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Simple Solutions for Complex Problems

Simple Solutions for Complex Problems

Bay Area NATS Meetup 3/22/2016

Tyler Treat

March 22, 2016
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  1. • Messaging tech lead at Workiva • Platform infrastructure •

    Distributed systems • bravenewgeek.com @tyler_treat
 [email protected] ABOUT THE SPEAKER
  2. • Embracing the reality of complex systems • Using simplicity

    to your advantage • Why NATS? • How Workiva uses NATS ABOUT THIS TALK
  3. “There will be no further print editions [of the Merck

    Manual]. Publishing a printed book every five years and sending reams of paper around the world on trucks, planes, and boats is no longer the optimal way to provide medical information.” Dr. Robert S. Porter
 Editor-in-Chief, The Merck Manuals
  4. Distributed computation is
 inherently asynchronous
 and the network is
 inherently

    unreliable[2]… [2] http://queue.acm.org/detail.cfm?id=2655736
  5. …but the natural tendency is to build distributed systems as

    if they aren’t distributed at all because it’s
 easy to reason about. strong consistency - reliable messaging - predictability
  6. • Message handed to the transport layer? • Enqueued in

    the recipient’s mailbox? • Recipient started processing it? • Recipient finished processing it? What’s a delivery guarantee?
  7. Guaranteed, ordered, exactly-once delivery is expensive (if not impossible[3]). [3]

    http://bravenewgeek.com/you-cannot-have-exactly-once-delivery/
  8. We can always build
 stronger guarantees on top,
 but we

    can’t always remove
 them from below.
  9. End-to-end system semantics matter much more than the semantics of

    an
 individual building block[4]. [4] http://web.mit.edu/Saltzer/www/publications/endtoend/endtoend.pdf
  10. “Simple can be harder than complex. You have to work

    hard to get your thinking clean to make it simple. But it’s worth it in the end because once you get there, you can move mountains.”
  11. • Wdesk: platform for enterprises to collect, manage, and report

    critical business data in real time • Increasing amounts of data and complexity of formats • Cloud solution:
 - Data accuracy
 - Secure
 - Highly available
 - Scalable
 - Mobile-enabled About Workiva
  12. • First solution built on Google App Engine • Scaling

    new solutions requires service-oriented approach • Scaling new services requires a low-latency communication backplane About Workiva
  13. • Always on, always available • Protects itself at all

    costs—no compromises on performance • Disconnects slow consumers and lazy listeners • Clients have automatic failover and reconnect logic • Clients buffer messages while temporarily partitioned Availability over Everything
  14. • Single, lightweight binary • Embraces the “negative space”:
 -

    Simplicity —> high-performance
 - No complicated configuration or external dependencies
 (e.g. ZooKeeper)
 - No fragile guarantees —> face complexity head-on, encourage async • Simple pub/sub semantics provide a versatile primitive:
 - Fan-in
 - Fan-out
 - Request/response
 - Distributed queueing • Simple text-based wire protocol Simplicity as a Feature
  15. • Fast, predictable performance at scale and at tail •

    ~8 million messages per second • Auto-pruning of interest graph allows efficient routing • When SLAs matter, it’s hard to beat NATS Fast as Hell
  16. “Just subscribe to this topic and decode using that encoding

    then deserialize in
 this way and extract these fields from
 this thing!”
  17. Pub/Sub is meant to decouple services but often ends up

    coupling the teams developing them.
  18. • Extension of Apache Thrift • IDL and cross-language, code-generated

    pub/sub APIs • Allows developers to think in terms of services and APIs rather than opaque messages and topics • Allows APIs to evolve while maintaining compatibility • Transports are pluggable (we use NATS) Frugal RPC
  19. struct Event {
 1: i64 id,
 2: string message,
 3:

    i64 timestamp,
 } scope Events prefix {user} {
 EventCreated: Event
 EventUpdated: Event
 EventDeleted: Event
 } subscriber.SubscribeEventCreated(
 "user-1", func(e *event.Event) {
 fmt.Println(e)
 },
 ) . . . publisher.PublishEventCreated(
 "user-1", event.NewEvent()) generated
  20. • Service instances form a queue group • Client “connects”

    to instance by publishing a message to the service queue group • Serving instance sets up an inbox for the client and sends it back in the response • Client sends requests to the inbox • Connecting is cheap—no service discovery and no sockets to create, just a request/response • Heartbeats used to check health of server and client • Very early prototype code: https://github.com/workiva/thrift-nats RPC over NATS
  21. • Store JSON containing cluster membership in S3 • Container

    reads JSON on startup and creates routes w/ correct credentials • Services only talk to the NATS daemon on their VM via localhost • Don’t have to worry about encryption between services and NATS, only between NATS peers NATS per VM
  22. • Only messages intended for a process on another host

    go over the network since NATS cluster maintains interest graph • Greatly reduces network hops (usually 0 vs. 2-3) • If local NATS daemon goes down, restart it automatically NATS per VM
  23. • Doesn’t scale to large number of VMs • Fairly

    easy to transition to floating NATS cluster or running on a subset of machines per AZ • NATS communication abstracted from service • Send messages to services without thinking about routing or service discovery • Queue groups provide service load balancing NATS per VM
  24. • We’re a SaaS company, not an infrastructure company •

    High availability • Operational simplicity • Performance • First-party clients:
 Go Java C C#
 Python Ruby Elixir Node.js NATS as a Messaging Backplane
  25. –Derek Landy, Skulduggery Pleasant “Every solution to every problem is

    simple…
 It's the distance between the two where the mystery lies.”