Micrometer Mastery: Unleash Advanced Observability in your JVM Apps

Transcript

1. 2024-08-28 Jonatan Ivanov Micrometer Mastery Unleash Advanced Observability in your JVM Apps
2. About Me - Spring Team - Micrometer - Spring Cloud, Spring Boot - Spring Observability Team - Seattle Java User Group - develotters.com - @jonatan_ivanov
3. Agenda • Brief recap of observability • Micrometer Observation API • Micrometer Docs Generator • Demos
4. Observability basics recap
5. What is Observability? How well we can understand the internals of a system based on its outputs (Providing meaningful information about what happens inside) (Data about your app)
6. Why do we need Observability? Today's systems are increasingly complex (cloud) (Death Star Architecture, Big Ball of Mud)
7. Environments can be chaotic You turn a knob here a little and apps are going down there We need to deal with unknown unknowns We can’t know everything Things can be perceived differently by observers Everything is broken for the users but seems ok to you Why do we need Observability?
8. Why do we need Observability? (business perspective) Reduce lost revenue from production incidents Lower mean time to recovery (MTTR) Require less specialized knowledge Shared method of investigating across system Quantify user experience Don't guess, measure!
9. Logging Metrics Distributed Tracing
10. Examples Latency Logging (What?) Processing took 140ms Metrics (Context?) P99.999: 140ms Max: 150ms Distributed Tracing (Why?) DB was slow (lot of data was requested) Error Logging (What?) Processing failed (stacktrace?) Metrics (Context?) The error rate is 0.001/sec 2 errors in the last 30 minutes Distributed Tracing (Why?) DB call failed (invalid input)
11. SLF4J with Logback comes pre-configured SLF4J (Simple Logging Façade for Java) Simple API for logging libraries Logback Natively implements the SLF4J API If you want Log4j2 instead of Logback: - spring-boot-starter-logging + spring-boot-starter-log4j2 Logging with JVM/Spring: SLF4J + Logback
12. Metrics with JVM/Spring: Micrometer Dimensional Metrics library on the JVM Like SLF4J, but for metrics API is independent of the configured metrics backend Supports many backends Comes with spring-boot-actuator Spring projects are instrumented using Micrometer Many third-party libraries use Micrometer
13. Supported metrics backends/formats/protocols Ganglia Graphite Humio InfluxDB JMX KairosDB New Relic (/actuator/metrics) OpenTSDB OTLP Prometheus SignalFx Stackdriver (GCP) StatsD Wavefront (VMware) AppOptics Atlas Azure Monitor CloudWatch (AWS) Datadog Dynatrace Elastic
14. Distributed Tracing with JVM/Spring Boot 2.x: Spring Cloud Sleuth Boot 3.x: Micrometer Tracing (Sleuth w/o Spring dependencies) Provide an abstraction layer on top of tracing libraries - Brave (OpenZipkin), “default” - OpenTelemetry (CNCF), “experimental” Instrumentation for Spring Projects, 3rd party libraries, your app Support for various backends
15. DEMO 🍵 github.com/jonatan-ivanov/teahouse
16. Tea Service 💻 Tealeaf Service Water Service Architecture Tealeaf DB Water DB
17. through traces TraceID ❮ Exemplars Tags ❯ metrics logs traces
18. Observation API
19. • Add Logs (application logs) • Add Metrics • Add Distributed Tracing You want to instrument your application…
20. Introducing Observation API • “New” module in Micrometer 1.10 (micrometer-observation) micrometer-core has a dependency on it • Higher level abstraction than metrics or tracing for timing an operation • Instrument once, configure handlers for multiple purposes (e.g.: metrics, tracing, logging) • Already used for most instrumentation shown
21. Observation API basic usage example Observation observation = Observation.start("talk",registry); try { // TODO: scope doSomething(); // ← This is what we’re observing } catch (Exception exception) { observation.error(exception); throw exception; } finally { // TODO: attach tags (key-value) observation.stop(); }
22. Configuring an ObservationHandler (without Boot) ObservationRegistry registry = ObservationRegistry.create(); registry.observationConfig() .observationHandler(new MetricsHandler(...)) .observationHandler(new TracingHandler(...)) .observationHandler(new LoggingHandler(...)) .observationHandler(new AuditEventHandler(...));
23. ObservationHandler with Spring Boot Spring Boot auto-configures handlers for meters and tracing. Boot will also register ObservationHandler beans to the ObservationRegistry that it auto-configures. @Bean ObservationHandler<MyContext> myHandler() { return new MyObservationHandler(); }
24. Observation API shortcuts Observation.createNotStarted("talk",registry) .lowCardinalityKeyValue("event", "S1") .highCardinalityKeyValue("uid", userId) .observe(this::talk); @Observed
25. Observation.Context • Holds the state/data of an Observation ◦ e.g. request/response object • ObservationHandler / ObservationConvention will receive it • Mutable, you can add data to it ◦ Instrumentation time ◦ Pass data between handler methods
26. Let’s look at some code
27. Observation Predicate and Filter ObservationPredicate • BiPredicate: (name, context) → Boolean • Whether an Observation is ignored (noop) ObservationFilter • Modify the Observation.Context • Right before ObservationHandler#onStop • e.g. common tags (KeyValues)
28. Conventions for instrumentation • Instrumentation by default provides a convention ◦ Naming, tags (KeyValues) • You may want to customize the convention for an instrumentation without rewriting the instrumentation • Control the timing of changing conventions ◦ Convention changes are breaking changes
29. Introducing ObservationConvention • Instrumentation can use a default ObservationConvention while allowing users to provide a custom implementation • Extend a default implementation or implement your own • See, for example, Spring Framework’s docs
30. Let’s look at some code (again)
31. Micrometer Docs Generator
32. Documenting instrumentation • Keeping documentation in sync with the implementation is difficult and error-prone. • Introducing Micrometer Docs Generator • Define an ObservationDocumentation enum for your Observation-based instrumentation and generate documentation based on it as part of the build • Integrate it with ObservationConvention
33. Let’s look at some code (again) (again)
34. Observation API real-world usage examples ServerHttpObservationFilter (Spring MVC) DefaultServerRequestObservationConvention ServerHttpObservationDocumentation RestTemplate
35. What’s ~new? • Improved Exemplars support • MeterProvider • Prometheus Java Client 1.x • New Docs site (micrometer.io) • Observability improvements in the Spring portfolio ◦ Context Propagation + Log Correlation ◦ Auto-Instrumentations, Performance • SBOM Actuator Endpoint
36. What’s ~next? • Exponential Histograms (OTLP) • TestObservationRegistry validation • ProcessInfoContributor • SslInfoContributor • SslHealthIndicator • Spring AI instrumentation
37. Thank you! @jonatan_ivanov develotters.com github.com/jonatan-ivanov/teahouse slack.micrometer.io