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How to properly blame things for causing latency - Voxxed Berlin

Adrian Cole
January 29, 2016

How to properly blame things for causing latency - Voxxed Berlin

Presentation about distributed tracing and zipkin. This is the second time around, and I've notably added more around what tracers do, and moved tracer inventory to "after questions" so I wouldn't run out of time. This turned out work because there weren't many questions :)

A few folks engaged in deep discussions afterwards, and I recommended the distributed-tracing google group because I realized they would be great to actually help improve things.

Adrian Cole

January 29, 2016
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  1. Latency Analysis 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.
  2. Troubleshooting latency problems When was the event and how long

    did it take? Where did this happen? Which event was it? Is it abnormal?
  3. When was the event and how long did it take?

    First log statement was at 15:31:29.103 GMT… last… 15:31:30.530 Server Received:15:31:29:103 POST /things Server Sent:15:31:30:530 Duration: 1427 milliseconds
  4. wombats:10.2.3.47:8080 Server log says Client IP was 1.2.3.4 This is

    a shard in the wombats cluster, listening on 10.2.3.47:8080 Server Received:15:31:29:103 POST /things Server Sent:15:31:30:530 Duration: 1427 milliseconds Where did this happen? peer.ipv4 1.2.3.4
  5. wombats:10.2.3.47:8080 Which event was it? The http response header had

    “request-id: abcd- ffe”? Is that what you mean? Server Received:15:31:29:103 POST /things Server Sent:15:31:30:530 Duration: 1427 milliseconds peer.ipv4 1.2.3.4 http.request-id abcd-ffe
  6. wombats:10.2.3.47:8080 Is it abnormal? I’ll check other logs for this

    request id and see what I can find out. Server Received:15:31:29:103 POST /things Server Sent:15:31:30:530 Duration: 1427 milliseconds Well, average response time for POST /things in the last 2 days is 100ms peer.ipv4 1.2.3.4 http.request-id abcd-ffe
  7. wombats:10.2.3.47:8080 Achieving understanding I searched the logs for others in

    that group.. took about the same time. Server Received:15:31:29:103 POST /things Server Sent:15:31:30:530 Duration: 1427 milliseconds Ok, looks like this client is in the experimental group for HD uploads peer.ipv4 1.2.3.4 http.request-id abcd-ffe http.request.size 15 MiB http.url …&features=HD-uploads
  8. 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
  9. and not all operations are on the critical path Wire

    Send Store Async Store Wire Send POST /things POST /things
  10. 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
  11. It’s getting harder to draw our architecture Polyglot microservice and

    data flow architectures are increasingly easy to write and deploy.
  12. Can we make troubleshooting wizard-free? We no longer need wizards

    to deploy complex architectures. We shouldn’t need wizards to troubleshoot them, either!
  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. Tracers record time, duration and host Wire Send Store Async

    Store Wire Send POST /things POST /things
  17. Tracers send trace data out of process Tracers propagate IDs

    in-band, to tell the receiver there’s a trace in progress Completed spans are reported out-of-band, to reduce overhead and allow for batching
  18. Tracers usually live in your application Tracers execute in your

    production apps! They are written to not log too much, and to not cause applications to crash. - propagate structural data in-band, and the rest out-of-band - have instrumentation or sampling policy to manage volume - often include opinionated instrumentation of layers such as HTTP
  19. Tracing Systems are Observability Tools Tracing systems collect, process and

    present data reported by tracers. - aggregate spans into trace trees - provide query and visualization for latency analysis - have retention policy (usually days)
  20. Zipkin has pluggable architecture Tracers collect timing data and transport

    it over HTTP or Kafka. Collectors store spans in MySQL or Cassandra. Users query for traces via Zipkin’s Web UI or Api. mysql:
 image: openzipkin/zipkin-cassandra:1.30.2
 ports:
 - 9042:9042
 query:
 image: openzipkin/zipkin-query:1.30.2
 environment: - TRANSPORT_TYPE=http
 - STORAGE_TYPE=cassandra
 ports:
 - 9411:9411
 links:
 - cassandra:storage
 web:
 image: openzipkin/zipkin-web:1.30.2
 ports:
 - 8080:8080
 environment:
 - TRANSPORT_TYPE=http
 links:
 - query
  21. 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. mysql:
 image: openzipkin/zipkin-mysql:1.30.2
 ports:
 - 3306:3306
 query:
 image: openzipkin/zipkin-java:0.4.4
 environment: - TRANSPORT_TYPE=http
 - STORAGE_TYPE=mysql
 ports:
 - 9411:9411
 links:
 - mysql:storage
 web:
 image: openzipkin/zipkin-web:1.30.2
 ports:
 - 8080:8080
 environment:
 - TRANSPORT_TYPE=http
 links:
 - query
  22. Zipkin can be as simple as a single file $

    curl -SL https://jcenter.bintray.com/io/zipkin/java/zipkin-server/0.4.4/zipkin-server-0.4.4-exec.jar > zipkin-server.jar $ java -jar zipkin-server.jar . ____ _ __ _ _ /\\ / ___'_ __ _ _(_)_ __ __ _ \ \ \ \ ( ( )\___ | '_ | '_| | '_ \/ _` | \ \ \ \ \\/ ___)| |_)| | | | | || (_| | ) ) ) ) ' |____| .__|_| |_|_| |_\__, | / / / / =========|_|==============|___/=/_/_/_/ :: Spring Boot :: (v1.3.1.RELEASE) 2016-01-25 15:15:16.456 INFO 94716 --- [ main] zipkin.server.ZipkinServer : Starting ZipkinServer on acole with PID 94716 (/tmp/zipkin-server.jar started by acole in /tmp) —snip— $ curl -s localhost:9411/api/v1/services|jq . [ "zipkin-query" ]
  23. 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 https://gitter.im/openzipkin/zipkin
  24. OpenTracing is an effort to clean-up and de-risk distributed tracing

    instrumentation OpenTracing Interfaces decouple instrumentation from vendor-specific dependencies and terminology. This allows applications to switch products with less effort. http://opentracing.io/ OpenTracing Go, Python, Java, JavaScript
  25. A single configuration change to bind a Tracer implementation in

    main() or similar import "github.com/opentracing/opentracing-go" import "github.com/tracer_x/tracerimpl" func main() { // Bind tracerimpl to the opentracing system opentracing.InitGlobalTracer( tracerimpl.New(kTracerImplAccessToken)) ... normal main() stuff ... } How does it work? Clean, vendor-neutral instrumentation code that naturally tells the story of a distributed operation import "github.com/opentracing/opentracing-go" func AddContact(c *Contact) { sp := opentracing.StartTrace("AddContact") defer sp.Finish() sp.Info("Added contact: ", *c) subRoutine(sp, ...) ... } func subRoutine(parentSpan opentracing.Span, ...) { ... sp := opentracing.JoinTrace("subRoutine", parentSpan) defer sp.Finish() sp.Info("deferred work to subroutine") ... } Thanks, @el_bhs for the slide!
  26. You can POST Spigo flows to zipkin $ run.sh —snip—

    $ curl -s 192.168.99.100:9411/api/v1/spans -X POST --data @json_metrics/lamp_flow.json -H "Content-Type: application/json"
  27. Where to go from here Start by sending traces directly

    to a zipkin server. Grow into fanciness as you need it: sampling, kafka, spark etc Remember you are not alone! gitter.im/openzipkin/zipkin @adrianfcole #VoxxedBerlin
  28. Finagle includes a Trace api and common integrations Finagle automatically

    traces stacks like http, thrift, mysql, redis and memcached. Report to zipkin via Scribe by depending on finagle-zipkin. https://github.com/twitter/finagle Finagle Scala
  29. Brave includes tracing apis and common integrations You can automatically

    trace with integrations such as Jersey filters or Apache HTTP client interceptors. Brave also includes tracing apis for custom instrumentation. https://github.com/openzipkin/brave Brave Java
  30. HTrace is a tracing framework for use with distributed systems.

    Hadoop includes commands to enable automatic tracing via HTrace. ZipkinSpanReceiver can report via Kafka or Scribe. HTrace apis can also be used directly. https://github.com/apache/incubator-htrace HTrace C, Java
  31. ZipkinTracer includes middleware for Rack and Faraday If a incoming

    request to Rack results in an outgoing request via Faraday, they will be two spans in the same trace. https://github.com/openzipkin/zipkin-tracer ZipkinTracer Ruby
  32. ZipkinTracerModule includes a tracing client and IHttpModule integration By configuring

    ZipkinRequestContextModule, incoming requests will be automatically traced. You can also use ITracerClient for custom instrumentation. https://github.com/mdsol/Medidata.ZipkinTracerModule ZipkinTracerModule .Net
  33. Spring Cloud Sleuth includes instrumentation for Spring Boot, and a

    streaming collector. Report to zipkin via HTTP by depending on spring-cloud- sleuth-zipkin. Spring Cloud Stream is also available, providing a more flexible and scalable pipeline. https://github.com/spring-cloud/spring-cloud-sleuth Spring Cloud Sleuth Java
  34. pyramid_zipkin is a Pyramid tween to add Zipkin service spans.

    By including ‘pyramid_zipkin’, incoming requests will be automatically traced. You can also use create_headers_for_new_span for outgoing requests. https://github.com/Yelp/pyramid_zipkin pyramid_zipkin Python