The Netflix API for a global service
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The document discusses Netflix's API architecture and its significance in supporting a global streaming service. It covers various aspects such as resiliency, developer velocity, tooling, and DevOps practices, with insights into features like personalization, recommendations, and failure management strategies. It also highlights the challenges of scaling and capacity management, as well as the importance of continuous delivery and real-time analysis in enhancing service performance.
![Script isolation & node
❏ Groovy scripts run as
part of API process
❏ UI teams would like to
use other languages
(in particular node.js)
var response = model.get("todos[0..2]
['name','done']");
API remote
service layer
Client libs
UI/device
scripts (node)
Falcor
Services](https://image.slidesharecdn.com/devnexustalkfebruary2016-topublish2-160228001417/85/The-Netflix-API-for-a-global-service-50-320.jpg)
The Netflix API for a global service
- 1. The Netflix API for a global service Katharina Probst Engineering Manager, API DevNexus, February 2016
- 2. What is Netflix? Stream TV shows and movies anywhere, any time.
- 3. Global! (except China and where we can’t operate for legal reasons)
- 5. Scale ❏ Peak downstream traffic in the US is 37%, upstream almost 7%. ❏ 75 Million subscribers worldwide and growing Source: http://www.sandvine.com/news/global_broadband_trends.asp
- 6. Netflix API ❏ Architecture ❏ Resiliency ❏ Developer velocity ❏ Tooling and DevOps ❏ Current and future directions API
- 7. Netflix API ❏ Architecture ❏ Resiliency ❏ Developer velocity ❏ Tooling and DevOps ❏ Current and future directions API
- 8. API Personali- zation Engine User Info Ratings Similar Movies A/B Test Engine …. ELB Zuul (gateway)
- 10. What is the API used for? Examples: ❏ Discovery ❏ Recommendations ❏ Move metadata ❏ Ratings ❏ Sign-up and Profiles ❏ Playback ❏ Bookmarks ❏ DRM ❏ A/B testing API
- 11. Direct dependencies on other services
- 12. Netflix API ❏ Architecture ❏ Resiliency ❏ Developer velocity ❏ Tooling and DevOps ❏ Current and future directions API
- 13. Hystrix Primer ❏ Protection from and control over latency and failure from dependencies ❏ Stop cascading failures in a complex distributed system ❏ Fall back and gracefully degrade ❏ Fail fast and rapidly recover https://github.com/Netflix/Hystrix
- 15. API Personali- zation Engine User Info Ratings Similar Movies A/B Test Engine …. Don’t let this happen.
- 16. API Personali- zation Engine User Info Ratings Similar Movies A/B Test Engine …. Don’t let this happen.
- 18. Failure Injection Testing (FIT) Goal: Study how the system behaves when a failures occur (e.g., backend service unreachable).
- 19. More automated failure testing Goal: Find groups of service calls that are needed for success. http://techblog.netflix.com/2016/01/automated-failure-testing.html
- 20. Autoscaling & Capacity Management http://nflx.it/1LvqLUi
- 21. Autoscaling & Capacity Management ❏ Red: traffic for current week (x-axis) ❏ Black: traffic for previous week for comparison ❏ What happened on February 7? Superbowl!
- 22. AWS Controls Reactive, does not scale up fast enough
- 23. Fine-grained Control with Scryer Complements AWS Controls ❏ Faster scale-up, improved cost ❏ Use reactive policy for organic scale down
- 24. Netflix API ❏ Architecture ❏ Resiliency ❏ Developer velocity ❏ Tooling and DevOps ❏ Current and future directions API
- 25. Lots of devices, lots of variety
- 27. And just to make things a little more interesting…. ❏ A/B tests ❏ profiles ❏ localization
- 28. Add server-side scripting capability ❏ Reduce network chattiness ❏ Support device optimizations ❏ Enable faster development for internal users
- 29. Discrete HTTP requests pay network tax repeatedly
- 30. Single, optimized request; pay network tax once Client data assembly logic pushed to server
- 32. ❏ UI (script) changes can happen independently ❏ Script changes can be pushed to running servers, so decoupled from API push schedule ❏ Decoupling leads to greater developer velocity Impact on velocity and collaboration
- 33. Netflix API ❏ Architecture ❏ Resiliency ❏ Developer velocity ❏ Tooling and DevOps ❏ Current and future directions API
- 34. Run 1% of your traffic on the new code and see how it does
- 35. ❏ Errors: 2xx, 4xx, 5xx ❏ latency ❏ network ❏ busy threads ❏ load, memory consumption ❏ ... So you’ve run a canary. Now what? Control Canary
- 38. Continuous Delivery with Spinnaker http://techblog.netflix.com/2015/09/moving-from-asgard-to-spinnaker.html
- 39. Quickly see status of all clusters http://techblog.netflix.com/2015/09/moving-from-asgard-to-spinnaker.html
- 40. Prod is a little different….
- 41. The things you can do … with server groups … with instances
- 44. Operations
- 45. Operations
- 46. Operations
- 47. Real-time analysis http://www.slideshare.net/g9yuayon/qcon-talk-on-netflix-mantis-a-stream-processing-system Submit a query, see requests in real time.
- 48. Netflix API ❏ Architecture ❏ Resiliency ❏ Developer velocity ❏ Tooling and DevOps ❏ Current and future directions API
- 49. ● > 900 active endpoints ● ~60 direct dependencies ● 78 thread pools ● 1000+ threads ● high memory usage What we’ve grown to
- 50. Script isolation & node ❏ Groovy scripts run as part of API process ❏ UI teams would like to use other languages (in particular node.js) var response = model.get("todos[0..2] ['name','done']"); API remote service layer Client libs UI/device scripts (node) Falcor Services
- 51. Thin client libraries ❏ Fat client libraries ❏ business logic and have ❏ multiple dependencies ❏ Move business logic and dependencies to services API remote service layer Thin client libs UI/device scripts (node) Falcor Services
- 52. Remove metadata from API servers ❏ Metadata takes up significant memory in API servers ❏ Challenge: reduce chattiness to metadata Metadata Service API remote service layer Thin client libs UI/device scripts (node) Falcor Services