaded on the system which may not be changed by careless users or misbehaving applications.
[AppArmor](https://www.apparmor.net/) is an effective and easy-to-use Linux application security system. AppArmor proactively protects the operating system and applications from external or internal threats, even zero-day attacks, by enforcing good behavior and preventing both known and unknown application flaws from being exploited. AppArmor supplements the traditional Unix discretionary access control (DAC) model by providing mandatory access control (MAC). It has been included in the mainline Linux kernel since version 2.6.36 and its development has been supported by Canonical since 2009.
[Control Groups(Cgroups)](https://www.redhat.com/sysadmin/cgroups-part-one) is a Linux kernel feature that allows you to allocate resources such as CPU time, system memory, network bandwidth, or any combination of these resources for user-defined groups of tasks (processes) running on a system.
[EarlyOOM](https://github.com/rfjakob/earlyoom) is a daemon for Linux that enables users to more quickly recover and regain control over their system in low-memory situations with heavy swap usage.
[Libgcrypt](https://www.gnupg.org/related_software/libgcrypt/) is a general purpose cryptographic library originally based on code from GnuPG.
[Kali Linux](https://www.kali.org/) is an open source project that is maintained and funded by Offensive Security, a provider of world-class information security training and penetration testing services.
[Pi-hole](https://pi-hole.net/) is a [DNS sinkhole](https://en.wikipedia.org/wiki/DNS_Sinkhole) that protects your devices from unwanted content, without installing any client-side software, intended for use on a private network. It is designed for use on embedded devices with network capability, such as the Raspberry Pi, but it can be used on other machines running Linux and cloud implementations.
[Aircrack-ng](https://www.aircrack-ng.org/) is a network software suite consisting of a detector, packet sniffer, WEP and WPA/WPA2-PSK cracker and analysis tool for 802.11 wireless LANs. It works with any wireless network interface controller whose driver supports raw monitoring mode and can sniff 802.11a, 802.11b and 802.11g traffic.
[Burp Suite](https://portswigger.net/burp) is a leading range of cybersecurity tools.
[KernelCI](https://foundation.kernelci.org/) is a community-based open source distributed test automation system focused on upstream kernel development. The primary goal of KernelCI is to use an open testing philosophy to ensure the quality, stability and long-term maintenance of the Linux kernel.
[Continuous Kernel Integration project](https://github.com/cki-project) helps find bugs in kernel patches before they are commited to an upstram kernel tree. We are team of kernel developers, kernel testers, and automation engineers.
[eBPF](https://ebpf.io) is a revolutionary technology that can run sandboxed programs in the Linux kernel without changing kernel source code or loading kernel modules. By making the Linux kernel programmable, infrastructure software can leverage existing layers, making them more intelligent and feature-rich without continuing to add additional layers of complexity to the system.
[Cilium](https://cilium.io/) uses eBPF to accelerate getting data in and out of L7 proxies such as Envoy, enabling efficient visibility into API protocols like HTTP, gRPC, and Kafka.
[Hubble](https://github.com/cilium/hubble) is a Network, Service & Security Observability for Kubernetes using eBPF.
[Istio](https://istio.io/) is an open platform to connect, manage, and secure microservices. Istio's control plane provides an abstraction layer over the underlying cluster management platform, such as Kubernetes and Mesos.
[Certgen](https://github.com/cilium/certgen) is a convenience tool to generate and store certificates for Hubble Relay mTLS.
[Scapy](https://scapy.net/) is a python-based interactive packet manipulation program & library.
[syzkaller](https://github.com/google/syzkaller) is an unsupervised, coverage-guided kernel fuzzer.
[SchedViz](https://github.com/google/schedviz) is a tool for gathering and visualizing kernel scheduling traces on Linux machines.
[oss-fuzz](https://google.github.io/oss-fuzz/) aims to make common open source software more secure and stable by combining modern fuzzing techniques with scalable, distributed execution.
[OSSEC](https://www.ossec.net/) is a free, open-source host-based intrusion detection system. It performs log analysis, integrity checking, Windows registry monitoring, rootkit detection, time-based alerting, and active response.
[Metasploit Project](https://www.metasploit.com/) is a computer security project that provides information about security vulnerabilities and aids in penetration testing and IDS signature development.
[Wfuzz](https://github.com/xmendez/wfuzz) was created to facilitate the task in web applications assessments and it is based on a simple concept: it replaces any reference to the FUZZ keyword by the value of a given payload.
[Nmap](https://nmap.org/) is a security scanner used to discover hosts and services on a computer network, thus building a "map" of the network.
[Patchwork](https://github.com/getpatchwork/patchwork) is a web-based patch tracking system designed to facilitate the contribution and management of contributions to an open-source project.
[pfSense](https://www.pfsense.org/) is a free and open source firewall and router that also features unified threat management, load balancing, multi WAN, and more.
[Snowpatch](https://github.com/ruscur/snowpatch) is a continuous integration tool for projects using a patch-based, mailing-list-centric git workflow. This workflow is used by a number of well-known open source projects such as the Linux kernel.
[Snort](https://www.snort.org/) is an open-source, free and lightweight network intrusion detection system (NIDS) software for Linux and Windows to detect emerging threats.
[Wireshark](https://www.wireshark.org/) is a free and open-source packet analyzer. It is used for network troubleshooting, analysis, software and communications protocol development, and education.
[OpenSCAP](https://www.open-scap.org/) is U.S. standard maintained by [National Institute of Standards and Technology (NIST)](https://www.nist.gov/). It provides multiple tools to assist administrators and auditors with assessment, measurement, and enforcement of security baselines. OpenSCAP maintains great flexibility and interoperability by reducing the costs of performing security audits. Whether you want to evaluate DISA STIGs, NIST‘s USGCB, or Red Hat’s Security Response Team’s content, all are supported by OpenSCAP.
[Tink](https://github.com/google/tink) is a multi-language, cross-platform, open source library that provides cryptographic APIs that are secure, easy to use correctly, and harder to misuse.
[OWASP](https://www.owasp.org/index.php/Main_Page) is an online community, produces freely-available articles, methodologies, documentation, tools, and technologies in the field of web application security.
[Open Vulnerability and Assessment Language](https://oval.mitre.org/) is a community effort to standardize how to assess and report upon the machine state of computer systems. OVAL includes a language to encode system details, and community repositories of content. Tools and services that use OVAL provide enterprises with accurate, consistent, and actionable information to improve their security.
[ClamAV](https://www.clamav.net/) is an open source antivirus engine for detecting trojans, viruses, malware & other malicious threats.
## Open Source Security Learning Resources
[Microsoft Open Source Software Security](https://www.microsoft.com/en-us/securityengineering/opensource)
[Cloudflare Open Source Security](https://cloudflare.github.io)
[The Seven Properties of Highly Secure Devices](https://www.microsoft.com/en-us/research/publication/seven-properties-highly-secure-devices/)
[How Layer 7 of the Internet Works](https://www.cloudflare.com/learning/ddos/what-is-layer-7/)
[The 7 Kinds of Security](https://www.veracode.com/sites/default/files/Resources/eBooks/7-kinds-of-security.pdf)
[The Libgcrypt Reference Manual](https://www.gnupg.org/documentation/manuals/gcrypt/)
[The Open Web Application Security Project(OWASP) Foundation Top 10](https://owasp.org/www-project-top-ten/)
[Best Practices for Using Open Source Code from The Linux Foundation](https://www.linuxfoundation.org/blog/2017/11/best-practices-using-open-source-code/)
[AWS Certified Security - Specialty Certification](https://aws.amazon.com/certification/certified-security-specialty/)
[Microsoft Certified: Azure Security Engineer Associate](https://docs.microsoft.com/en-us/learn/certifications/azure-security-engineer)
[Google Cloud Certified Professional Cloud Security Engineer](https://cloud.google.com/certification/cloud-security-engineer)
[Cisco Security Certifications](https://www.cisco.com/c/en/us/training-events/training-certifications/certifications/security.html)
[The Red Hat Certified Specialist in Security: Linux](https://www.redhat.com/en/services/training/ex415-red-hat-certified-specialist-security-linux-exam)
[Linux Professional Institute LPIC-3 Enterprise Security Certification](https://www.lpi.org/our-certifications/lpic-3-303-overview)
[Cybersecurity Training and Courses from IBM Skills](https://www.ibm.com/skills/topics/cybersecurity/)
[Cybersecurity Courses and Certifications by Offensive Security](https://www.offensive-security.com/courses-and-certifications/)
[RSA Certification Program](https://community.rsa.com/community/training/certification)
[Check Point Certified Security Expert(CCSE) Certification](https://training-certifications.checkpoint.com/#/courses/Check%20Point%20Certified%20Expert%20(CCSE)%20R80.x)
[Check Point Certified Security Administrator(CCSA) Certification](https://training-certifications.checkpoint.com/#/courses/Check%20Point%20Certified%20Admin%20(CCSA)%20R80.x)
[Check Point Certified Security Master (CCSM) Certification](https://training-certifications.checkpoint.com/#/courses/Check%20Point%20Certified%20Master%20(CCSM)%20R80.x)
[Certified Cloud Security Professional(CCSP) Certification](https://www.isc2.org/Certifications/CCSP)
[Certified Information Systems Security Professional (CISSP) Certification](https://www.isc2.org/Certifications/CISSP)
[CCNP Routing and Switching](https://learningnetwork.cisco.com/s/ccnp-enterprise)
[Certified Information Security Manager(CISM)](https://www.isaca.org/credentialing/cism)
[Wireshark Certified Network Analyst (WCNA)](https://www.wiresharktraining.com/certification.html)
[Juniper Networks Certification Program Enterprise (JNCP)](https://www.juniper.net/us/en/training/certification/)
[Security Training Certifications and Courses from Udemy](https://www.udemy.com/courses/search/?src=ukw&q=secuirty)
[Security Training Certifications and Courses from Coursera](https://www.coursera.org/search?query=security&)
[Security Certifications Training from Pluarlsight](https://www.pluralsight.com/browse/information-cyber-security/security-certifications)
# Differential Privacy
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
Above is a simple diagram of how Differential Privacy-Preserving Data Sharing and Data Mining protects a User's Data
## Learning Resources
[Differential Privacy](https://www.microsoft.com/en-us/ai/ai-lab-differential-privacy) is a system that simultaneously enables researchers and analysts to extract useful insights from datasets containing personal information and offers stronger privacy protections. This is achieved by introducing "statistical noise".
[Statistical Noise](https://news.microsoft.com/on-the-issues/2020/08/27/statistical-noise-data-differential-privacy/) is a process that small aletrations to masked datasets. The statistical noise hides identifiable characteristics of individuals, ensuring that the privacy of personal information is protected, but it's small enough to not materially impact the accuracy of the answers extracted by analysts and researchers.
[Laplacian Noise](https://en.wikipedia.org/wiki/Laplace_distribution) is a mechanism that adds Laplacian-distributed noise to a function.
[Differential Privacy Blog Series by the National Institute of Standards and Technology(NIST)](https://www.nist.gov/itl/applied-cybersecurity/privacy-engineering/collaboration-space/focus-areas/de-id/dp-blog)
[Apple's Differential Privacy Overview](https://www.apple.com/privacy/docs/Differential_Privacy_Overview.pdf)
[Learning with Privacy at Scale with Apple Machine Learning](https://machinelearning.apple.com/research/learning-with-privacy-at-scale)
[Microsoft Research Differential Privacy Overview](https://www.microsoft.com/en-us/research/publication/differential-privacy/)
[Responsible Machine Learning with Microsoft Azure](https://azure.microsoft.com/en-us/services/machine-learning/responsibleml/)
[Responsible AI Resources with Microsoft AI](https://www.microsoft.com/en-us/ai/responsible-ai-resources)
[Preserve data privacy by using differential privacy and the SmartNoise package](https://docs.microsoft.com/en-us/azure/machine-learning/concept-differential-privacy)
[Open Differential Privacy(OpenDP) Initiative by Microsoft and Harvard](https://projects.iq.harvard.edu/opendp)
[Google's Differential Privacy Library](https://github.com/google/differential-privacy)
[Computing Private Statistics with Privacy on Beam from Google Codelabs](https://codelabs.developers.google.com/codelabs/privacy-on-beam/#0)
[Introducing TensorFlow Privacy: Learning with Differential Privacy for Training Data](https://blog.tensorflow.org/2020/06/introducing-new-privacy-testing-library.html)
[TensorFlow Federated: Machine Learning on Decentralized Data](https://www.tensorflow.org/federated/)
[Federated Analytics: Collaborative Data Science without Data Collection](https://ai.googleblog.com/2020/05/federated-analytics-collaborative-data.html)
[Differentially-Private Stochastic Gradient Descent(DP-SGD)](https://github.com/tensorflow/privacy/blob/master/tutorials/walkthrough/README.md)
[Learning Differential Privacy from Harvard University Privacy Tools Project](https://privacytools.seas.harvard.edu/differential-privacy)
[Harvard University Privacy Tools Project Courses & Educational Materials](https://privacytools.seas.harvard.edu/courses-educational-materials)
[The Weaknesses of Differential Privacy course on Coursera](https://www.coursera.org/lecture/data-results/weaknesses-of-differential-privacy-50Y9k)
[The Differential Privacy of Bayesian Inference](https://privacytools.seas.harvard.edu/publications/differential-privacy-bayesian-inference)
[Simultaneous private learning of multiple concepts](https://privacytools.seas.harvard.edu/publications/simultaneous-private-learning-multiple-concepts)
[The Complexity of Computing the Optimal Composition of Differential Privacy](https://privacytools.seas.harvard.edu/publications/complexity-computing-optimal-composition-differential-privacy)
[Order revealing encryption and the hardness of private learning](https://privacytools.seas.harvard.edu/publications/order-revealing-encryption-and-hardness-private-learning)
[SAP HANA data anonymization using SAP Software Solutions](https://www.sap.com/cmp/dg/crm-xt17-ddm-data-anony/index.html)
[SAP HANA Security using their In-Memory Database](https://www.sap.com/products/hana/features/security.html)
[DEFCON Differential Privacy Training Launch](https://opensource.googleblog.com/2020/08/defcon-differential-privacy-training.html)
[Secure and Private AI course on Udacity](https://www.udacity.com/course/secure-and-private-ai--ud185)
[Differential Privacy - Security and Privacy for Big Data - Part 1 course on Coursera](https://www.coursera.org/learn/security-privacy-big-data)
[Differential Privacy - Security and Privacy for Big Data - Part 2 course on Coursera](https://www.coursera.org/learn/security-privacy-big-data-protection)
[Certified Ethical Emerging Technologist Professional Certificate course on Coursera](https://www.coursera.org/professional-certificates/certified-ethical-emerging-technologist)
## Tools
[PySyft](https://github.com/OpenMined/PySyft) is a Python library for secure and private Deep Learning. PySyft decouples private data from model training, using [Federated Learning](https://ai.googleblog.com/2017/04/federated-learning-collaborative.html), [Differential Privacy](https://www.microsoft.com/en-us/ai/ai-lab-differential-privacy), and Encrypted Computation (like [Multi-Party Computation (MPC)](https://multiparty.org) and [Homomorphic Encryption (HE)](https://www.microsoft.com/en-us/research/project/homomorphic-encryption/) within the main Deep Learning frameworks like [PyTorch](https://pytorch.org/) and [TensorFlow](https://www.tensorflow.org/).
[TensorFlow Privacy](https://github.com/tensorflow/privacy) is a Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy. The library comes with tutorials and analysis tools for computing the privacy guarantees provided.
[TensorFlow Federated (TFF)](https://github.com/tensorflow/federated) is an open-source framework for machine learning and other computations on decentralized data. TFF has been developed to facilitate open research and experimentation with [Federated Learning (FL)](https://ai.googleblog.com/2017/04/federated-learning-collaborative.html), an approach to machine learning where a shared global model is trained across many participating clients that keep their training data locally.
[Privacy on Beam](https://github.com/google/differential-privacy/tree/main/privacy-on-beam) is an end-to-end differential privacy solution built on [Apache Beam](https://beam.apache.org/documentation/). It is intended to be usable by all developers, regardless of their differential privacy expertise.
[PyDP](https://github.com/OpenMined/PyDP) is a Python wrapper for Google's Differential Privacy project.
[PennyLane](https://pennylane.ai) is a cross-platform Python library for [differentiable programming](https://en.wikipedia.org/wiki/Differentiable_programming) of quantum computers. By training a quantum computer the same way as a neural network.
[BoTorch](https://botorch.org) is a library for Bayesian Optimization built on PyTorch.
[PyTorch Geometric (PyG)](https://github.com/rusty1s/pytorch_geometric) is a geometric deep learning extension library for [PyTorch](https://pytorch.org/).
[Skorch](https://github.com/skorch-dev/skorch) is a scikit-learn compatible neural network library that wraps PyTorch.
[Diffprivlib](https://github.com/IBM/differential-privacy-library) is the IBM Differential Privacy Library for experimenting with, investigating and developing applications in, differential privacy.
[Opacus](https://opacus.ai/) is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the client, has little impact on training performance and allows the client to online track the privacy budget expended at any given moment.
[Smart Noise](https://github.com/opendifferentialprivacy/smartnoise-sdk) is a toolkit that uses state-of-the-art differential privacy (DP) techniques to inject noise into data, to prevent disclosure of sensitive information and manage exposure risk.
# Kubernetes
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Kubernetes (K8s)](https://kubernetes.io/) is an open-source system for automating deployment, scaling, and management of containerized applications.
**Building Highly-Availability(HA) Clusters with kubeadm. Source: [Kubernetes.io](https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/high-availability/)**
[Google Kubernetes Engine (GKE)](https://cloud.google.com/kubernetes-engine/) is a managed, production-ready environment for running containerized applications.
[Azure Kubernetes Service (AKS)](https://azure.microsoft.com/en-us/services/kubernetes-service/) is serverless Kubernetes, with a integrated continuous integration and continuous delivery (CI/CD) experience, and enterprise-grade security and governance. Unite your development and operations teams on a single platform to rapidly build, deliver, and scale applications with confidence.
[Amazon EKS](https://docs.aws.amazon.com/eks/latest/userguide/what-is-eks.html) is a tool that runs Kubernetes control plane instances across multiple Availability Zones to ensure high availability.
[AWS Controllers for Kubernetes (ACK)](https://aws.amazon.com/blogs/containers/aws-controllers-for-kubernetes-ack/) is a new tool that lets you directly manage AWS services from Kubernetes. ACK makes it simple to build scalable and highly-available Kubernetes applications that utilize AWS services.
[Container Engine for Kubernetes (OKE)](https://www.oracle.com/cloud-native/container-engine-kubernetes/) is an Oracle-managed container orchestration service that can reduce the time and cost to build modern cloud native applications. Unlike most other vendors, Oracle Cloud Infrastructure provides Container Engine for Kubernetes as a free service that runs on higher-performance, lower-cost compute.
[Anthos](https://cloud.google.com/anthos/docs/concepts/overview) is a modern application management platform that provides a consistent development and operations experience for cloud and on-premises environments.
[Red Hat Openshift](https://www.openshift.com/) is a fully managed Kubernetes platform that provides a foundation for on-premises, hybrid, and multicloud deployments.
[OKD](https://okd.io/) is a community distribution of Kubernetes optimized for continuous application development and multi-tenant deployment. OKD adds developer and operations-centric tools on top of Kubernetes to enable rapid application development, easy deployment and scaling, and long-term lifecycle maintenance for small and large teams.
[Odo](https://odo.dev/) is a fast, iterative, and straightforward CLI tool for developers who write, build, and deploy applications on Kubernetes and OpenShift.
[Kata Operator](https://github.com/openshift/kata-operator) is an operator to perform lifecycle management (install/upgrade/uninstall) of [Kata Runtime](https://katacontainers.io/) on Openshift as well as Kubernetes cluster.
[Thanos](https://thanos.io/) is a set of components that can be composed into a highly available metric system with unlimited storage capacity, which can be added seamlessly on top of existing Prometheus deployments.
[OpenShift Hive](https://github.com/openshift/hive) is an operator which runs as a service on top of Kubernetes/OpenShift. The Hive service can be used to provision and perform initial configuration of OpenShift 4 clusters.
[Rook](https://rook.io/) is a tool that turns distributed storage systems into self-managing, self-scaling, self-healing storage services. It automates the tasks of a storage administrator: deployment, bootstrapping, configuration, provisioning, scaling, upgrading, migration, disaster recovery, monitoring, and resource management.
[VMware Tanzu](https://tanzu.vmware.com/tanzu) is a centralized management platform for consistently operating and securing your Kubernetes infrastructure and modern applications across multiple teams and private/public clouds.
[Kubespray](https://kubespray.io/) is a tool that combines Kubernetes and Ansible to easily install Kubernetes clusters that can be deployed on [AWS](https://github.com/kubernetes-sigs/kubespray/blob/master/docs/aws.md), GCE, [Azure](https://github.com/kubernetes-sigs/kubespray/blob/master/docs/azure.md), [OpenStack](https://github.com/kubernetes-sigs/kubespray/blob/master/docs/openstack.md), [vSphere](https://github.com/kubernetes-sigs/kubespray/blob/master/docs/vsphere.md), [Packet](https://github.com/kubernetes-sigs/kubespray/blob/master/docs/packet.md) (bare metal), Oracle Cloud Infrastructure (Experimental), or Baremetal.
[KubeInit](https://github.com/kubeinit/kubeinit) provides Ansible playbooks and roles for the deployment and configuration of multiple Kubernetes distributions.
[Rancher](https://rancher.com/) is a complete software stack for teams adopting containers. It addresses the operational and security challenges of managing multiple Kubernetes clusters, while providing DevOps teams with integrated tools for running containerized workloads.
[K3s](https://github.com/rancher/k3s) is a highly available, certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances.
[Helm](https://helm.sh/) is a Kubernetes Package Manager tool that makes it easier to install and manage Kubernetes applications.
[Knative](https://knative.dev/) is a Kubernetes-based platform to build, deploy, and manage modern serverless workloads. Knative takes care of the operational overhead details of networking, autoscaling (even to zero), and revision tracking.
[KubeFlow](https://www.kubeflow.org/) is a tool dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable.
[Etcd](https://etcd.io/) is a distributed key-value store that provides a reliable way to store data that needs to be accessed by a distributed system or cluster of machines. Etcd is used as the backend for service discovery and stores cluster state and configuration for Kubernetes.
[OpenEBS](https://openebs.io/) is a Kubernetes-based tool to create stateful applications using Container Attached Storage.
[Container Storage Interface (CSI)](https://www.architecting.it/blog/container-storage-interface/) is an API that lets container orchestration platforms like Kubernetes seamlessly communicate with stored data via a plug-in.
[MicroK8s](https://microk8s.io/) is a tool that delivers the full Kubernetes experience. In a Fully containerized deployment with compressed over-the-air updates for ultra-reliable operations. It is supported on Linux, Windows, and MacOS.
[Charmed Kubernetes](https://ubuntu.com/kubernetes/features) is a well integrated, turn-key, conformant Kubernetes platform, optimized for your multi-cloud environments developed by Canonical.
[Grafana Kubernetes App](https://grafana.com/grafana/plugins/grafana-kubernetes-app) is a toll that allows you to monitor your Kubernetes cluster's performance. It includes 4 dashboards, Cluster, Node, Pod/Container and Deployment. It allows for the automatic deployment of the required Prometheus exporters and a default scrape config to use with your in cluster Prometheus deployment.
[KubeEdge](https://kubeedge.io/en/) is an open source system for extending native containerized application orchestration capabilities to hosts at Edge.It is built upon kubernetes and provides fundamental infrastructure support for network, app. deployment and metadata synchronization between cloud and edge.
[Lens](https://k8slens.dev/) is the most powerful IDE for people who need to deal with Kubernetes clusters on a daily basis. It has support for MacOS, Windows and Linux operating systems.
[kind](https://kind.sigs.k8s.io/) is a tool for running local Kubernetes clusters using Docker container “nodes”. It was primarily designed for testing Kubernetes itself, but may be used for local development or CI.
[Flux CD](https://fluxcd.io/) is a tool that automatically ensures that the state of your Kubernetes cluster matches the configuration you've supplied in Git. It uses an operator in the cluster to trigger deployments inside Kubernetes, which means that you don't need a separate continuous delivery tool.
## Kubernetes Learning Resources
[Getting Kubernetes Certifications](https://training.linuxfoundation.org/certification/catalog/?_sft_technology=kubernetes)
[Getting started with Kubernetes on AWS](https://aws.amazon.com/kubernetes/)
[Kubernetes on Microsoft Azure](https://azure.microsoft.com/en-us/topic/what-is-kubernetes/)
[Intro to Azure Kubernetes Service](https://docs.microsoft.com/en-us/azure/aks/kubernetes-dashboard)
[Getting started with Google Cloud](https://cloud.google.com/learn/what-is-kubernetes)
[Getting started with Kubernetes on Red Hat](https://www.redhat.com/en/topics/containers/what-is-kubernetes)
[Getting started with Kubernetes on IBM](https://www.ibm.com/cloud/learn/kubernetes)
[YAML basics in Kubernetes](https://developer.ibm.com/technologies/containers/tutorials/yaml-basics-and-usage-in-kubernetes/)
[Elastic Cloud on Kubernetes](https://www.elastic.co/elastic-cloud-kubernetes)
[Docker and Kubernetes](https://www.docker.com/products/kubernetes)
[Deploy a model to an Azure Kubernetes Service cluster](https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-azure-kubernetes-service?tabs=python)
[Simplify Machine Learning Inference on Kubernetes with Amazon SageMaker Operators](https://aws.amazon.com/blogs/machine-learning/simplify-machine-learning-inference-on-kubernetes-with-amazon-sagemaker-operators/)
[Running Apache Spark on Kubernetes](http://spark.apache.org/docs/latest/running-on-kubernetes.html)
[Kubernetes Across VMware vRealize Automation](https://blogs.vmware.com/management/2019/06/kubernetes-across-vmware-cloud-automation-services.html)
[VMware Tanzu Kubernetes Grid](https://tanzu.vmware.com/kubernetes-grid)
[All the Ways VMware Tanzu Works with AWS](https://tanzu.vmware.com/content/blog/all-the-ways-vmware-tanzutm-works-with-aws)
[VMware Tanzu Education](https://tanzu.vmware.com/education)
[Using Ansible in a Cloud-Native Kubernetes Environment](https://www.ansible.com/blog/how-useful-is-ansible-in-a-cloud-native-kubernetes-environment)
[Managing Kubernetes (K8s) objects with Ansible](https://docs.ansible.com/ansible/latest/collections/community/kubernetes/k8s_module.html)
[Setting up a Kubernetes cluster using Vagrant and Ansible](https://kubernetes.io/blog/2019/03/15/kubernetes-setup-using-ansible-and-vagrant/)
[Running MongoDB with Kubernetes](https://www.mongodb.com/kubernetes)
[Kubernetes Fluentd](https://docs.fluentd.org/v/0.12/articles/kubernetes-fluentd)
[Understanding the new GitLab Kubernetes Agent](https://about.gitlab.com/blog/2020/09/22/introducing-the-gitlab-kubernetes-agent/)
[Kubernetes Contributors](https://www.kubernetes.dev/)
[KubeAcademy from VMware](https://kube.academy/)
# Machine Learning
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
## ML frameworks & applications
[TensorFlow](https://www.tensorflow.org) is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
[Tensorman](https://github.com/pop-os/tensorman) is a utility for easy management of Tensorflow containers by developed by [System76]( https://system76.com).Tensorman allows Tensorflow to operate in an isolated environment that is contained from the rest of the system. This virtual environment can operate independent of the base system, allowing you to use any version of Tensorflow on any version of a Linux distribution that supports the Docker runtime.
[Keras](https://keras.io) is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.It was developed with a focus on enabling fast experimentation. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, or PlaidML.
[PyTorch](https://pytorch.org) is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds. Primarily developed by Facebook's AI Research lab.
[Amazon SageMaker](https://aws.amazon.com/sagemaker/) is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models.
[Azure Databricks](https://azure.microsoft.com/en-us/services/databricks/) is a fast and collaborative Apache Spark-based big data analytics service designed for data science and data engineering. Azure Databricks, sets up your Apache Spark environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn.
[Microsoft Cognitive Toolkit (CNTK)](https://docs.microsoft.com/en-us/cognitive-toolkit/) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers.
[Apache Airflow](https://airflow.apache.org) is an open-source workflow management platform created by the community to programmatically author, schedule and monitor workflows. Install. Principles. Scalable. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity.
[Open Neural Network Exchange(ONNX)](https://github.com/onnx) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
[Apache MXNet](https://mxnet.apache.org/) is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. Support for Python, R, Julia, Scala, Go, Javascript and more.
[AutoGluon](https://autogluon.mxnet.io/index.html) is toolkit for Deep learning that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data.
[Anaconda](https://www.anaconda.com/) is a very popular Data Science platform for machine learning and deep learning that enables users to develop models, train them, and deploy them.
[PlaidML](https://github.com/plaidml/plaidml) is an advanced and portable tensor compiler for enabling deep learning on laptops, embedded devices, or other devices where the available computing hardware is not well supported or the available software stack contains unpalatable license restrictions.
[OpenCV](https://opencv.org) is a highly optimized library with focus on real-time computer vision applications. The C++, Python, and Java interfaces support Linux, MacOS, Windows, iOS, and Android.
[Scikit-Learn](https://scikit-learn.org/stable/index.html) is a Python module for machine learning built on top of SciPy, NumPy, and matplotlib, making it easier to apply robust and simple implementations of many popular machine learning algorithms.
[Weka](https://www.cs.waikato.ac.nz/ml/weka/) is an open source machine learning software that can be accessed through a graphical user interface, standard terminal applications, or a Java API. It is widely used for teaching, research, and industrial applications, contains a plethora of built-in tools for standard machine learning tasks, and additionally gives transparent access to well-known toolboxes such as scikit-learn, R, and Deeplearning4j.
[Caffe](https://github.com/BVLC/caffe) is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.
[Theano](https://github.com/Theano/Theano) is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently including tight integration with NumPy.
[nGraph](https://github.com/NervanaSystems/ngraph) is an open source C++ library, compiler and runtime for Deep Learning. The nGraph Compiler aims to accelerate developing AI workloads using any deep learning framework and deploying to a variety of hardware targets.It provides the freedom, performance, and ease-of-use to AI developers.
[NVIDIA cuDNN](https://developer.nvidia.com/cudnn) is a GPU-accelerated library of primitives for [deep neural networks](https://developer.nvidia.com/deep-learning). cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN accelerates widely used deep learning frameworks, including [Caffe2](https://caffe2.ai/), [Chainer](https://chainer.org/), [Keras](https://keras.io/), [MATLAB](https://www.mathworks.com/solutions/deep-learning.html), [MxNet](https://mxnet.incubator.apache.org/), [PyTorch](https://pytorch.org/), and [TensorFlow](https://www.tensorflow.org/).
[Jupyter Notebook](https://jupyter.org/) is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Jupyter is used widely in industries that do data cleaning and transformation, numerical simulation, statistical modeling, data visualization, data science, and machine learning.
[Apache Spark](https://spark.apache.org/) is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
[Apache Spark Connector for SQL Server and Azure SQL](https://github.com/microsoft/sql-spark-connector) is a high-performance connector that enables you to use transactional data in big data analytics and persists results for ad-hoc queries or reporting. The connector allows you to use any SQL database, on-premises or in the cloud, as an input data source or output data sink for Spark jobs.
[Apache PredictionIO](https://predictionio.apache.org/) is an open source machine learning framework for developers, data scientists, and end users. It supports event collection, deployment of algorithms, evaluation, querying predictive results via REST APIs. It is based on scalable open source services like Hadoop, HBase (and other DBs), Elasticsearch, Spark and implements what is called a Lambda Architecture.
[Cluster Manager for Apache Kafka(CMAK)](https://github.com/yahoo/CMAK) is a tool for managing [Apache Kafka](https://kafka.apache.org/) clusters.
[BigDL](https://bigdl-project.github.io/) is a distributed deep learning library for Apache Spark. With BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Spark or Hadoop clusters.
[Koalas](https://pypi.org/project/koalas/) is project makes data scientists more productive when interacting with big data, by implementing the pandas DataFrame API on top of Apache Spark.
[Apache Spark™ MLflow](https://mlflow.org/) is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components:
**[MLflow Tracking](https://mlflow.org/docs/latest/tracking.html)**: Record and query experiments: code, data, config, and results.
**[MLflow Projects](https://mlflow.org/docs/latest/projects.html)**: Package data science code in a format to reproduce runs on any platform.
**[MLflow Models](https://mlflow.org/docs/latest/models.html)**: Deploy machine learning models in diverse serving environments.
**[Model Registry](https://mlflow.org/docs/latest/model-registry.html)**: Store, annotate, discover, and manage models in a central repository.
[Eclipse Deeplearning4J (DL4J)](https://deeplearning4j.konduit.ai/) is a set of projects intended to support all the needs of a JVM-based(Scala, Kotlin, Clojure, and Groovy) deep learning application. This means starting with the raw data, loading and preprocessing it from wherever and whatever format it is in to building and tuning a wide variety of simple and complex deep learning networks.
[Numba](https://github.com/numba/numba) is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaconda, Inc. It uses the LLVM compiler project to generate machine code from Python syntax. Numba can compile a large subset of numerically-focused Python, including many NumPy functions. Additionally, Numba has support for automatic parallelization of loops, generation of GPU-accelerated code, and creation of ufuncs and C callbacks.
[Chainer](https://chainer.org/) is a Python-based deep learning framework aiming at flexibility. It provides automatic differentiation APIs based on the define-by-run approach (dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. It also supports CUDA/cuDNN using [CuPy](https://github.com/cupy/cupy) for high performance training and inference.
[cuML](https://github.com/rapidsai/cuml) is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn.
## Online ML Learning Resources
[Machine Learning by Stanford University from Coursera](https://www.coursera.org/learn/machine-learning)
[Machine Learning Courses Online from Coursera](https://www.coursera.org/courses?query=machine%20learning&)
[Machine Learning Courses Online from Udemy](https://www.udemy.com/topic/machine-learning/)
[Learn Machine Learning with Online Courses and Classes from edX](https://www.edx.org/learn/machine-learning)
# IoT Protocols
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[DBus](https://www.freedesktop.org/wiki/Software/dbus/) is an open source software bus developed Red Hat for inter-process communication, and remote procedure call mechanism that allows communication between multiple processes running concurrently on the same machine.
[SOAP](https://www.soapui.org) is a messaging protocol specification for exchanging structured information in the implementation of web services in computer networks. SOAP can extend HTTP for XML messaging. SOAP provides data transport for Web services. SOAP can exchange complete documents or call a remote procedure. SOAP can be used for broadcasting a message.
[gRPC](https://grpc.io) is a modern, open source remote procedure call (RPC) framework developed by Google that can run anywhere. It enables client and server applications to communicate transparently, and makes it easier to build connected systems.It uses HTTP/2 for transport, Protocol Buffers as the interface description language, and provides features such as authentication, bidirectional streaming and flow control, blocking or nonblocking bindings, and cancellation and timeouts.
[LWM2M](https://www.omaspecworks.org/what-is-oma-specworks/iot/lightweight-m2m-lwm2m/) is a protocol from the Open Mobile Alliance for M2M or IoT device management. Lightweight M2M enabler defines the application layer communication protocol between a LWM2M Server and a LWM2M Client, which is located in a LWM2M Device.
[Advanced Message Queuing Protocol (AMQP)](https://www.amqp.org) is an open standard for passing business messages between applications or organizations. It connects systems, feeds business processes with the information they need and reliably transmits onward the instructions that achieve their goals. The defining features of AMQP are message orientation, queuing, routing, reliability and security.
[Constrained Application Protocol (CoAP)](https://coap.technology) is a specialized web transfer protocol for use with constrained nodes and constrained networks in the Internet of Things. The protocol is designed for machine-to-machine (M2M) applications such as smart energy and building automation."
[Extensible Messaging and Presence Protocol (XMPP)](https://xmpp.org) is a communication protocol for message-oriented middleware based on XML (Extensible Markup Language). It enables the near real-time exchange of structured yet extensible data between any two or more network entities.
[OASIS Message Queuing Telemetry Transport (MQTT)](https://www.oasis-open.org) is an open OASIS and ISO standard (ISO/IEC 20922) lightweight, publish-subscribe network protocol that transports messages between devices. The protocol usually runs over TCP/IP; however, any network protocol that provides ordered, lossless, bi-directional connections can support MQTT.
[Very Simple Control Protocol (VSCP)](https://vscp.org) is a free automation protocol suitable for all sorts of automation task where building- or home-automation is in the main focus. Its main advantage is that each VSCP-node can work completely autonomous, being part of distributed network of other nodes.
# Operating systems
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Raspberry Pi OS](https://www.raspberrypi.org/software/operating-systems/)
[Hass.io(Home Assistant OS)](https://www.home-assistant.io/hassio/installation/)
[Manjaro Linux ARM](https://manjaro.org/download/#ARM)
[Arch Linux ARM](https://archlinuxarm.org/platforms/armv8/broadcom/raspberry-pi-4)
[Ubuntu MATE for Raspberry Pi](https://ubuntu-mate.org/ports/raspberry-pi/)
[Ubuntu Desktop for Raspberry Pi](https://ubuntu.com/raspberry-pi)
[Ubuntu Core on a Raspberry Pi](https://ubuntu.com/download/raspberry-pi-core)
[Ubuntu Server for ARM](https://ubuntu.com/download/server/arm)
[Debian](https://wiki.debian.org)
[Fedora ARM](https://arm.fedoraproject.org)
[openSUSE](https://en.opensuse.org/openSUSE)
[SUSE](https://documentation.suse.com/)
[Kali Linux for the Raspberry Pi](https://www.kali.org/docs/arm/kali-linux-raspberry-pi/)
[RetroArch](https://www.retroarch.com/?page=platforms)
[RetroPie](https://retropie.org.uk/)
[LibreELEC](https://libreelec.tv/)
[OSMC](https://osmc.tv)
[RISC OS](https://www.riscosopen.org/content/)
[Windows 10 IoT Core](https://docs.microsoft.com/en-us/windows/iot-core/windows-iot-core)
[HeliOS](https://www.arduino.cc/reference/en/libraries/helios/) is an embedded operating system that is free for anyone to use. While called an operating system for simplicity, HeliOS is better described as a multitasking kernel for embedded systems.
[Simba](https://simba-os.readthedocs.io/en/latest/getting-started.html) is a small OS for an Embedded Programming Platform like Arduino. It aims to make embedded programming easy and portable.
[Trampoline](https://github.com/TrampolineRTOS/) is a static RTOS for small embedded systems.
[DuinOS](https://github.com/DuinOS/DuinOS) is Framework (a wrapper) for use the FreeRTOSwith Arduino.
[VxWorks](https://www.windriver.com/products/vxworks) is an industry-leading real-time operating systems (RTOS) for building embedded devices and systems for more than 30 years.
[LynxOS](https://www.lynx.com/products/lynxos-posix-real-time-operating-system-rtos) is a native POSIX, hard real-time partitioning operating system developed by Lynx Software Technologies.
[Zephyr OS](https://www.zephyrproject.org/zephyr-rtos-featured-in-risc-v-getting-started-guide/) is a popular security-oriented RTOS with a small-footprint kernel designed for use on resource-constrained and embedded systems. Zephyr has a small-foorprint Kernel focusing on embedded devices compatible with x86, ARM, RISC-V, Xtensa and [others](https://docs.zephyrproject.org/latest/boards/index.html).
[FreeRTOS](https://freertos.org/) is an open source, real-time operating system for microcontrollers that makes small, low-power edge devices easy to program, deploy, secure, connect, and manage.
[Arm Mbed TLS](https://os.mbed.com) provides a comprehensive SSL/TLS solution and makes it easy for developers to include cryptographic and SSL/TLS capabilities in their software and embedded products. As an SSL library, it provides an intuitive API, readable source code and a minimal and highly configurable code footprint.
[Contiki-os](https://github.com/contiki-os) is an operating system for networked, memory-constrained systems with a focus on low-power wireless Internet of Things devices.
# Middleware
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Red Hat® JBoss® Middleware](https://connect.redhat.com/zones/red-hat-middleware) is middleware that integrates software from various open source communities, including the JBoss community, Apache Software Foundation, and Eclipse Foundation, into robust, fully tested, integrated platforms available via subscriptions that include support and long-term maintenance.
[IoTSyS](https://iotsyst.com) is an integration middleware for the Internet of Things. It provides a communication stack for embedded devices based on IPv6, Web services, and OBIX to establish interoperable interfaces for smart objects.
[OpenIoT](https://github.com/OpenIotOrg/openiot) is an open source middleware infrastructure will support flexible configuration and deployment of algorithms for collection, and filtering information streams stemming from the internet-connected objects, while at the same time generating and processing important business/applications events.
[OpenRemote](https://github.com/openremote/openremote) is an open source middleware project, which integrates many different protocols and solutions available for smart building, and smart city automation, and offers visualization tools.
[Kaa](https://www.kaaproject.org/platform/) is a Enterprise IoT Platform has been designed with heavy-duty, enterprise-grade IoT solutions in mind. It banishes a monolithic approach to architecture in favour of highly portable microservices, which allow for flexible rearrangement and customization even in the middle of the solution's lifecycle.
# Node flow editors
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Node-RED](https://nodered.org) is a programming tool for wiring together hardware devices, APIs and online services in new and interesting ways. It provides a browser-based editor that makes it easy to wire together flows using the wide range of nodes in the palette that can be deployed to its runtime in a single-click.
### Toolkits
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[KinomaJS](https://github.com/Kinoma/kinomajs) is a visual code editor designed to help developers build starter projects for Kinoma Create and Kinoma Element. The project is built on Angular 2(RC7) and runs in a web browser. The live version is hosted using Google App Engine, but you can modify and build it yourself by following the instructions in this document.
[IoT Toolkit](https://www.segger.com/products/security-iot/iot-toolkit/) is a collection of libraries that enables communication with modern IoT based environments and devices. It is a high-performance collection of libraries optimized for minimum memory consumption in RAM, ROM, high speed, and versatility working on any device.
# Data Visualization
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Freeboard](https://github.com/Freeboard/freeboard) is an open source real-time dashboard builder for IOT and other web mashups. A free open-source alternative to Geckoboard.
[ThingSpeak](https://thingspeak.com) is an IoT analytics platform service that allows you to aggregate, visualize, and analyze live data streams in the cloud. You can send data to ThingSpeak from your devices, create instant visualization of live data, and send alerts.
# Search
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Thingful](https://www.thingful.net) is a Search Engine for the Internet of Things Find & use open IoT data from around the world.
# Hardware
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Arduino Ethernet Shield 2](https://www.arduino.cc/en/Guide/ArduinoEthernetShield) allows an Arduino board to connect to the internet using the Ethernet library and to read and write an SD card using the SD library.This shield is fully compatible with the former version, but relies on the newer W5500 chip.
[Raspberry Pi](https://www.raspberrypi.org) is a series of small single-board computers developed in the United Kingdom by the Raspberry Pi Foundation to promote teaching of basic computer science in schools and in developing countries. Price range from $10-45 depending on model.
[BeagleBone](https://beagleboard.org/bone) is a low-power open-source single-board computer produced by Texas Instruments. It runs Android, Ubuntu and other Linux flavors.
[openPicus FlyportPro](https://www.open-electronics.org/flyport-professional-iot-modules-by-openpicus/) is a system on a module dedicated to IoT and M2M application, especially for professional use. Following some details on the solution: Why FlyportPRO SoM? A system-on-module is the best solution for those customers looking for flexibility and for development time and risk reduction.
[Pinoccio](https://www.open-electronics.org/pinoccio-wifi-mesh-networking-for-arduino-and-iot-available-now/) is a solution to add mesh networking capability and WiFi-Internet access to all yout IoT devices, and it is Arduino compatible. Each board can assume the role of Scout in a Troop and one of the Scouts is the Lead to connect internet: Field Scouts talk to each other using a mesh network (called a Troop), using an extremely low-power radio.
### In-memory data grids
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Ehcache](https://www.ehcache.org) is an open source, standards-based cache that boosts performance, offloads your database, and simplifies scalability. It's the most widely-used Java-based cache because it's robust, proven, full-featured, and integrates with other popular libraries and frameworks.
[Hazelcast](https://hazelcast.com) is an open source in-memory data grid based on Java.
# Home automation
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Home Assistant](https://github.com/home-assistant/core) is open source home automation that puts local control and privacy first. Powered by a worldwide community of tinkerers and DIY enthusiasts. Perfect to run on a Raspberry Pi or a local server.
[openHAB](https://github.com/openhab) is a cross-platform software with the aim to integrate all kinds of Smart Home technologies, devices, etc.
[Eclipse SmartHome](https://www.eclipse.org/smarthome/) is a framework, not a ready-to-use solution. It offers a large set of features to choose from and leaves enough possibilities to design a Smart Home solution specific to your expectations. Its modular design brings millions of combinations and proves to be easily extensible by custom parts.
[The Thing System](https://github.com/TheThingSystem) is a set of software components and network protocols that aims to fix the Internet of Things. Our steward software is written in node.js making it both portable and easily extensible. It can run on your laptop, or fit onto a small single board computer like the Raspberry Pi.
# Robotics
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Open Source Robotics Foundation](https://www.openrobotics.org/) works with industry, academia, and government to create and support open software and hardware for use in robotics, from research and education to product development.
## Tools for Robotics
[ROS](https://www.ros.org/) is robotics middleware. Although ROS is not an operating system, it provides services designed for a heterogeneous computer cluster such as hardware abstraction, low-level device control, implementation of commonly used functionality, message-passing between processes, and package management.
[ROS2](https://index.ros.org/doc/ros2/) is a set of [software libraries and tools](https://github.com/ros2) that help you build robot applications. From drivers to state-of-the-art algorithms, and with powerful developer tools, ROS has what you need for your next robotics project. And it’s all open source.
[Robot Framework](https://robotframework.org/) is a generic open source automation framework. It can be used for test automation and robotic process automation. It has easy syntax, utilizing human-readable keywords. Its capabilities can be extended by libraries implemented with Python or Java.
[The Robotics Library (RL)](https://github.com/roboticslibrary/rl) is a self-contained C++ library for robot kinematics, motion planning and control. It covers mathematics, kinematics and dynamics, hardware abstraction, motion planning, collision detection, and visualization.RL runs on many different systems, including Linux, macOS, and Windows. It uses CMake as a build system and can be compiled with Clang, GCC, and Visual Studio.
[MoveIt](https://moveit.ros.org/) is the most widely used software for manipulation and has been used on over 100 robots. It provides an easy-to-use robotics platform for developing advanced applications, evaluating new designs and building integrated products for industrial, commercial, R&D, and other domains.
[AutoGluon](https://autogluon.mxnet.io/index.html) is toolkit for [Deep learning](https://gitlab.com/maos20008/intro-to-machine-learning) that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data.
[Gazebo](http://gazebosim.org/) accurately and efficiently simulates indoor and outdoor robots. You get a robust physics engine, high-quality graphics, and programmatic and graphical interfaces.
[Robotics System Toolbox](https://www.mathworks.com/products/robotics.html) provides tools and algorithms for designing, simulating, and testing manipulators, mobile robots, and humanoid robots. For manipulators and humanoid robots, the toolbox includes algorithms for collision checking, trajectory generation, forward and inverse kinematics, and dynamics using a rigid body tree representation.
For mobile robots, it includes algorithms for mapping, localization, path planning, path following, and motion control. The toolbox provides reference examples of common industrial robot applications. It also includes a library of
commercially available industrial robot models that you can import, visualize, and simulate.
[Intel Robot DevKit](https://github.com/intel/robot_devkit) is the tool to generate Robotics Software Development Kit (RDK) designed for autonomous devices, including the ROS2 core and capacibilities packages like perception, planning, control driver etc. It provides flexible build/runtime configurations to meet different autonomous requirement on top of diversity hardware choices, for example use different hareware engine CPU/GPU/VPU to accelerate AI related features.
[Arduino](https://www.arduino.cc/) is an open-source platform used for building electronics projects. Arduino consists of both a physical programmable circuit board (often referred to as a microcontroller) and a piece of software, or IDE (Integrated Development Environment) that runs on your computer, used to write and upload computer code to the physical board.
[ArduPilot](https://ardupilot.org/ardupilot/index.html) enables the creation and use of trusted, autonomous, unmanned vehicle systems for the peaceful benefit of all. ArduPilot provides a comprehensive suite of tools suitable for almost any vehicle and application.
[AirSim](https://github.com/Microsoft/AirSim) is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open-source, cross platform, and supports hardware-in-loop with popular flight controllers such as PX4 for physically and visually realistic simulations.
[F´ (F Prime)](https://github.com/nasa/fprime) is a component-driven framework that enables rapid development and deployment of spaceflight and other embedded software applications. Originally developed at the Jet Propulsion Laboratory, F´ has been successfully deployed on several space applications.
[The JPL Open Source Rover](https://github.com/nasa-jpl/open-source-rover) is an open source, build it yourself, scaled down version of the 6 wheel rover design that JPL uses to explore the surface of Mars. The Open Source Rover is designed almost entirely out of consumer off the shelf (COTS) parts. This project is intended to be a teaching and learning experience for those who want to get involved in mechanical engineering, software, electronics, or robotics.
[Light Detection and Ranging(LiDAR)](https://en.wikipedia.org/wiki/Lidar) is a remote sensing method that uses light in the form of a pulsed laser at an object, and uses the time and wavelength of the reflected beam of light to estimate the distance and in some applications ([Laser Imaging](https://en.wikipedia.org/wiki/Laser_scanning)), to create a 3D representation of the object and its surface characteristics. This technology is commonly used in aircraft and self-driving vehicles.
[AliceVision](https://github.com/alicevision/AliceVision) is a Photogrammetric Computer Vision Framework which provides a 3D Reconstruction and Camera Tracking algorithms. AliceVision aims to provide strong software basis with state-of-the-art computer vision algorithms that can be tested, analyzed and reused. The project is a result of collaboration between academia and industry to provide cutting-edge algorithms with the robustness and the quality required for production usage.
[CARLA](https://github.com/carla-simulator/carla) is an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites and environmental conditions.
[ROS bridge](https://github.com/carla-simulator/ros-bridge) is a package to bridge ROS for CARLA Simulator.
[ROS-Industrial](https://rosindustrial.org/) is an open source project that extends the advanced capabilities of ROS software to manufacturing.
[AWS RoboMaker](https://aws.amazon.com/robomaker/) is the most complete cloud solution for robotic developers to simulate, test and securely deploy robotic applications at scale. RoboMaker provides a fully-managed, scalable infrastructure for simulation that customers use for multi-robot simulation and CI/CD integration with regression testing in simulation.
[Microsoft Robotics Developer Studio](https://www.microsoft.com/en-us/download/details.aspx?id=29081) is a free .NET-based programming environment for building robotics applications.
[Visual Studio Code Extension for ROS](https://github.com/ms-iot/vscode-ros) is an extension provides support for Robot Operating System (ROS) development.
[Azure Kinect ROS Driver](https://github.com/microsoft/azure_kinect_ros_driver) is a node which publishes sensor data from the [Azure Kinect Developer Kit](https://azure.microsoft.com/en-us/services/kinect-dk/) to the [Robot Operating System (ROS)](http://www.ros.org/). Developers working with ROS can use this node to connect an Azure Kinect Developer Kit to an existing ROS installation.
[Azure IoT Hub for ROS](https://github.com/microsoft/ros_azure_iothub) is a ROS package works with the Microsoft Azure IoT Hub service to relay telemetry messages from the Robot to Azure IoT Hub or reflect properties from the Digital Twin to the robot using dynamic reconfigure.
[ROS 2 with ONNX Runtime](https://github.com/ms-iot/ros_msft_onnx) is a program that uses ROS 2 to run on different hardware platforms using their respective AI acceleration libraries for optimized execution of the ONNX model.
[Azure Cognitive Services LUIS ROS Node](https://github.com/ms-iot/ros_msft_luis) is a ROS node that bridges between ROS and the Azure Language Understanding Service. it can be configured to process audio directly from a microphone, or can subscribe to a ROS audio topic, then processes speech and generates "intent" ROS messages which can be processed by another ROS node to generate ROS commands.
## Robotics Learning Resources
[Robotics courses from Coursera](https://www.edx.org/learn/robotics)
[Learn Robotics with Online Courses and Classes from edX](https://www.edx.org/learn/robotics)
[Top Robotics Courses Online from Udemy](https://www.udemy.com/topic/robotics/)
[Free Online AI & Robotics Courses](https://www.futurelearn.com/subjects/it-and-computer-science-courses/ai-and-robotics)
[REC Foundation Robotics Industry Certification](https://www.roboticseducation.org/industry-certifications/)
[Carnegie Mellon Robotics Academy](https://www.cmu.edu/roboticsacademy/Training/Certifications.html)
[RIA Robotic Integrator Certification Program](https://www.robotics.org/robotics/integrator-certification)
[AWS RoboMaker – Develop, Test, Deploy, and Manage Intelligent Robotics Apps](https://aws.amazon.com/blogs/aws/aws-robomaker-develop-test-deploy-and-manage-intelligent-robotics-apps/)
[Microsoft AI School](https://aischool.microsoft.com/en-us/home)
[Language Understanding (LUIS) for Azure Cognitive Services](https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis)
[Azure VM templates to bootstrap ROS and ROS 2 environments](https://ms-iot.github.io/ROSOnWindows/ROSAtMS/AzureVM.html)
[Google Robotics Research](https://research.google/teams/brain/robotics/)
# Mesh networks
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
[Open Garden](https://opengarden.com) develops the FireChat mobile application, which enables peer-to-peer mobile Internet connection sharing with faster and more efficient data transmissions by automatically and actively choosing and switching to the best available network without requiring users to manually sift through available networks to find the best one available.
[OpenWSN](https://github.com/openwsn-berkeley/) is a project created at the University of California Berkeley and extended at the INRIA and at the Open University of Catalonia which aims to build an open standard-based and open source implementation of a complete constrained network protocol stack for wireless sensor networks and Internet of Things.
# Node.js Development
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
## Node.js Learning Resources
[Node.js](https://nodejs.org/) is a JavaScript runtime built on Chrome's V8 JavaScript engine that lets developers write command line tools and server-side scripts outside of a browser.
[Node.js Build Working Group](https://github.com/nodejs/build) maintains and controls infrastructure used for continuous integration (CI), releases, benchmarks, web hosting (of nodejs.org and other Node.js web properties) and more.
[The OpenJS Foundation](https://openjsf.org/) is made up of 32 open source JavaScript projects including Appium, Dojo, Electron, jQuery, Node.js, and webpack. The foundation's mission is to support the healthy growth of JavaScript and web technologies by providing a neutral organization to host and sustain projects, as well as collaboratively fund activities that benefit the ecosystem as a whole.
[Set up NodeJS on WSL 2](https://docs.microsoft.com/en-us/windows/nodejs/setup-on-wsl2)
[Getting started with Node.js in Google Cloud](https://cloud.google.com/nodejs/getting-started)
[Getting Started with Node.js in AWS](https://docs.aws.amazon.com/sdk-for-javascript/v2/developer-guide/getting-started-nodejs.html)
[Node.js App Hosting & Deployment in Microsoft Azure](https://azure.microsoft.com/en-us/develop/nodejs/)
[The Node.js best practices list ](https://github.com/goldbergyoni/nodebestpractices)
[Introduction to Node.js by W3Schools](https://www.w3schools.com/nodejs/nodejs_intro.asp)
[The Node.js Community Committee](https://github.com/nodejs/community-committee)
[Node.js Mentorship Program Initiative](https://github.com/nodejs/mentorship)
[Node.js tutorial in Visual Studio Code](https://code.visualstudio.com/docs/nodejs/nodejs-tutorial)
[Server-side Development with NodeJS, Express and MongoDB on Coursera](https://www.coursera.org/learn/server-side-nodejs)
## Node.js Tools
[NPM](https://www.npmjs.com/) is the company behind Node package manager, the npm Registry, and npm CLI.
[node-gyp](https://github.com/nodejs/node-gyp) is a cross-platform command-line tool written in Node.js for compiling native addon modules for Node.js. It contains a vendored copy of the gyp-next project that was previously used by the Chromium team, extended to support the development of Node.js native addons.
[nvm ](https://github.com/nvm-sh/nvm) is a version manager for node.js, designed to be installed per-user, and invoked per-shell. nvm works on any POSIX-compliant shell (sh, dash, ksh, zsh, bash), in particular on these platforms: unix, macOS, and windows WSL.
[node-docker](https://hub.docker.com/_/node/) is the official Node.js docker image, made with love by the node community.
[Mocha](https://github.com/mochajs/mocha) is a simple, flexible, fun JavaScript test framework for Node.js & The Browser.
[AVA](https://github.com/avajs/ava) is a test runner for Node.js with a concise API, detailed error output, embrace of new language features and process isolation that lets you develop with confidence.
[egg](https://eggjs.org/) is a born to build better enterprise frameworks and apps with Node.js & Koa.
[mysqljs](https://github.com/mysqljs/mysql) is a pure node.js JavaScript Client implementing the MySQL protocol.
[axios](https://github.com/axios/axios) is a promise based HTTP client for the browser and node.js.
[Fastify](https://www.fastify.io/) is a fast and low overhead web framework, for Node.js.
[Express](https://expressjs.com/) is a fast, unopinionated, minimalist web framework for node.
[Meteor](https://www.meteor.com/) is an ultra-simple environment for building modern web applications with JavavScript.
[NW.js](https://nwjs.io/) is an app runtime based on Chromium and node.js. You can write native apps in HTML and JavaScript with NW.js. It also lets you call Node.js modules directly from the DOM and enables a new way of writing native applications with all Web technologies.
[PM2](https://pm2.io/) is a production process manager for Node.js applications with a built-in load balancer. It allows you to keep applications alive forever, to reload them without downtime and to facilitate common system admin tasks.
[NestJS](https://nestjs.com/) is a framework for building efficient, scalable Node.js web applications. It uses modern JavaScript, is built with TypeScript and combines elements of OOP (Object Oriented Progamming), FP (Functional Programming), and FRP (Functional Reactive Programming).
[jenkins-nodejs](https://plugins.jenkins.io/nodejs/) is a Jenkins plugin for Node.js that provides the NodeJS auto-installer, allowing to create as many NodeJS installations "profiles" as you want.
[Strapi](https://strapi.io/) is an open source Node.js Headless CMS to easily build customisable APIs.
[Standard](https://standardjs.com/) is a JavaScript Style Guide, with linter & automatic code fixer.
[React Starter Kit](https://www.reactstarterkit.com/) is an isomorphic web app boilerplate for web development built on top of [Node.js](https://nodejs.org/), [Express](http://expressjs.com/), [GraphQL](http://graphql.org/) and [React](https://facebook.github.io/react/), containing modern web development tools such as [Webpack](https://webpack.github.io/), [Babel](https://babeljs.io/) and [Browsersync](https://www.browsersync.io/). Helping you to stay productive following the best practices.
[Hexo](https://hexo.io/) is a A fast, simple & powerful blog framework, powered by Node.js.
# Java Development
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
## Java Learning Resources
[Java](https://www.oracle.com/java/) is a popular programming language and development platform(JDK). It reduces costs, shortens development timeframes, drives innovation, and improves application services. With millions of developers running more than 51 billion Java Virtual Machines worldwide.
[The Eclipse Foundation](https://www.eclipse.org/downloads/) is home to a worldwide community of developers, the Eclipse IDE, Jakarta EE and over 375 open source projects, including runtimes, tools and frameworks for Java and other languages.
[Getting Started with Java](https://docs.oracle.com/javase/tutorial/)
[Oracle Java certifications from Oracle University](https://education.oracle.com/java-certification-benefits)
[Google Developers Training](https://developers.google.com/training/)
[Google Developers Certification](https://developers.google.com/certification/)
[Java Tutorial by W3Schools](https://www.w3schools.com/java/)
[Building Your First Android App in Java](codelabs.developers.google.com/codelabs/build-your-first-android-app/)
[Getting Started with Java in Visual Studio Code](https://code.visualstudio.com/docs/java/java-tutorial)
[Google Java Style Guide](https://google.github.io/styleguide/javaguide.html)
[AOSP Java Code Style for Contributors](https://source.android.com/setup/contribute/code-style)
[Chromium Java style guide](https://chromium.googlesource.com/chromium/src/+/master/styleguide/java/java.md)
[Get Started with OR-Tools for Java](https://developers.google.com/optimization/introduction/java)
[Getting started with Java Tool Installer task for Azure Pipelines](https://docs.microsoft.com/en-us/azure/devops/pipelines/tasks/tool/java-tool-installer)
[Gradle User Manual](https://docs.gradle.org/current/userguide/userguide.html)
## Java Tools & Frameworks
[Java SE](https://www.oracle.com/java/technologies/javase/tools-jsp.html) contains several tools to assist in program development and debugging, and in the monitoring and troubleshooting of production applications.
[JDK Development Tools](https://docs.oracle.com/javase/7/docs/technotes/tools/) includes the Java Web Start Tools (javaws) Java Troubleshooting, Profiling, Monitoring and Management Tools (jcmd, jconsole, jmc, jvisualvm); and Java Web Services Tools (schemagen, wsgen, wsimport, xjc).
[Android Studio](https://developer.android.com/studio/) is the official integrated development environment for Google's Android operating system, built on JetBrains' IntelliJ IDEA software and designed specifically for Android development. Availble on Windows, macOS, Linux, Chrome OS.
[IntelliJ IDEA](https://www.jetbrains.com/idea/) is an IDE for Java, but it also understands and provides intelligent coding assistance for a large variety of other languages such as Kotlin, SQL, JPQL, HTML, JavaScript, etc., even if the language expression is injected into a String literal in your Java code.
[NetBeans](https://netbeans.org/features/java/index.html) is an IDE provides Java developers with all the tools needed to create professional desktop, mobile and enterprise applications. Creating, Editing, and Refactoring. The IDE provides wizards and templates to let you create Java EE, Java SE, and Java ME applications.
[Java Design Patterns ](https://github.com/iluwatar/java-design-patterns) is a collection of the best formalized practices a programmer can use to solve common problems when designing an application or system.
[Elasticsearch](https://www.elastic.co/products/elasticsearch) is a distributed RESTful search engine built for the cloud written in Java.
[RxJava](https://github.com/ReactiveX/RxJava) is a Java VM implementation of [Reactive Extensions](http://reactivex.io/): a library for composing asynchronous and event-based programs by using observable sequences. It extends the [observer pattern](http://en.wikipedia.org/wiki/Observer_pattern) to support sequences of data/events and adds operators that allow you to compose sequences together declaratively while abstracting away concerns about things like low-level threading, synchronization, thread-safety and concurrent data structures.
[Guava](https://github.com/google/guava) is a set of core Java libraries from Google that includes new collection types (such as multimap and multiset), immutable collections, a graph library, and utilities for concurrency, I/O, hashing, caching, primitives, strings, and more! It is widely used on most Java projects within Google, and widely used by many other companies as well.
[okhttp](https://square.github.io/okhttp/) is a HTTP client for Java and Kotlin developed by Square.
[Retrofit](https://square.github.io/retrofit/) is a type-safe HTTP client for Android and Java develped by Square.
[LeakCanary](https://square.github.io/leakcanary/) is a memory leak detection library for Android develped by Square.
[Apache Spark](https://spark.apache.org/) is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.
[Apache Flink](https://flink.apache.org/) is an open source stream processing framework with powerful stream- and batch-processing capabilities with elegant and fluent APIs in Java and Scala.
[Fastjson](https://github.com/alibaba/fastjson/wiki) is a Java library that can be used to convert Java Objects into their JSON representation. It can also be used to convert a JSON string to an equivalent Java object.
[libGDX](https://libgdx.com/) is a cross-platform Java game development framework based on OpenGL (ES) that works on Windows, Linux, Mac OS X, Android, your WebGL enabled browser and iOS.
[Jenkins](https://www.jenkins.io/) is the leading open-source automation server. Built with Java, it provides over 1700 [plugins](https://plugins.jenkins.io/) to support automating virtually anything, so that humans can actually spend their time doing things machines cannot.
[DBeaver](https://dbeaver.io/) is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports any database which has JDBC driver (which basically means - ANY database). EE version also supports non-JDBC datasources (MongoDB, Cassandra, Redis, DynamoDB, etc).
[Redisson](https://redisson.pro/) is a Redis Java client with features of In-Memory Data Grid. Over 50 Redis based Java objects and services: Set, Multimap, SortedSet, Map, List, Queue, Deque, Semaphore, Lock, AtomicLong, Map Reduce, Publish / Subscribe, Bloom filter, Spring Cache, Tomcat, Scheduler, JCache API, Hibernate, MyBatis, RPC, and local cache.
[GraalVM](https://www.graalvm.org/) is a universal virtual machine for running applications written in JavaScript, Python, Ruby, R, JVM-based languages like Java, Scala, Clojure, Kotlin, and LLVM-based languages such as C and C++.
[Gradle](https://gradle.org/) is a build automation tool for multi-language software development. From mobile apps to microservices, from small startups to big enterprises, Gradle helps teams build, automate and deliver better software, faster. Write in Java, C++, Python or your language of choice.
[Apache Groovy](http://www.groovy-lang.org/) is a powerful, optionally typed and dynamic language, with static-typing and static compilation capabilities, for the Java platform aimed at improving developer productivity thanks to a concise, familiar and easy to learn syntax. It integrates smoothly with any Java program, and immediately delivers to your application powerful features, including scripting capabilities, Domain-Specific Language authoring, runtime and compile-time meta-programming and functional programming.
[JaCoCo](https://www.jacoco.org/jacoco/) is a free code coverage library for Java, which has been created by the EclEmma team based on the lessons learned from using and integration existing libraries for many years.
[Apache JMeter](http://jmeter.apache.org/) is used to test performance both on static and dynamic resources, Web dynamic applications. It also used to simulate a heavy load on a server, group of servers, network or object to test its strength or to analyze overall performance under different load types.
[Junit](https://junit.org/) is a simple framework to write repeatable tests. It is an instance of the xUnit architecture for unit testing frameworks.
[Mockito](https://site.mockito.org/) is the most popular Mocking framework for unit tests written in Java.
[SpotBugs](https://spotbugs.github.io/) is a program which uses static analysis to look for bugs in Java code.
[SpringBoot](https://spring.io/projects/spring-boot) is a great tool that helps you to create Spring-powered, production-grade applications and services with absolute minimum fuss. It takes an opinionated view of the Spring platform so that new and existing users can quickly get to the bits they need.
[YourKit](https://www.yourkit.com/) is a technology leader, creator of the most innovative and intelligent tools for profiling Java & .NET applications.
# Python Development
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
## Python Learning Resources
[Python](https://www.python.org) is an interpreted, high-level programming language. Python is used heavily in the fields of Data Science and Machine Learning.
[Python Developer’s Guide](https://devguide.python.org) is a comprehensive resource for contributing to Python – for both new and experienced contributors. It is maintained by the same community that maintains Python.
[Azure Functions Python developer guide](https://docs.microsoft.com/en-us/azure/azure-functions/functions-reference-python) is an introduction to developing Azure Functions using Python. The content below assumes that you've already read the [Azure Functions developers guide](https://docs.microsoft.com/en-us/azure/azure-functions/functions-reference).
[CheckiO](https://checkio.org/) is a programming learning platform and a gamified website that teaches Python through solving code challenges and competing for the most elegant and creative solutions.
[Python Institute](https://pythoninstitute.org)
[PCEP – Certified Entry-Level Python Programmer certification](https://pythoninstitute.org/pcep-certification-entry-level/)
[PCAP – Certified Associate in Python Programming certification](https://pythoninstitute.org/pcap-certification-associate/)
[PCPP – Certified Professional in Python Programming 1 certification](https://pythoninstitute.org/pcpp-certification-professional/)
[PCPP – Certified Professional in Python Programming 2](https://pythoninstitute.org/pcpp-certification-professional/)
[MTA: Introduction to Programming Using Python Certification](https://docs.microsoft.com/en-us/learn/certifications/mta-introduction-to-programming-using-python)
[Getting Started with Python in Visual Studio Code](https://code.visualstudio.com/docs/python/python-tutorial)
[Google's Python Style Guide](https://google.github.io/styleguide/pyguide.html)
[Google's Python Education Class](https://developers.google.com/edu/python/)
[Real Python](https://realpython.com)
[The Python Open Source Computer Science Degree by Forrest Knight](https://github.com/ForrestKnight/open-source-cs-python)
[Intro to Python for Data Science](https://www.datacamp.com/courses/intro-to-python-for-data-science)
[Intro to Python by W3schools](https://www.w3schools.com/python/python_intro.asp)
[Codecademy's Python 3 course](https://www.codecademy.com/learn/learn-python-3)
[Learn Python with Online Courses and Classes from edX](https://www.edx.org/learn/python)
[Python Courses Online from Coursera](https://www.coursera.org/courses?query=python)
## Python Frameworks and Tools
[Python Package Index (PyPI)](https://pypi.org/) is a repository of software for the Python programming language. PyPI helps you find and install software developed and shared by the Python community.
[PyCharm](https://www.jetbrains.com/pycharm/) is the best IDE I've ever used. With PyCharm, you can access the command line, connect to a database, create a virtual environment, and manage your version control system all in one place, saving time by avoiding constantly switching between windows.
[Python Tools for Visual Studio(PTVS)](https://microsoft.github.io/PTVS/) is a free, open source plugin that turns Visual Studio into a Python IDE. It supports editing, browsing, IntelliSense, mixed Python/C++ debugging, remote Linux/MacOS debugging, profiling, IPython, and web development with Django and other frameworks.
[Pylance](https://github.com/microsoft/pylance-release) is an extension that works alongside Python in Visual Studio Code to provide performant language support. Under the hood, Pylance is powered by Pyright, Microsoft's static type checking tool.
[Pyright](https://github.com/Microsoft/pyright) is a fast type checker meant for large Python source bases. It can run in a “watch” mode and performs fast incremental updates when files are modified.
[Django](https://www.djangoproject.com/) is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.
[Flask](https://flask.palletsprojects.com/) is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries.
[Web2py](http://web2py.com/) is an open-source web application framework written in Python allowing allows web developers to program dynamic web content. One web2py instance can run multiple web sites using different databases.
[AWS Chalice](https://github.com/aws/chalice) is a framework for writing serverless apps in python. It allows you to quickly create and deploy applications that use AWS Lambda.
[Tornado](https://www.tornadoweb.org/) is a Python web framework and asynchronous networking library. Tornado uses a non-blocking network I/O, which can scale to tens of thousands of open connections.
[HTTPie](https://github.com/httpie/httpie) is a command line HTTP client that makes CLI interaction with web services as easy as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers.
[Scrapy](https://scrapy.org/) is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing.
[Sentry](https://sentry.io/) is a service that helps you monitor and fix crashes in realtime. The server is in Python, but it contains a full API for sending events from any language, in any application.
[Pipenv](https://github.com/pypa/pipenv) is a tool that aims to bring the best of all packaging worlds (bundler, composer, npm, cargo, yarn, etc.) to the Python world.
[Python Fire](https://github.com/google/python-fire) is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
[Bottle](https://github.com/bottlepy/bottle) is a fast, simple and lightweight [WSGI](https://www.wsgi.org/) micro web-framework for Python. It is distributed as a single file module and has no dependencies other than the [Python Standard Library](https://docs.python.org/library/).
[CherryPy](https://cherrypy.org) is a minimalist Python object-oriented HTTP web framework.
[Sanic](https://github.com/huge-success/sanic) is a Python 3.6+ web server and web framework that's written to go fast.
[Pyramid](https://trypyramid.com) is a small and fast open source Python web framework. It makes real-world web application development and deployment more fun and more productive.
[TurboGears](https://turbogears.org) is a hybrid web framework able to act both as a Full Stack framework or as a Microframework.
[Falcon](https://falconframework.org/) is a reliable, high-performance Python web framework for building large-scale app backends and microservices with support for MongoDB, Pluggable Applications and autogenerated Admin.
[Neural Network Intelligence(NNI)](https://github.com/microsoft/nni) is an open source AutoML toolkit for automate machine learning lifecycle, including [Feature Engineering](https://github.com/microsoft/nni/blob/master/docs/en_US/FeatureEngineering/Overview.md), [Neural Architecture Search](https://github.com/microsoft/nni/blob/master/docs/en_US/NAS/Overview.md), [Model Compression](https://github.com/microsoft/nni/blob/master/docs/en_US/Compressor/Overview.md) and [Hyperparameter Tuning](https://github.com/microsoft/nni/blob/master/docs/en_US/Tuner/BuiltinTuner.md).
[Dash](https://plotly.com/dash) is a popular Python framework for building ML & data science web apps for Python, R, Julia, and Jupyter.
[Luigi](https://github.com/spotify/luigi) is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built-in.
[Locust](https://github.com/locustio/locust) is an easy to use, scriptable and scalable performance testing tool.
[spaCy](https://github.com/explosion/spaCy) is a library for advanced Natural Language Processing in Python and Cython.
[NumPy](https://www.numpy.org/) is the fundamental package needed for scientific computing with Python.
[Pillow](https://python-pillow.org/) is a friendly PIL(Python Imaging Library) fork.
[IPython](https://ipython.org/) is a command shell for interactive computing in multiple programming languages, originally developed for the Python programming language, that offers enhanced introspection, rich media, additional shell syntax, tab completion, and rich history.
[GraphLab Create](https://turi.com/) is a Python library, backed by a C++ engine, for quickly building large-scale, high-performance machine learning models.
[Pandas](https://pandas.pydata.org/) is a fast, powerful, and easy to use open source data structrures, data analysis and manipulation tool, built on top of the Python programming language.
[PuLP](https://coin-or.github.io/pulp/) is an Linear Programming modeler written in python. PuLP can generate LP files and call on use highly optimized solvers, GLPK, COIN CLP/CBC, CPLEX, and GUROBI, to solve these linear problems.
[Matplotlib](https://matplotlib.org/) is a 2D plotting library for creating static, animated, and interactive visualizations in Python. Matplotlib produces publication-quality figures in a variety of hardcopy formats and interactive environments across platforms.
[Scikit-Learn](https://scikit-learn.org/stable/index.html) is a simple and efficient tool for data mining and data analysis. It is built on NumPy,SciPy, and mathplotlib.
# Rust Development
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
## Rust Learning Resources
[Rust](https://www.rust-lang.org) is a multi-paradigm programming language focused on performance and safety. Rust has a comparable amount of runtime to C and C++, and has set up its standard library to be amenable towards OS development. Specifically, the standard library is split into two parts: core and std. Core is the lowest-level aspects only, and doesn't include things like allocation, threading, and other higher-level features.
[The Rust Language Reference](https://doc.rust-lang.org/nightly/reference/)
[The Rust Programming Language Book](https://doc.rust-lang.org/book/)
[Learning Rust](https://www.rust-lang.org/learn)
[Why AWS loves Rust](https://aws.amazon.com/blogs/opensource/why-aws-loves-rust-and-how-wed-like-to-help/)
[Rust Programming courses on Udemy](https://www.udemy.com/courses/search/?src=ukw&q=Rust)
[Safety in Systems Programming with Rust at Standford by Ryan Eberhardt](https://reberhardt.com/blog/2020/10/05/designing-a-new-class-at-stanford-safety-in-systems-programming.html)
[WebAssembly meets Kubernetes with Krustlet using Rust](https://cloudblogs.microsoft.com/opensource/2020/04/07/announcing-krustlet-kubernetes-rust-kubelet-webassembly-wasm/)
[Microsoft's Project Verona](https://github.com/microsoft/verona/blob/master/docs/explore.md)
## Rust Tools
[Cargo](https://github.com/rust-lang/cargo) is a package manager that downloads your Rust project’s dependencies and compiles your project.
[Crater](https://crater.rust-lang.org/) is a tool to run experiments across parts of the Rust ecosystem. Its primary purpose is to detect regressions in the Rust compiler, and it does this by building a large number of crates, running their test suites and comparing the results between two versions of the Rust compiler. It can operate locally (with Docker as the only dependency) or distributed on the cloud. It can operate locally (with Docker as the only dependency) or distributed on the cloud.
[VSCode-Rust](https://github.com/rust-lang/vscode-rust) is plugin that adds language support for Rust to Visual Studio Code. Rust support is powered by a separate language server - either by the official Rust Language Server (RLS) or rust-analyzer, depending on the user's preference. If you don't have it installed, the extension will install it for you (with permission). This extension is built and maintained by the Rust IDEs and editors team with the focus on providing a stable, high quality extension that makes the best use of the respective language server.
[Apache Arrow](https://github.com/apache/arrow) is a development platform for in-memory analytics. It contains a set of technologies that enable big data systems to process and move data fast. Arrow's libraries are available for C, C++, C#, Go, Java, JavaScript, MATLAB, Python, R, Ruby, and Rust.
[Wasmer](https://wasmer.io/) enables super lightweight containers based on [WebAssembly](https://webassembly.org/) that can run anywhere such as the Desktop to the Cloud and IoT devices, and also embedded in [any programming language](https://github.com/wasmerio/wasmer#language-integrations).
[Firecracker](https://firecracker-microvm.github.io) is an open source virtualization technology that is purpose-built for creating and managing secure, multi-tenant container and function-based services that provide serverless operational models. Firecracker runs workloads in lightweight virtual machines, called microVMs, which combine the security and isolation properties provided by hardware virtualization technology with the speed and flexibility of containers. Firecracker has also been integrated in container runtimes, for example [Kata Containers](https://github.com/kata-containers/documentation/wiki/Initial-release-of-Kata-Containers-with-Firecracker-support) and [Weaveworks Ignite](https://github.com/weaveworks/ignite).
[Tokio](https://github.com/tokio-rs/tokio) is an event-driven, non-blocking I/O platform for writing asynchronous applications with the Rust programming language.
[TiKV](https://github.com/tikv/tikv) is an open-source distributed transactional key-value database that also provides classical key-vlue APIs, but also transactional APIs with ACID compliance.
[Sonic](https://crates.io/crates/sonic-server) is a fast, lightweight and schema-less search backend similar to Elasticsearch in some use-cases.
[Hyper](https://github.com/hyperium/hyper) is a fast and correct HTTP library for Rust.
[Rocket](https://github.com/SergioBenitez/Rocket) is an async web framework for Rust with a focus on usability, security, extensibility, and speed.
[Clippy](https://rust-lang.github.io/rust-clippy/) is a collection of lints to catch common mistakes and improve your Rust code.
[Servo](https://github.com/servo/servo) is a prototype web browser engine written in the Rust language.
[Vector](https://vector.dev/) is a high-performance, end-to-end (agent & aggregator) observability data platform that puts the user in control of their observability data.
[RustPython](https://github.com/RustPython/RustPython) is a Python Interpreter written in Rust.
[Miri](https://github.com/rust-lang/miri) is an interpreter for Rust's mid-level intermediate representation. It can run binaries and test suites of cargo projects and detect certain classes of undefined behavior. Miri will alsowill also tell you about memory leaks: when there is memory still allocated at the end of the execution, and that memory is not reachable from a global static, Miri will raise an error.
[Chalk](https://rust-lang.github.io/chalk/book/) is an implementation and definition of the Rust trait system using a PROLOG-like logic solver.
[stdarch](https://doc.rust-lang.org/stable/core/arch/) is Rust's standard library vendor-specific APIs and run-time feature detection.
[Simpleinfra](https://github.com/rust-lang/simpleinfra) is rep that contains the tools and automation written by the Rust infrastructure team to manage our services. Using some of the tools in this repo require privileges only infra team members have.
[Rustlings](https://github.com/rust-lang/rustlings) is a small set of exercises to get you used to reading and writing Rust code.
[Krustlet](https://krustlet.dev/) acts as a Kubernetes Kubelet(written in Rust) by listening on the event stream for new pods that the scheduler assigns to it based on specific Kubernetes [tolerations](https://kubernetes.io/docs/concepts/configuration/taint-and-toleration/). The project is currently experimental.
## Operating System
[Redox](https://www.redox-os.org) is a Unix-like Operating System written in Rust, aiming to bring the innovations of Rust to a modern microkernel and full set of applications. Acitvely being developed by [Jeremy Soeller](https://gitlab.redox-os.org/jackpot51).
[Bottlerocket OS](https://github.com/bottlerocket-os/bottlerocket) is an open-source Linux-based operating system meant for hosting containers. Bottlerocket focuses on security and maintainability, providing a reliable, consistent, and safe platform for container-based workloads.
[Tock](https://www.tockos.org) is an embedded operating system designed for running multiple concurrent, mutually distrustful applications on Cortex-M and RISC-V based embedded platforms. Tock's design centers around protection, both from potentially malicious applications and from device drivers. Tock uses two mechanisms to protect different components of the operating system. First, the kernel and device drivers are written in Rust, a systems programming language that provides compile-time memory safety, type safety and strict aliasing. Tock uses Rust to protect the kernel (the scheduler and hardware abstraction layer) from platform specific device drivers as well as isolate device drivers from each other. Second, Tock uses memory protection units to isolate applications from each other and the kernel.
[Rust on Chrome OS](https://chromium.googlesource.com/chromiumos/docs/+/master/rust_on_cros.md) is a document that provides information on creating Rust projects for installation within Chrome OS and Chrome OS SDK.
[Writing an OS in Rust ](https://os.phil-opp.com) is a blog series creates a small operating system in the Rust programming language by [Philipp Oppermann](https://github.com/phil-opp).
# Swift Development
[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)
## Swift Learning Resources
[Swift](https://developer.apple.com/swift/) is Apple's main programming language for iOS, macOS, watchOS, and tvOS app development. Though, many parts of Swift will be familiar to developers from their experience of developing in C and Objective-C.
[Swift Evolution](https://github.com/apple/swift-evolution) maintains proposals for changes and user-visible enhancements to the Swift Programming Language.
[Xcode + Swift](https://developer.apple.com/swift/resources/) makes developing applications for MacOS and iOS fast and fun.
[Swift 5.3 Basics](https://docs.swift.org/swift-book/LanguageGuide/TheBasics.html)
[Start Developing iOS Apps with Swift](https://developer.apple.com/library/archive/referencelibrary/GettingStarted/DevelopiOSAppsSwift/)
[Apple Developer Documentation](https://developer.apple.com/documentation)
[Apple Foundation Framework](https://developer.apple.com/documentation/foundation)
[Apple Core Animation Framework](https://developer.apple.com/documentation/quartzcore)
[Apple Core Graphics Framework](https://developer.apple.com/documentation/coregraphics)
[Getting Started with LLDB](https://developer.apple.com/library/archive/documentation/IDEs/Conceptual/gdb_to_lldb_transition_guide/document/lldb-basics.html)
[Mac Catalyst - iOS - Human Interface Guidelines](https://developer.apple.com/design/human-interface-guidelines/ios/overview/mac-catalyst/)
[Amazon EC2 Mac Instances](https://aws.amazon.com/ec2/instance-types/mac/)
[Swift GitHub](https://github.com/apple/swift)
[Apple Developer Forums](https://developer.apple.com/forums/)
[Swift Forums](https://forums.swift.org/)
[Google's Swift Style Guide](https://google.github.io/swift/)
[Swift Courses Online from Coursera](https://www.coursera.org/courses?query=swift)
[Swift Courses Online from Udemy](https://www.udemy.com/topic/swift/)
[Learning Swift course from Codecademy](https://www.codecademy.com/learn/learn-swift)
## Swift Tools
[Xcode](https://developer.apple.com/xcode/) includes everything developers need to create great applications for Mac, iPhone, iPad, Apple TV, and Apple Watch. Xcode provides developers a unified workflow for user interface design, coding, testing, and debugging. Xcode 12 is built as an Universal app that runs 100% natively on Intel-based CPUs and Apple Silicon. It includes a unified macOS SDK that features all the frameworks, compilers, debuggers, and other tools you need to build apps that run natively on Apple Silicon and the Intel x86_64 CPU.
[SwiftUI](https://developer.apple.com/documentation/swiftui) is a user interface toolkit that provides views, controls, and layout structures for declaring your app's user interface. The SwiftUI framework provides event handlers for delivering taps, gestures, and other types of input to your application.
[UIKit](https://developer.apple.com/documentation/uikit) is a framework provides the required infrastructure for your iOS or tvOS apps. It provides the window and view architecture for implementing your interface, the event handling infrastructure for delivering Multi-Touch and other types of input to your app, and the main run loop needed to manage interactions among the user, the system, and your app.
[AppKit](https://developer.apple.com/documentation/appkit) is a graphical user interface toolkit that contains all the objects you need to implement the user interface for a macOS app such as windows, panels, buttons, menus, scrollers, and text fields, and it handles all the details for you as it efficiently draws on the screen, communicates with hardware devices and screen buffers, clears areas of the screen before drawing, and clips views.
[ARKit](https://developer.apple.com/augmented-reality/arkit/) is a set set of software development tools to enable developers to build augmented-reality apps for iOS developed by Apple. The latest version ARKit 3.5 takes advantage of the new LiDAR Scanner and depth sensing system on iPad Pro(2020) to support a new generation of AR apps that use Scene Geometry for enhanced scene understanding and object occlusion.
[RealityKit](https://developer.apple.com/documentation/realitykit) is a framework to implement high-performance 3D simulation and rendering with information provided by the ARKit framework to seamlessly integrate virtual objects into the real world.
[SceneKit](https://developer.apple.com/scenekit/) is a high-level 3D graphics framework that helps you create 3D animated scenes and effects in your iOS apps.
[Mac Catalyst](https://developer.apple.com/mac-catalyst/) is a set of Apple APIs that developers can use to rapidly port their iOS apps to [Apple Silicon M1 Chip](https://www.apple.com/mac/m1/) and take full advantage of the new capabilities on the new Apple hardware.
[Instruments](https://help.apple.com/instruments/mac/current/#/dev7b09c84f5) is a powerful and flexible performance-analysis and testing tool that’s part of the Xcode tool set. It’s designed to help you profile your iOS, watchOS, tvOS, and macOS apps, processes, and devices in order to better understand and optimize their behavior and performance.
[Cocoapods](https://cocoapods.org/) is a dependency manager for Swift and Objective-C used in Xcode projects by specifying the dependencies for your project in a simple text file. CocoaPods then recursively resolves dependencies between libraries, fetches source code for all dependencies, and creates and maintains an Xcode workspace to build your project.
[AppCode](https://www.jetbrains.com/objc/) is constantly monitoring the quality of your code. It warns you of errors and smells and suggests quick-fixes to resolve them automatically. AppCode provides lots of code inspections for Objective-C, Swift, C/C++, and a number of code inspections for other supported languages.
[Vapor](https://github.com/vapor/vapor) is a web framework for Swift. It provides a beautifully expressive and easy to use foundation for your next website, API, or cloud project.
[Hero](https://github.com/HeroTransitions/Hero) is a library for building iOS view controller transitions. It provides a declarative layer on top of the UIKit's cumbersome transition APIs—making custom transitions an easy task for developers.
[Kingfisher](https://github.com/onevcat/Kingfisher) is a powerful, pure-Swift library for downloading and caching images from the web. It provides you a chance to use a pure-Swift way to work with remote images in your next app.
[Realm](https://github.com/realm/realm-cocoa) is a mobile database that runs directly inside phones, tablets or wearables. This repository holds the source code for the iOS, macOS, tvOS & watchOS versions of Realm Swift & Realm Objective-C.
[Perfect](https://github.com/PerfectlySoft/Perfect) is a complete and powerful toolbox, framework, and application server for Linux, iOS, and macOS (OS X). It provides everything a Swift engineer needs for developing lightweight, maintainable, and scalable apps and other REST services entirely in the Swift programming language for both client-facing and server-side applications.
[Alamofire](https://github.com/Alamofire/Alamofire) is an HTTP networking library written in Swift.
[Eureka](https://github.com/xmartlabs/Eureka) is an elegant iOS form builder in Swift
[Carthage](https://github.com/Carthage/Carthage) is intended to be the simplest way to add frameworks to your Cocoa application. Carthage builds your dependencies and provides you with binary frameworks, but you retain full control over your project structure and setup. Carthage does not automatically modify your project files or your build settings.
[ReactiveCocoa](https://github.com/ReactiveCocoa/ReactiveCocoa) is reactive extensions to Cocoa frameworks, built on top of ReactiveSwift.
## Contribute
- [x] If would you like to contribute to this guide simply make a [Pull Request](https://github.com/mikeroyal/IoT-Guide/pulls).
## License
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Distributed under the [Creative Commons Attribution 4.0 International (CC BY 4.0) Public License](https://creativecommons.org/licenses/by/4.0/).