{"id":1336,"url":"https://github.com/mikeroyal/IoT-Guide","name":"IoT-Guide","description":"IoT Guide","projects_count":645,"last_synced_at":"2026-07-17T10:00:37.954Z","repository":{"id":103565273,"uuid":"354122853","full_name":"mikeroyal/IoT-Guide","owner":"mikeroyal","description":"IoT Guide","archived":false,"fork":false,"pushed_at":"2022-02-06T20:13:11.000Z","size":530,"stargazers_count":28,"open_issues_count":0,"forks_count":10,"subscribers_count":3,"default_branch":"main","last_synced_at":"2026-06-29T00:03:50.219Z","etag":null,"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"],"latest_commit_sha":null,"homepage":"","language":"Shell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mikeroyal.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2021-04-02T20:11:25.000Z","updated_at":"2026-03-21T18:43:44.000Z","dependencies_parsed_at":null,"dependency_job_id":"2edf337b-5f6e-4e52-917f-e428e5984931","html_url":"https://github.com/mikeroyal/IoT-Guide","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mikeroyal/IoT-Guide","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mikeroyal%2FIoT-Guide","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mikeroyal%2FIoT-Guide/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mikeroyal%2FIoT-Guide/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mikeroyal%2FIoT-Guide/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mikeroyal","download_url":"https://codeload.github.com/mikeroyal/IoT-Guide/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mikeroyal%2FIoT-Guide/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35576837,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-17T02:00:06.162Z","response_time":116,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-04T17:49:42.145Z","updated_at":"2026-07-17T10:00:37.954Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Node.js Tools","Swift Tools","Java Tools \u0026 Frameworks","Security Tools","Tools","SQL/NoSQL Tools and Databases","Python Frameworks and Tools","Node.js Learning Resources","Networking Tools \u0026 Concepts","Online ML Learning Resources","License","ML frameworks \u0026 applications","Java Learning Resources","Tools for Robotics","Open Source Security Learning Resources","Telco Learning Resources","Network Protocols","Kubernetes Learning Resources","SQL/NoSQL Learning Resources","Rust Learning Resources","Rust Tools","Security Standards, Frameworks and Benchmarks","Operating System","Python Learning Resources","Swift Learning Resources","Robotics Learning Resources","Learning Resources"],"sub_categories":["In-memory data grids","Interfaces","Toolkits"],"readme":"\u003ch1 align=\"center\"\u003e\n \u003cimg src=\"https://user-images.githubusercontent.com/45159366/146080708-26611923-bea3-4689-9765-f92cc59edc07.png\"\u003e\n  \u003cbr /\u003e\n IoT Guide\n\u003c/h1\u003e\n\n #### A guide for getting started with IoT devices including software and hardware that will make you a better and more efficient IoT developer.\n \n **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).**\n \n  \u003cp align=\"center\"\u003e\n \u003cimg src=\"https://user-images.githubusercontent.com/45159366/146080693-9a8bef64-edab-4a15-a42a-6e31d49b4d9e.png\"\u003e\n  \u003cbr /\u003e\n\u003c/p\u003e\n \n# Table of Contents\n\n\n1. [IoT Learning Resources](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#iot-learning-resources)\n\n2. [IoT Tools](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#iot-tools)\n \n3. [Networking](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#networking)\n\n4. [Databases](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#databases)\n\n5. [Telco 5G](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#telco-5g)\n\n6. [Open Source Security](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#open-source-security)\n\n7. [Differential Privacy](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#differential-privacy)\n\n8. [Kubernetes](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#kubernetes)\n\n9. [Machine Learning](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#machine-learning)\n\n10. [IoT Protocols](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#iot-protocols)\n\n11. [Operating systems (OS)](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#operating-systems)\n\n12. [Middleware](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#middleware)\n\n13. [Node Flow editors](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#node-flow-editors)\n\n14. [Toolkits](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#toolkits)\n\n15. [Data visualization](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#data-visualization)\n \n16. [Search](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#search)\n\n17. [Hardware](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#hardware)\n\n18. [In-memory data grids](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#in-memory-data-grids)\n\n19. [Home automation](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#home-automation)\n\n20. [Robotics](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#robotics)\n\n21. [Mesh networks](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#mesh-networks)\n\n22. [Node.js Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#nodejs-development)\n\n23. [Java Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#java-development)\n\n24. [Python Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#python-development)\n\n25. [Rust Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#rust-development)\n\n26. [Swift Development](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#swift-development)\n\n\n# IoT Learning Resources\n \n[Microsoft Certified: Azure IoT Developer Specialty](https://docs.microsoft.com/en-us/learn/certifications/azure-iot-developer-specialty)\n\n[AWS Internet of Things Foundation Series Training](https://www.aws.training/Details/Curriculum?id=27289)\n\n[Google’s Internet of Things (IoT)](https://developers.google.com/iot/)\n\n[Internet Of Things Courses from Udemy](https://www.udemy.com/topic/internet-of-things/)\n\n[IoT (Internet of Things) Courses from edX](https://www.edx.org/learn/iot-internet-of-things)\n\n[IoT (Internet of Things) Courses from Coursera](https://www.coursera.org/courses?languages=en\u0026query=iot)\n\n# IoT Tools\n\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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. \n\n[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.\n\n[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.\n\n[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. \n\n[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.\n\n[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.\n\n[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.\n\n[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).\n\n# Networking\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide#table-of-contents)\n\n\u003cp align=\"center\"\u003e\n \u003cimg src=\"https://user-images.githubusercontent.com/45159366/82833053-d1687b80-9e71-11ea-8c6d-074100f2f54b.png\"\u003e\n  \u003cbr /\u003e\n\u003c/p\u003e\n\n## Networking Tools \u0026 Concepts\n\n[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.\n\n[cURL Fuzzer](https://github.com/curl/curl-fuzzer) is a quality assurance testing for the curl project.\n\n[DoH](https://github.com/curl/doh) is a stand-alone application for DoH (DNS-over-HTTPS) name resolves and lookups.\n\n[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/).\n\n[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.\n\n[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.\n\n[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.\n\n[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 \u0026 HTTP servers.\n\n[HTTPStat](https://github.com/reorx/httpstat) is a tool that visualizes curl statistics in a simple layout.\n\n[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.\n\n[Websocat](https://github.com/vi/websocat) is a ommand-line client for WebSockets, like netcat (or curl) for ws:// with advanced socat-like functions.\n\n    • 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.\n\n    • 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.\n\nPackets 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.\n\n    • 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.\n\nA 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.\n\n    • 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.\n\n    • 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.\nIf an interface is connected to the WAN, it is generally assumed that it is reachable through the internet.\n\n    • 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.\n\nSome 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.\n\n    • 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.\n\n    • 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.\n\n    • 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.\n\n    • 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.\n\n## Network Layers\n\n\tWhile 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.\n\n\tAs 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.\n\n\tOne 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:\n\n    • 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.\n\n    • 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.\n\n    • Session: The session layer is a connection handler. It creates, maintains, and destroys connections between nodes in a persistent way.\n\n    • 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.\n\n    • 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.\n\n    • 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.\n\n    • 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).\n\nThe 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:\n\n    • 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.\nThe communication takes place between peers network.\n\n    • 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.\n\n    • 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.\n\n    • 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.\n\n### Interfaces\n**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.\n\n## Network Protocols\n\nNetworking 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.\n\n**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.\n\n**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.\n\n**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.\n\n**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.\n\n**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.\n\n**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.\n\n**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.\n\n**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.\n\n**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.\n\n[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.\n\n[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).\n\n[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.\n\n# Databases\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide#table-of-contents)\n\n\u003cp align=\"center\"\u003e\n \u003cimg src=\"https://user-images.githubusercontent.com/45159366/119279004-daec0700-bbdd-11eb-9662-b1fc86ec8448.png\"\u003e\n  \u003cbr /\u003e\n\u003c/p\u003e\n\n \u003cp align=\"center\"\u003e\n \u003cimg src=\"https://user-images.githubusercontent.com/45159366/119279002-da537080-bbdd-11eb-9d7a-44efb52f3506.png\"\u003e\n  \u003cbr /\u003e\n\u003c/p\u003e\n\n\n## SQL/NoSQL Learning Resources\n\n[SQL](https://en.wikipedia.org/wiki/SQL) is a standard language for storing, manipulating and retrieving data in relational databases.\n\n[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.\n\n[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.\n\n[Introduction to Transact-SQL](https://docs.microsoft.com/en-us/learn/modules/introduction-to-transact-sql/)\n\n[SQL Tutorial by W3Schools](https://www.w3schools.com/sql/)\n\n[Learn SQL Skills Online from Coursera](https://www.coursera.org/courses?query=sql)\n\n[SQL Courses Online from Udemy](https://www.udemy.com/topic/sql/)\n\n[SQL Online Training Courses from LinkedIn Learning](https://www.linkedin.com/learning/topics/sql)\n\n[Learn SQL For Free from Codecademy](https://www.codecademy.com/learn/learn-sql)\n\n[GitLab's SQL Style Guide](https://about.gitlab.com/handbook/business-ops/data-team/platform/sql-style-guide/)\n\n[OracleDB SQL Style Guide Basics](https://oracle.readthedocs.io/en/latest/sql/basics/style-guide.html)\n\n[Tableau CRM: BI Software and Tools](https://www.salesforce.com/products/crm-analytics/overview/)\n\n[Databases on AWS](https://aws.amazon.com/products/databases/)\n\n[Best Practices and Recommendations for SQL Server Clustering in AWS EC2.](https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/aws-sql-clustering.html)\n\n[Connecting from Google Kubernetes Engine to a Cloud SQL instance.](https://cloud.google.com/sql/docs/mysql/connect-kubernetes-engine)\n\n[Educational Microsoft Azure SQL resources](https://docs.microsoft.com/en-us/sql/sql-server/educational-sql-resources?view=sql-server-ver15)\n\n[MySQL Certifications](https://www.mysql.com/certification/)\n\n[SQL vs. NoSQL Databases: What's the Difference?](https://www.ibm.com/cloud/blog/sql-vs-nosql)\n\n[What is NoSQL?](https://aws.amazon.com/nosql/)\n\n## SQL/NoSQL Tools and Databases\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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).\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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).\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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/).\n\n[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.\n\n[MongoDB](https://www.mongodb.com/) is a document database meaning it stores data in JSON-like documents.\n\n[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.\n\n[MariaDB](https://mariadb.com/) is an enterprise open source database solution for modern, mission-critical applications.\n\n[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.\n\n[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.\n\n[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/).\n\n[Atlas](https://github.com/Netflix/atlas) is an in-memory dimensional [time series database](https://en.wikipedia.org/wiki/Time_series_database).\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n# Telco 5G\n\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)\n\n\n\u003cimg src=\"https://user-images.githubusercontent.com/45159366/105409952-14881380-5be6-11eb-84fc-b07db69698ed.png\"\u003e\n \n **VMware Cloud First Approach. Source: [VMware](https://www.vmware.com/products/telco-cloud-automation.html).**\n \n \n \u003cimg src=\"https://user-images.githubusercontent.com/45159366/105409956-1520aa00-5be6-11eb-8215-735c92a5470c.png\"\u003e\n \n **VMware Telco Cloud Automation Components. Source: [VMware](https://www.vmware.com/products/telco-cloud-automation.html).**\n \n \n## Telco Learning Resources\n\n[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)\n\n[Network Functions Virtualization Infrastructure (NFVI) by Cisco](https://www.cisco.com/c/en/us/solutions/service-provider/network-functions-virtualization-nfv-infrastructure/index.html)\n\n[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)\n\n[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)\n\n[5G Telco Cloud from VMware](https://telco.vmware.com/)\n\n[Maturing OpenStack Together To Solve Telco Needs from Red Hat](https://www.redhat.com/cms/managed-files/4.Nokia%20CloudBand%20\u0026%20Red%20Hat%20-%20Maturing%20Openstack%20together%20to%20solve%20Telco%20needs%20Ehud%20Malik,%20Senior%20PLM,%20Nokia%20CloudBand.pdf)\n\n[Red Hat telco ecosystem program](https://connect.redhat.com/en/programs/telco-ecosystem)\n\n[OpenStack for Telcos by Canonical](https://ubuntu.com/blog/openstack-for-telcos-by-canonical)\n\n[Open source NFV platform for 5G from Ubuntu](https://ubuntu.com/telco)\n\n[Understanding 5G Technology from Verizon](https://www.verizon.com/5g/)\n\n[Verizon and Unity partner to enable 5G \u0026 MEC gaming and enterprise applications](https://www.verizon.com/about/news/verizon-unity-partner-5g-mec-gaming-enterprise)\n\n[Understanding 5G Technology from Intel](https://www.intel.com/content/www/us/en/wireless-network/what-is-5g.html)\n\n[Understanding 5G Technology from Qualcomm](https://www.qualcomm.com/invention/5g/what-is-5g)\n\n[Telco Acceleration with Xilinx](https://www.xilinx.com/applications/wired-wireless/telco.html)\n\n[VIMs on OSM Public Wiki](https://osm.etsi.org/wikipub/index.php/VIMs)\n\n[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)\n\n[Citrix Certified Associate – Networking(CCA-N)](http://training.citrix.com/cms/index.php/certification/networking/)\n\n[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/)\n\n[CCNP Routing and Switching](https://learningnetwork.cisco.com/s/ccnp-enterprise)\n\n[Certified Information Security Manager(CISM)](https://www.isaca.org/credentialing/cism)\n\n[Wireshark Certified Network Analyst (WCNA)](https://www.wiresharktraining.com/certification.html)\n\n[Juniper Networks Certification Program Enterprise (JNCP)](https://www.juniper.net/us/en/training/certification/)\n\n[Cloud Native Computing Foundation Training and Certification Program](https://www.cncf.io/certification/training/)\n\n\n## Tools\n\n[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 \u0026 SDN for network traffic optimization to handle the core cloud-computing services of compute, networking, storage, identity, and image services.\n\n[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.\n\n[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.\n\n[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. \n\n[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. \n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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).\n\n[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.\n\n[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.\n\n[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.\n \n[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.\n \n[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.\n\n[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.\n\n# Open Source Security\n\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)\n\n\n[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.\n\n## Security Standards, Frameworks and Benchmarks\n\n[STIGs Benchmarks - Security Technical Implementation Guides](https://public.cyber.mil/stigs/)\n\n[CIS Benchmarks - CIS Center for Internet Security](https://www.cisecurity.org/cis-benchmarks/)\n\n[NIST - Current FIPS](https://www.nist.gov/itl/current-fips)\n\n[ISO Standards Catalogue](https://www.iso.org/standards.html)\n\n[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. \n\n[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).\n\n[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.\n\n[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.\nIt 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.\n\n[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.\n\n[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).\n\n[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.\n\n[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. \n\n[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.\n\n## Security Tools\n\n[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.\n\n[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.\n\n[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.\n\n[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. \n\n[Libgcrypt](https://www.gnupg.org/related_software/libgcrypt/) is a general purpose cryptographic library originally based on code from GnuPG.\n\n[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.\n\n[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.\n\n[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.\n\n[Burp Suite](https://portswigger.net/burp) is a leading range of cybersecurity tools.\n\n[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.\n\n[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.\n\n[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.\n\n[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. \n\n[Hubble](https://github.com/cilium/hubble) is a Network, Service \u0026 Security Observability for Kubernetes using eBPF.\n\n[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.\n\n[Certgen](https://github.com/cilium/certgen) is a convenience tool to generate and store certificates for Hubble Relay mTLS.\n\n[Scapy](https://scapy.net/) is a python-based interactive packet manipulation program \u0026 library.\n\n[syzkaller](https://github.com/google/syzkaller) is an unsupervised, coverage-guided kernel fuzzer.\n\n[SchedViz](https://github.com/google/schedviz) is a tool for gathering and visualizing kernel scheduling traces on Linux machines.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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. \n\n[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. \n\n[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.\n\n[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.\n\n[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.\n\n[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. \n\n[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.\n\n[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. \n\n[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.\n\n[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.\n\n[ClamAV](https://www.clamav.net/) is an open source antivirus engine for detecting trojans, viruses, malware \u0026 other malicious threats.\n\n## Open Source Security Learning Resources\n\n[Microsoft Open Source Software Security](https://www.microsoft.com/en-us/securityengineering/opensource)\n\n[Cloudflare Open Source Security](https://cloudflare.github.io)\n\n[The Seven Properties of Highly Secure Devices](https://www.microsoft.com/en-us/research/publication/seven-properties-highly-secure-devices/)\n\n[How Layer 7 of the Internet Works](https://www.cloudflare.com/learning/ddos/what-is-layer-7/)\n\n[The 7 Kinds of Security](https://www.veracode.com/sites/default/files/Resources/eBooks/7-kinds-of-security.pdf)\n\n[The Libgcrypt Reference Manual](https://www.gnupg.org/documentation/manuals/gcrypt/)\n\n[The Open Web Application Security Project(OWASP) Foundation Top 10](https://owasp.org/www-project-top-ten/)\n\n[Best Practices for Using Open Source Code from The Linux Foundation](https://www.linuxfoundation.org/blog/2017/11/best-practices-using-open-source-code/)\n\n[AWS Certified Security - Specialty Certification](https://aws.amazon.com/certification/certified-security-specialty/)\n\n[Microsoft Certified: Azure Security Engineer Associate](https://docs.microsoft.com/en-us/learn/certifications/azure-security-engineer)\n\n[Google Cloud Certified Professional Cloud Security Engineer](https://cloud.google.com/certification/cloud-security-engineer)\n\n[Cisco Security Certifications](https://www.cisco.com/c/en/us/training-events/training-certifications/certifications/security.html)\n\n[The Red Hat Certified Specialist in Security: Linux](https://www.redhat.com/en/services/training/ex415-red-hat-certified-specialist-security-linux-exam)\n\n[Linux Professional Institute LPIC-3 Enterprise Security Certification](https://www.lpi.org/our-certifications/lpic-3-303-overview)\n\n[Cybersecurity Training and Courses from IBM Skills](https://www.ibm.com/skills/topics/cybersecurity/)\n\n[Cybersecurity Courses and Certifications by Offensive Security](https://www.offensive-security.com/courses-and-certifications/)\n\n[RSA Certification Program](https://community.rsa.com/community/training/certification)\n\n[Check Point Certified Security Expert(CCSE) Certification](https://training-certifications.checkpoint.com/#/courses/Check%20Point%20Certified%20Expert%20(CCSE)%20R80.x)\n\n[Check Point Certified Security Administrator(CCSA) Certification](https://training-certifications.checkpoint.com/#/courses/Check%20Point%20Certified%20Admin%20(CCSA)%20R80.x)\n\n[Check Point Certified Security Master (CCSM) Certification](https://training-certifications.checkpoint.com/#/courses/Check%20Point%20Certified%20Master%20(CCSM)%20R80.x)\n\n[Certified Cloud Security Professional(CCSP) Certification](https://www.isc2.org/Certifications/CCSP)\n\n[Certified Information Systems Security Professional (CISSP) Certification](https://www.isc2.org/Certifications/CISSP)\n\n[CCNP Routing and Switching](https://learningnetwork.cisco.com/s/ccnp-enterprise)\n\n[Certified Information Security Manager(CISM)](https://www.isaca.org/credentialing/cism)\n\n[Wireshark Certified Network Analyst (WCNA)](https://www.wiresharktraining.com/certification.html)\n\n[Juniper Networks Certification Program Enterprise (JNCP)](https://www.juniper.net/us/en/training/certification/)\n\n[Security Training Certifications and Courses from Udemy](https://www.udemy.com/courses/search/?src=ukw\u0026q=secuirty)\n\n[Security Training Certifications and Courses from Coursera](https://www.coursera.org/search?query=security\u0026)\n\n[Security Certifications Training from Pluarlsight](https://www.pluralsight.com/browse/information-cyber-security/security-certifications)\n\n# Differential Privacy\n\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://user-images.githubusercontent.com/45159366/103486337-ff238480-4db1-11eb-9895-f7f49cc5715a.png\"\u003e\n  \u003cbr /\u003e\n  Above is a simple diagram of how Differential Privacy-Preserving Data Sharing and Data Mining protects a User's Data\n\u003c/p\u003e\n\n## Learning Resources\n\n[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\".\n\n[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.\n\n[Laplacian Noise](https://en.wikipedia.org/wiki/Laplace_distribution) is a mechanism that adds Laplacian-distributed noise to a function.\n\n[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)\n\n[Apple's Differential Privacy Overview](https://www.apple.com/privacy/docs/Differential_Privacy_Overview.pdf)\n\n[Learning with Privacy at Scale with Apple Machine Learning](https://machinelearning.apple.com/research/learning-with-privacy-at-scale)\n\n[Microsoft Research Differential Privacy Overview](https://www.microsoft.com/en-us/research/publication/differential-privacy/)\n\n[Responsible Machine Learning with Microsoft Azure](https://azure.microsoft.com/en-us/services/machine-learning/responsibleml/)\n\n[Responsible AI Resources with Microsoft AI](https://www.microsoft.com/en-us/ai/responsible-ai-resources)\n\n[Preserve data privacy by using differential privacy and the SmartNoise package](https://docs.microsoft.com/en-us/azure/machine-learning/concept-differential-privacy)\n\n[Open Differential Privacy(OpenDP) Initiative by Microsoft and Harvard](https://projects.iq.harvard.edu/opendp)\n\n[Google's Differential Privacy Library](https://github.com/google/differential-privacy)\n\n[Computing Private Statistics with Privacy on Beam from Google Codelabs](https://codelabs.developers.google.com/codelabs/privacy-on-beam/#0)\n\n[Introducing TensorFlow Privacy: Learning with Differential Privacy for Training Data](https://blog.tensorflow.org/2020/06/introducing-new-privacy-testing-library.html)\n\n[TensorFlow Federated: Machine Learning on Decentralized Data](https://www.tensorflow.org/federated/)\n\n[Federated Analytics: Collaborative Data Science without Data Collection](https://ai.googleblog.com/2020/05/federated-analytics-collaborative-data.html)\n\n[Differentially-Private Stochastic Gradient Descent(DP-SGD)](https://github.com/tensorflow/privacy/blob/master/tutorials/walkthrough/README.md)\n\n[Learning Differential Privacy from Harvard University Privacy Tools Project](https://privacytools.seas.harvard.edu/differential-privacy)\n\n[Harvard University Privacy Tools Project Courses \u0026 Educational Materials](https://privacytools.seas.harvard.edu/courses-educational-materials)\n\n[The Weaknesses of Differential Privacy course on Coursera](https://www.coursera.org/lecture/data-results/weaknesses-of-differential-privacy-50Y9k)\n\n[The Differential Privacy of Bayesian Inference](https://privacytools.seas.harvard.edu/publications/differential-privacy-bayesian-inference)\n\n[Simultaneous private learning of multiple concepts](https://privacytools.seas.harvard.edu/publications/simultaneous-private-learning-multiple-concepts)\n\n[The Complexity of Computing the Optimal Composition of Differential Privacy](https://privacytools.seas.harvard.edu/publications/complexity-computing-optimal-composition-differential-privacy)\n\n[Order revealing encryption and the hardness of private learning](https://privacytools.seas.harvard.edu/publications/order-revealing-encryption-and-hardness-private-learning)\n\n[SAP HANA data anonymization using SAP Software Solutions](https://www.sap.com/cmp/dg/crm-xt17-ddm-data-anony/index.html)\n\n[SAP HANA Security using their In-Memory Database](https://www.sap.com/products/hana/features/security.html)\n\n[DEFCON Differential Privacy Training Launch](https://opensource.googleblog.com/2020/08/defcon-differential-privacy-training.html)\n\n[Secure and Private AI course on Udacity](https://www.udacity.com/course/secure-and-private-ai--ud185)\n\n[Differential Privacy - Security and Privacy for Big Data - Part 1 course on Coursera](https://www.coursera.org/learn/security-privacy-big-data)\n\n[Differential Privacy - Security and Privacy for Big Data - Part 2 course on Coursera](https://www.coursera.org/learn/security-privacy-big-data-protection)\n\n[Certified Ethical Emerging Technologist Professional Certificate course on Coursera](https://www.coursera.org/professional-certificates/certified-ethical-emerging-technologist)\n\n\n## Tools\n\n[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/).\n\n[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.\n\n[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. \n\n[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.\n\n[PyDP](https://github.com/OpenMined/PyDP) is a Python wrapper for Google's Differential Privacy project.\n\n[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.\n\n[BoTorch](https://botorch.org) is a library for Bayesian Optimization built on PyTorch.\n\n[PyTorch Geometric (PyG)](https://github.com/rusty1s/pytorch_geometric) is a geometric deep learning extension library for [PyTorch](https://pytorch.org/).\n\n[Skorch](https://github.com/skorch-dev/skorch) is a scikit-learn compatible neural network library that wraps PyTorch.\n\n[Diffprivlib](https://github.com/IBM/differential-privacy-library) is the IBM Differential Privacy Library for experimenting with, investigating and developing applications in, differential privacy.\n\n[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.\n\n[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.\n\n# Kubernetes\n\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)\n\n[Kubernetes (K8s)](https://kubernetes.io/) is an open-source system for automating deployment, scaling, and management of containerized applications.\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://user-images.githubusercontent.com/45159366/105645195-db9ea780-5e4e-11eb-8357-fb38b2f06d74.png\"\u003e\n\n**Building Highly-Availability(HA) Clusters with kubeadm. Source: [Kubernetes.io](https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/high-availability/)**\n\u003c/p\u003e\n\n[Google Kubernetes Engine (GKE)](https://cloud.google.com/kubernetes-engine/) is a managed, production-ready environment for running containerized applications.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[Red Hat Openshift](https://www.openshift.com/) is a fully managed Kubernetes platform that provides a foundation for on-premises, hybrid, and multicloud deployments. \n\n[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.\n\n[Odo](https://odo.dev/) is a fast, iterative, and straightforward CLI tool for developers who write, build, and deploy applications on Kubernetes and OpenShift.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[KubeInit](https://github.com/kubeinit/kubeinit) provides Ansible playbooks and roles for the deployment and configuration of multiple Kubernetes distributions.\n\n[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.\n\n[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. \n\n[Helm](https://helm.sh/) is a Kubernetes Package Manager tool that makes it easier to install and manage Kubernetes applications.\n\n[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. \n\n[KubeFlow](https://www.kubeflow.org/) is a tool dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable.\n\n[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.\n\n[OpenEBS](https://openebs.io/) is a Kubernetes-based tool to create stateful applications using Container Attached Storage.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n## Kubernetes Learning Resources\n\n[Getting Kubernetes Certifications](https://training.linuxfoundation.org/certification/catalog/?_sft_technology=kubernetes)\n\n[Getting started with Kubernetes on AWS](https://aws.amazon.com/kubernetes/)\n\n[Kubernetes on Microsoft Azure](https://azure.microsoft.com/en-us/topic/what-is-kubernetes/)\n\n[Intro to Azure Kubernetes Service](https://docs.microsoft.com/en-us/azure/aks/kubernetes-dashboard)\n\n[Getting started with Google Cloud](https://cloud.google.com/learn/what-is-kubernetes)\n\n[Getting started with Kubernetes on Red Hat](https://www.redhat.com/en/topics/containers/what-is-kubernetes)\n\n[Getting started with Kubernetes on IBM](https://www.ibm.com/cloud/learn/kubernetes)\n\n[YAML basics in Kubernetes](https://developer.ibm.com/technologies/containers/tutorials/yaml-basics-and-usage-in-kubernetes/)\n\n[Elastic Cloud on Kubernetes](https://www.elastic.co/elastic-cloud-kubernetes)\n\n[Docker and Kubernetes](https://www.docker.com/products/kubernetes)\n\n[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)\n\n[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/)\n\n[Running Apache Spark on Kubernetes](http://spark.apache.org/docs/latest/running-on-kubernetes.html)\n\n[Kubernetes Across VMware vRealize Automation](https://blogs.vmware.com/management/2019/06/kubernetes-across-vmware-cloud-automation-services.html)\n\n[VMware Tanzu Kubernetes Grid](https://tanzu.vmware.com/kubernetes-grid)\n\n[All the Ways VMware Tanzu Works with AWS](https://tanzu.vmware.com/content/blog/all-the-ways-vmware-tanzutm-works-with-aws)\n\n[VMware Tanzu Education](https://tanzu.vmware.com/education)\n\n[Using Ansible in a Cloud-Native Kubernetes Environment](https://www.ansible.com/blog/how-useful-is-ansible-in-a-cloud-native-kubernetes-environment)\n\n[Managing Kubernetes (K8s) objects with Ansible](https://docs.ansible.com/ansible/latest/collections/community/kubernetes/k8s_module.html)\n\n[Setting up a Kubernetes cluster using Vagrant and Ansible](https://kubernetes.io/blog/2019/03/15/kubernetes-setup-using-ansible-and-vagrant/)\n\n[Running MongoDB with Kubernetes](https://www.mongodb.com/kubernetes)\n\n[Kubernetes Fluentd](https://docs.fluentd.org/v/0.12/articles/kubernetes-fluentd)\n\n[Understanding the new GitLab Kubernetes Agent](https://about.gitlab.com/blog/2020/09/22/introducing-the-gitlab-kubernetes-agent/)\n\n[Kubernetes Contributors](https://www.kubernetes.dev/)\n\n[KubeAcademy from VMware](https://kube.academy/)\n\n\n# Machine Learning\n\n[Back to the Top](https://github.com/mikeroyal/IoT-Guide/blob/main/README.md#table-of-contents)\n\n\u003cimg src=\"https://user-images.githubusercontent.com/45159366/108111395-756e0480-7049-11eb-85ca-b87315e9d3ef.jpeg\"\u003e\n\n## ML frameworks \u0026 applications\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[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. \n\n[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.\n\n[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.\n\n[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.\n\n[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/).\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n[Cluster Manager for Apache Kafka(CMAK)](https://github.com/yahoo/CMAK) is a tool for managing [Apache Kafka](https://kafka.apache.org/) clusters.\n\n[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.\n\n[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.\n\n[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:\n\n**[MLflow Tracking](https://mlflow.org/docs/latest/tracking.html)**: Record and query experiments: code, data, config, and results.\n\n**[MLflow Projects](https://mlflow.org/docs/latest/projects.html)**: Package data science code in a format to reproduce runs on any platform.\n\n**[MLflow Models](https://mlflow.org/docs/latest/models.html)**: Deploy machine learning models in diverse serving environments.\n\n**[Model Registry](https://mlflow.org/docs/latest/model-registry.html)**: Store, annotate, discover, and manage models in a central repository.\n\n[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.\n\n[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.\n\n[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.\n\n[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.\n\n## Online ML Learning Resources\n\n[Machine Learning by Stanford University from Coursera](https://","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/mikeroyal%2Fiot-guide/projects"}