OpenWhisk - A platform for cloud native, serverless, event driven apps


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Cloud computing has recently evolved to enable developers to write cloud native applications better, faster, and cheaper using serverless technology. 

OpenWhisk provides an open source platform to enable cloud native, serverless, event driven applications.

This presentation lays out the technical and business drivers behind the rise of serverless architectures, and provides an intro to the OpenWhisk open source project.

Presented at Cloud Native Day in Toronto, Canada on August 25, 2016.

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OpenWhisk - A platform for cloud native, serverless, event driven apps

  1. 1. OpenWhisk Cloud native • Serverless • Event driven • Microservices @DanielKrook • IBM Cloud
  2. 2. What you will learn today • How cloud computing has recently evolved to enable developers to write cloud native applications better, faster, and cheaper using serverless technology. • How OpenWhisk provides an open source platform to enable cloud native, serverless, event driven applications.
  3. 3. What makes serverless, event driven computing so compelling?
  4. 4. Cloud evolution means developers can write apps better, faster, and cheaper Bare metal Virtual machines Containers Functions Decreasing  concern  (and  control)  over  stack  implementation Increasing  focus  on  business  logic
  5. 5. Newer workloads are a better fit for event driven programming Execute app logic in response to database triggers Execute app logic in response to sensor data Execute app logic in response to cognitive trends Execute app logic in response to scheduled tasks Provide easy server-side backend for mobile app
  6. 6. Problem: It’s expensive to scale microservices Explosion in number of containers / processes: 1. Increase of infrastructure cost footprint 2. Increase of operational management cost and complexity Region BRegion A Break-­down  into  microservices Make  each  micro  service  HA Protect  against  regional  outages Monolithic application
  7. 7. Serverless can handle many cloud native app 12 Factors I Codebase Handled by developer (Manage versioning of functions on their own) II Dependencies Handled by developer, facilitated by serverless platform (Runtimes and packages) III Config Handled by platform (Environment variables or injected event parameters) IV Backing services Handled by platform (Connection information injected as event parameters) V Build, release, run Handled by platform (Deployed resources are immutable and internally versioned) VI Processes Handled by platform (Single stateless containers often used) VII Port binding Handled by platform (Actions or functions are automatically discovered) VIII Concurrency Handled by platform (Process model is hidden and scales in response to demand) IX Disposability Handled by platform (Lifecycle is hidden from the user, fast startup and elastic scale is prioritized) X Dev/prod parity Handled by developer (The developer is the deployer. Scope of what differs is narrower) XI Logs Handled by platform (Developer writes to console.log, platform handles log streaming) XII Admin processes Handled by developer (No distinction between one off processes and long running)
  8. 8. Problem: Programming and pricing models aren’t efficient Continuous polling needed in the absence of an event driven programming model Charged for resources, even when idle Worries persist about capacity management Swif t Application Container VMCF 2 Polling 1b Request 1a
  9. 9. Cost model offers a better match between app and resources Applications charged by compute time (millisecond) rather than reserved memory (GB/hour). While many applications must still be deployed in a daemon model, serverless provides an alternative that can mean substantial cost savings for a variety of event driven workloads. Greater linkage between cloud resources used and business operations executed.
  10. 10. Technological and business factors make serverless compelling Serverless platforms and frameworks are gaining traction Cost models getting more granular and efficient Growth of event driven workloads that need automated scale Platforms evolving to facilitate cloud native design for developers
  11. 11. Introducing OpenWhisk
  12. 12. OpenWhisk in a nutshell OpenWhisk is a cloud platform that executes code in response to events OpenWhisk
  13. 13. OpenWhisk is different than other hosted services Serverless deployment and operations model Optimized utilization, fine grained pricing at any scale Flexible programming model with powerful tooling Open source and open ecosystem Ability to run in public, private, and hybrid models OpenWhisk
  14. 14. OpenWhisk supports many growing workloads OpenWhisk can help power various mobile, web and IoT app use cases by simplifying the programming model of orchestrating various services using events without a dedicated backend. Digital app workloads Big Data/Analytics pipeline Complex data pipelines for Big Data/Analytics tasks can be scripted using changes in data services or streams for near real-time analytics and feedback. DevOps and infrastructure as code OpenWhisk can be used to automate DevOps pipelines based on events triggered from successful builds, or completed staging, or a go-live event. Microservices builder OpenWhisk can be used to easily build microservices given the footprint and programming model desired by microservices
  15. 15. The OpenWhisk programming model
  16. 16. Triggers, actions, rules (and packages) Data sources define the events they emit as triggers. Developers associate actions to handle the events via rules. T A R
  17. 17. Triggers A class of events that can occurT Social events Data changes Device readings Location updates User input
  18. 18. Actions Code that runs in response to an event (that is, an event handler) A
  19. 19. Actions Can be written in a variety of languages, such as JavaScript, Python, Java, and Swift A function main(params)  { return  {  message:  'Hello,  ' + +  '  from  ' + }; };
  20. 20. Actions Or any other language by packaging with DockerA
  21. 21. Actions Can be composed to create sequences that increase flexibility and foster reuse A AA := A1 + A2 + A3 AB := A2 + A1 + A3 AC := A3 + A1 + A2
  22. 22. Rules An association of a trigger to an action in a many to many mapping. R R := T A
  23. 23. Packages A shared collection of triggers and actionsP A A read write T changes A translate A forecast A post T topic Open Source A myAction T myFeed Yours T commit Third Party
  24. 24. OpenWhisk in action
  25. 25. The OpenWhisk execution model Pool of actions Swift DockerJS Trigger 1 Running action Running action Running action 3 OpenWhisk Engine 2 A T AAA
  26. 26. OpenWhisk enables event driven applications Event Providers Cloudant GitHub Weather … Which triggers execution of associated OpenWhisk action 2 Slack JS Swift Docker … An event occurs, for example • Commit pushed to GitHub repository • Data changed in Cloudant 1 OpenWhisk
  27. 27. OpenWhisk can implement REST microservices Send HTTP request HTTP GET 1 Invoke OpenWhisk action get-customers Browser Mobile App Web App 2 JS Swift Docker … OpenWhisk API Proxy
  28. 28. Watson IOT OpenWhisk Customer registry Shipping system SendGrid Service reports actions IBM Cloud LOB, SoR systems & databases Need a new filter Email: Filter on its way!
  29. 29. analyze reading OpenWhisk create order alert customer alarm changes changes service order appliance feed Watson IoT A A AT T T T P P P
  30. 30. OpenWhisk CLI: Create and test action Create the Action that analyzes IoT readings, then stores in the database wsk action create analyze-service-event analyze-service-event.js --param cloudant_user $CLOUDANT_USER --param cloudant_pass $CLOUDANT_PASS Invoke the Action manually with sample message data to test wsk action invoke --blocking --result analyze-service-event --param service '{"appliance_serial": "xxxxyyyyzzzz", "part_number": "ddddeeeeffff", "reading": 13, "timestamp": 1466188262}' A
  31. 31. OpenWhisk CLI: Link trigger to action Create the Trigger that subscribes to an MQTT topic pattern wsk trigger create openfridge-feed-trigger --feed mqtt/mqtt-feed-action --param topic 'iot-2/type/+/id/+/evt/+/fmt/json' --param url 'ssl://’ Link the Trigger to the action using a Rule wsk rule create --enable openfridge-feed-rule openfridge-feed-trigger analyze-service-event R := T A
  32. 32. OpenWhisk high level implementation architecture
  33. 33. OpenWhisk design principles 1. Provide an open interface for event providers 2. Offer polyglot support and simple extensibility for new runtimes 3. Support higher level constructs as appropriate (e.g. action sequences) 4. Scale dynamically on a per request basis 5. Enable sharing of actions and event providers 6. Leverage best of breed open source software (Docker, Kafka, Consul, …) 7. Use the Apache 2 License
  34. 34. OpenWhisk under the hood Consul Couch DB Router (NGINX) Controller Kafka Invoker Invoker Docker Executor Executor Docker Java Swift Executor Executor NodeJS Python 1. Router receives request to API via CLI or UI 2. Controller checks entitlement and dispatches requests to Kafka 3. Invokers pull requests and start execution of the action
  35. 35. Summary
  36. 36. What you learned today • We’re in the early days of an evolution that is empowering developers to write cloud native applications better, faster, and cheaper • OpenWhisk provides an open source platform to enable cloud native, serverless, event driven applications
  37. 37. Join us to build a cloud native platform for the future! #openwhisk
  38. 38. See a demo at the IBM booth!
  39. 39. OpenWhisk Cloud native • Serverless • Event driven • Microservices