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Adrian Cole - An Introduction to Distributed Tracing and Zipkin

Adrian Cole - An Introduction to Distributed Tracing and Zipkin

Latency analysis is the act of blaming components for causing user perceptible delay. In today's world of microservices, this can be tricky as requests can fan out across polyglot components and even data-centers. This session will overview how to debug latency and better understand your production environment with Zipkin. You'll see a demo and leave knowing how to get started with distributed tracing.

Adrian Cole (@adrianfcole)
Adrian is an active member of cloud interoperability circles. He is the founder of a few popular open source projects, notably Apache jclouds and Netflix feign. Recently, he’s focused on distributed tracing, particularly in the OpenZipkin project. Adrian works at Pivotal in the Spring Cloud OSS team.

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DevOpsDays Singapore

October 08, 2016
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  1. © 2016 Pivotal !1 An introduction to Distributed Tracing and

    Zipkin Adrian Cole, Pivotal @adrianfcole How to Properly Blame Things for Causing Latency
  2. Introduction introduction understanding latency distributed tracing zipkin demo wrapping up

    @adrianfcole #zipkin
  3. @adrianfcole • spring cloud at pivotal • focused on distributed

    tracing • helped open zipkin
  4. Understanding Latency introduction understanding latency distributed tracing zipkin demo wrapping

    up @adrianfcole #zipkin
  5. Understanding our architecture Microservice and data pipeline architectures are a

    often a graph of components, distributed across a network. A call graph or data flow can become delayed or fail due to the nature of the operation, components, or edges between them. We want to understand our current architecture and troubleshoot latency problems, in production.
  6. Why is POST /things slow? POST /things

  7. POST /things There’s often two sides to the story Client

    Sent:15:31:28:500 Client Received:15:31:31:000 Duration: 2500 milliseconds Server Received:15:31:29:103 POST /things Server Sent:15:31:30:530 Duration: 1427 milliseconds
  8. and not all operations are on the critical path Wire

    Send Store Async Store Wire Send POST /things POST /things
  9. and not all operations are relevant Wire Send Store Async

    Async Store Failed Wire Send POST /things POST /things KQueueArrayWrapper.kev UnboundedFuturePool-2 SelectorUtil.select LockSupport.parkNan ReferenceQueue.remove
  10. Service architecture isn’t this simple anymore Single-server scenarios aren’t realistic

    or don’t fully explain latency. David Vignoni Gnome-fs-server.svg
  11. Can we make troubleshooting wizard-free? We no longer need wizards

    to deploy complex architectures. We shouldn’t need wizards to troubleshoot them, either!
  12. Distributed Tracing introduction understanding latency distributed tracing zipkin demo wrapping

    up @adrianfcole #zipkin
  13. Distributed Tracing commoditizes knowledge Distributed tracing systems collect end-to-end latency

    graphs (traces) in near real-time. You can compare traces to understand why certain requests take longer than others.
  14. Distributed Tracing Vocabulary A Span is an individual operation that

    took place. A span contains timestamped events and tags. A Trace is an end-to-end latency graph, composed of spans.
  15. wombats:10.2.3.47:8080 A Span is an individual operation Server Received POST

    /things Server Sent Events Tags Operation peer.ipv4 1.2.3.4 http.request-id abcd-ffe http.request.size 15 MiB http.url …&features=HD-uploads
  16. Tracing Systems are Observability Tools Tracing systems collect, process and

    present data reported by tracers. - aggregate spans into trace trees - provide query and visualization focused on latency - have retention policy (usually days)
  17. ProTip: Tracing is not just for latency Some wins unrelated

    to latency - Understand your architecture - Find services that aren’t used - Reduce time spent on triage
  18. Zipkin introduction understanding latency distributed tracing zipkin demo wrapping up

    @adrianfcole #zipkin
  19. Zipkin is a distributed tracing system

  20. Zipkin lives in GitHub Zipkin was created by Twitter in

    2012. In 2015, OpenZipkin became the primary fork. OpenZipkin is an org on GitHub. It contains tracers, OpenApi spec, service components and docker images. https://github.com/openzipkin
  21. Zipkin Architecture Platform frameworks for Zipkin: Bosh (Cloud Foundry) Docker

    (in Zipkin’s org) Kubernetes Mesos Tracers report spans HTTP or Kafka. Servers collect spans, storing them in MySQL, Cassandra, or Elasticsearch. Users query for traces via Zipkin’s Web UI or Api.
  22. Zipkin has starter architecture Tracing is new for a lot

    of folks. For many, the MySQL option is a good start, as it is familiar. services: storage: image: openzipkin/zipkin-mysql container_name: mysql ports: - 3306:3306 server: image: openzipkin/zipkin environment: - STORAGE_TYPE=mysql - MYSQL_HOST=mysql ports: - 9411:9411 depends_on: - storage
  23. Zipkin can be as simple as a single file $

    curl -SL 'https://search.maven.org/remote_content?g=io.zipkin.java&a=zipkin-server&v=LATEST&c=exec' > zipkin.jar $ SELF_TRACING_ENABLED=true java -jar zipkin.jar . ____ _ __ _ _ /\\ / ___'_ __ _ _(_)_ __ __ _ \ \ \ \ ( ( )\___ | '_ | '_| | '_ \/ _` | \ \ \ \ \\/ ___)| |_)| | | | | || (_| | ) ) ) ) ' |____| .__|_| |_|_| |_\__, | / / / / =========|_|==============|___/=/_/_/_/ :: Spring Boot :: (v1.4.0.RELEASE) 2016-08-01 18:50:07.098 INFO 8526 --- [ main] zipkin.server.ZipkinServer : Starting ZipkinServer on acole with PID 8526 (/Users/acole/oss/sleuth-webmvc-example/zipkin.jar started by acole in /Users/acole/oss/sleuth-webmvc-example) —snip— $ curl -s localhost:9411/api/v1/services|jq . [ "zipkin-server" ]
  24. Demo introduction understanding latency distributed tracing zipkin demo wrapping up

    @adrianfcole #zipkin
  25. Two Spring Boot (Java) services collaborate over http. Zipkin will

    show how long the whole operation took, as well how much time was spent in each service. https://github.com/openzipkin/sleuth-webmvc-example Distributed Tracing across Spring Boot apps
  26. Web requests in the demo are served by Spring MVC

    controllers. Tracing of these are automatically performed by Spring Cloud Sleuth. Spring Cloud Sleuth reports to Zipkin via HTTP by depending on spring-cloud-sleuth-zipkin. https://cloud.spring.io/spring-cloud-sleuth/ Spring Cloud Sleuth Java
  27. Wrapping Up introduction understanding latency distributed tracing zipkin demo wrapping

    up @adrianfcole #zipkin
  28. Wrapping up Start by sending traces directly to a zipkin

    server. Grow into fanciness as you need it: sampling, streaming, etc Remember you are not alone! @adrianfcole #zipkin gitter.im/spring-cloud/spring-cloud-sleuth gitter.im/openzipkin/zipkin