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https://github.com/tushar-borole/dope-stacks

Curated list of open source stack
https://github.com/tushar-borole/dope-stacks

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dope-stacks


This repo contain awsome open source stacks


Frontend




  • React : React makes it painless to create

    interactive UIs


  • Vuejs : Vue.js is an open-source JavaScript framework for building user interfaces and single-page applications.


  • react-native : Build native mobile apps using JavaScript and React


  • Flutter : Flutter is an open-source mobile application development framework


  • svelte : Instead of using techniques like virtual DOM diffing, Svelte writes code that surgically updates the DOM when the state of your app changes.


  • Polymer Project.org/ : Web component form web.


  • Typescript : TypeScript is a typed superset of JavaScript that compiles to plain JavaScript.


Database




  • PrestoDB Presto was designed and written

    from the ground up for interactive analytics and approaches the speed

    of commercial data warehouses while scaling to the size of

    organizations like Facebook.


  • Apache Druid : Druid is an is a high performance

    real-time analytics database


  • Pinot : Pinot is a realtime distributed

    OLAP datastore, which is used at LinkedIn to deliver scalable real

    time analytics with low latency.


  • Prometheus : It is used to record real-time

    metrics in a time series

    database
    (allowing for high dimensionality) built using a

    HTTP pull model, with flexible queries and real-time alerting.


  • influxdb : InfluxDB is the open source time series database


CI/CD




  • Spinnaker : Spinnaker is an open source, multi-cloud continuous delivery platform for releasing software changes with high velocity and confidence.


Machine Learning and AI




  • PyTorch : Deep learning Framework.


  • M3 db : ## The fully open source metrics platform

    built on M3DB, a distributed timeseries database


  • Tensor Flow : TensorFlow is an

    end-to-end open source platform for machine learning


All About Containers




  • Peloton : a unified scheduler

    designed to manage resources across distinct workloads, combining our

    separate clusters into a unified one


  • Mesos : Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual), enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.


  • Kubernetes : Automated container deployment, scaling, and management


  • Conductor : Conductor is a microservices orchestration engine


Data Analytics




  • Superset : Superset provides

    intuitive interface to explore and visualize datasets, and create

    interactive dashboards.


Networking




  • grpc : A high performance, open-source universal RPC framework


  • kuma : Kuma is a universal open source control-plane for Service Mesh and Microservices that can run and be operated natively across both Kubernetes and VM environments.


Serverless




  • Openwisk : Apache OpenWhisk (Incubating) is an open source, distributed Serverless platform that executes functions (fx) in response to events at any scale.


  • Serverless Framework : The Serverless Framework consists of an open source CLI that makes it easy to develop, deploy and test serverless apps across different cloud providers.


Testing




  • Enzyme : Enzyme is a JavaScript Testing

    utility for React that makes it easier to test your React Components’

    output.


  • taiko : Taiko is a free and open source browser automation tool built by the team behind Gauge by ThoughtWorks.


Distributed System




  • zookeeper : ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services.


  • cadenceworkflow : Cadence fault-oblivious stateful code platform preserves complete multithreaded application state including thread stacks with local variables across hardware and software failures


Big Data




  • Parquet : Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language.


  • Orc : the smallest, fastest columnar storage for Hadoop workloads.


Monitoring




  • stackdriver : Monitor, troubleshoot, and improve infrastructure and application performance


Documentation




  • Docusaurus : Docusaurus makes it easy to maintain Open Sourcedocumentation websites


  • Storybook : Storybook provides a sandbox to build UI components in isolation so you can develop hard-to-reach states and edge cases.


  • docz : Documentation makes easy


  • react-styleguidist : Isolated React component development environment with a living style guide


Performance



Messaging




  • Pulsar : pache Pulsar is an open-source distributed pub-sub messaging system originally created at Yahoo and now part of the Apache Software Foundation


  • Kafka : Kafka is a distributed

    streaming platform



Miscellaneous




  • Airpal : a web-based query execution

    tool built on top of Facebook’s PrestoDB.


  • Airflow : Airflow is a platform to

    programmatically author, schedule and monitor workflows.


  • Vitess : Vitess is a database clustering system for horizontal scaling of MySQL


  • Apache Beam : Implement batch and

    streaming data processing jobs that run on any execution engine.


  • Apache Flink : Flink has been designed

    to run in all common cluster environments, perform computations at

    in-memory speed_ and at any scale


  • bazel.build : Build and test software of any size, quickly and reliably


  • jaegertracing : open source, end-to-end distributed tracing


Contributing


Open an issue first to discuss potential changes/additions. If you have questions with the guide, feel free to leave them as issues in the repository. If you find a typo, create a pull request. The idea is to keep the content up to date and use github’s native feature to help tell the story with issues and PR’s, which are all searchable via google. Why? Because odds are if you have a question, someone else does too! You can learn more here at about how to contribute.


By contributing to this repository you are agreeing to make your content available subject to the license of this repository.


Process


1. Discuss the changes in a GitHub issue.

2. Open a Pull Request, reference the issue, and explain the change and why it adds value.
3. The Pull Request will be evaluated and either merged or declined.

License


Use this guide. Attributions are appreciated._


Copyright


Copyright © 2014-2015 Tushar Borole


(The MIT License)


Permission is hereby granted, free of charge, to any person obtaining

a copy of this software and associated documentation files (the

‘Software’), to deal in the Software without restriction, including

without limitation the rights to use, copy, modify, merge, publish,

distribute, sublicense, and/or sell copies of the Software, and to

permit persons to whom the Software is furnished to do so, subject to

the following conditions:


The above copyright notice and this permission notice shall be

included in all copies or substantial portions of the Software.


THE SOFTWARE IS PROVIDED ‘AS IS’, WITHOUT WARRANTY OF ANY KIND,

EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF

MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.

IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY

CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,

TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE

SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


Last but not least


This is made in San Francisco with love and passion ʕ´•ᴥ•`ʔ