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DockerSF Meetup: Building a Serverless Platform on Docker

DockerSF Meetup: Building a Serverless Platform on Docker

Chad Arimura

February 02, 2018
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  1. Building a Serverless Platform on Docker Chad Arimura VP Serverless,

    Oracle @chadarimura Docker SF Meetup: 2/1/18
  2. About Me • Engineer and builder • 3x entrepreneur ◦

    1999-2006: Founding CTO of AllDorm ◦ 2008-2011: Founding Partner of Appoxy ◦ 2011-2017: Founding CEO of Iron.io • Now VP Serverless, Oracle me
  3. What is Serverless? • Serverless is an abstraction of infrastructure

    and its operations including provisioning, scaling, patching, etc. • Serverless architecture is when an app is built entirely on serverless components (compute, storage, networking) • FaaS is the compute component in a serverless architecture
  4. Why Serverless? • Easier: Just think about your code, not

    infrastructure • Powerful: Transparent and limitless scaling • Faster: Deploy faster, iterate faster, innovate faster • Cheaper: Only pay for what you use to the 100ms (never idle)
  5. Functions-as-a-Service • Functions are small bits of code that do

    one thing well and are easy to understand and maintain • As a service means no complicated plumbing, the system takes care of provisioning, scaling, patching, maintaining, etc. Each function scales independently. In mathematics, a function is a relation between a set of inputs and a set of permissible outputs with the property that each input is related to exactly one output. Function (mathematics) - Wikipedia https://en.wikipedia.org/wiki/Function_(mathematics)
  6. Containers vs Functions Function is a container with a set

    of known traits: • Short running • Ephemeral • Stateless • Invoked • Single Purpose • Self-contained
  7. Introducing the Fn Project • Open-source serverless compute platform •

    Can be deployed to any cloud and on-premise • Simple, elegant, and extensible by design • Containers are primitives • Hot containers provide fast response times (< 100ms) • Active w/ 2500+ commits across 50+ contributors • Independently governed with plans for foundation
  8. For Developers

  9. An Fn Function • Small chunk of code wrapped into

    a container image • Gets input via STDIN and environment • Produces output to STDOUT • Logs to STDERR The Fn server handles everything else, like the API gateway, piping things around, storing logs, etc.
  10. Fn CLI • fn init --runtime go • fn run

    • fn test • fn deploy --app myapp • fn call myapp myfunc → http://localhost:8080/r/myapp/myfunc
  11. fn deploy details 1. Builds container (multi-stage) + bumps version

    2. Pushes container to registry 3. Creates/updates function route (servers lazy load images) MyFunc:0.0.2 MyFunc:0.0.2 MyFunc:0.0.2 Your code Fn Service myfunc → /r/myapp/myfunc:0.0.2 1 2 3
  12. Function Development Kits (FDKs) • Used to help with parsing

    input and writing output • Familiar syntax for Lambda developers • Simply write a `handler` function that adheres to the FDK’s interface and it will parse STDIN and provide the input data to your function and deal with writing the proper output format. • Makes it a lot easier to write hot functions
  13. Debugging • fn calls list myapp • fn calls get

    myapp <call-id> • fn logs get myapp <call-id> • Metrics created using OpenTracing w/ initial collectors and extensions for Prometheus, ZipKin, and soon Jaeger
  14. Fn UI

  15. Demo #1

  16. For Operators

  17. Architecture

  18. Fn Server • Handles CRUD operations for setting up routes

    and functions • Executes sync functions, returning responses to clients immediately • Queues async function calls • Executes async functions when capacity is available • Written in Go, easy to extend via plugin module system
  19. Fn LB • Simple, fast load balancer that routes functions

    to certain nodes consistently for hot function efficiency • Scales each function independently based on traffic to any particular function • Can be used to scale Fn servers and infrastructure as well as it has a view of global state of all fn servers
  20. Fn LB Details

  21. Supporting Services • DB, MQ, blob store are all pluggable

    modules that are thin wrappers around their respective drivers. ◦ DB: MySQL, sqlite3, Postgres ◦ Queue: Redis, Kafka ◦ Registry: Any Docker v2-compliant, even private • Metrics/Monitoring ◦ OpenTracing API for metrics ◦ Prometheus support, pluggable backends ◦ Logging via syslog
  22. Open Tracing and Prometheus • OpenTracing spans with plugins to

    send to prom where Grafana can be used to view Fn data
  23. Request Flow

  24. Sync Request

  25. Async Request

  26. Scheduling

  27. Fn Scheduling t0

  28. Fn Scheduling t1

  29. Fn Scheduling t2

  30. Fn Scheduling t3

  31. Fn Scheduling t4

  32. Fn Scheduling t5

  33. Fn Scheduling t6

  34. Fn Scheduling t7

  35. Kubernetes

  36. Kubernetes • Fn is scheduler agnostic but lots of optimization/management

    work in process to optimize on Kubernetes • Helm chart available at https://github.com/fnproject/fn-helm • Thinking about deeper Kubernetes integrations including CRD’s to model functions
  37. Kubernetes Deployment

  38. Why not K8s Scheduling? 1. Speed a. Pod launch time

    is too slow for sync requests b. Coordinating all resource alloc to one k8s master is slow c. Yes we can preload + hot pod like we do with current scheduling but… 2. Scale a. Runs out of addressable network space quickly b. Functions easily scale to the hundreds of thousands / millions
  39. Docker

  40. Storage Stuff 1. Tried a lot of various storage drivers

    a. Overlay1 ran out of file descriptors / blocks b. Btrfs container creation / deletion under load was minutes c. Overlay2 was the only one that ended up tenable
  41. Why DinD? 1. Contained blast radius a. Doesn’t affect outer

    VM b. Kick the fn container and fire up a new one c. Systemd can manage Fn nicely 2. Control Docker version / config easier for our customers a. Inner can differ from outer
  42. Fn Flow

  43. Fn Flow • Build long-running, reliable, scalable functions with rich

    sets of language-specific primitives including fork-join, chaining, delays and error handling • Supports complex parallel processes that are readable and testable (including unit tests) with standard programming tools • Java support using CompletableFuture API from Java 8 with JS, Python, Go language support on the way!
  44. Plate Detect Function Draw Function Slack Function Twitter Function Scraper

  45. Scraper Plate Detect Function Draw Function Slack Function Twitter Function

    FlowFuture.invoke() thenCompose() thenCompose() allOf() whenComplete()
  46. Scraper Plate Detect Function Draw Function Slack Function Twitter Function

    FlowFuture.invoke() thenCompose() thenCompose() allOf() whenComplete() Flow Function
  47. None
  48. Demo #2

  49. Thank you! 1. Star the project: github.com/fnproject/fn 2. Join the

    conversation: slack.fnproject.io 3. Learn more: fnproject.io 4. We’re hiring engineers and evangelists: chad.arimura@oracle.com Name Title @twitter Get Involved
  50. Appendix