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production-observability

Use when adding service-wide Spring Boot 4 Actuator, Micrometer Observation and Tracing, OpenTelemetry or OTLP export, structured logging, health probes, dashboards, or alerts. Combine with ai-observability only for Spring AI-specific token, prompt, and model telemetry.

インストール方法を見る

含まれるファイル(5)

  • SKILL.md3.0 KB
  • agents/openai.yaml211 B
  • examples/bad-observation.java201 B
  • examples/good-observability.yml485 B
  • examples/good-observation.java496 B

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Production Observability

Instrument user-visible operations and operational boundaries, not every method.

Baseline

  • Add the Boot 4 Actuator starter and one metrics registry selected by the platform.
  • For OpenTelemetry tracing over OTLP, use spring-boot-starter-opentelemetry and Boot's management.opentelemetry.tracing.export.otlp.* properties.
  • Use Micrometer Observation for application metrics and traces.
  • Prefer Micrometer APIs over direct OpenTelemetry APIs in application code.
  • Export metrics and traces through OTLP when an OpenTelemetry collector is the platform boundary.
  • Expose only required actuator endpoints and secure non-public endpoints.

Observation conventions

  • Name observations by stable operation, such as orders.create.
  • Use low-cardinality key values for metrics and high-cardinality values only for traces.
  • Never tag metrics with user IDs, entity IDs, URLs containing IDs, or exception messages.
  • Register a ContextPropagatingTaskDecorator for async executor boundaries.
  • Enable Reactor automatic context propagation only deliberately and test it.
  • Avoid annotating already instrumented MVC controllers or repositories with @Observed.

Health and readiness

  • Keep liveness independent from remote dependencies.
  • Put traffic-critical dependencies in readiness groups.
  • Give custom health checks strict timeouts and stable detail keys.
  • Keep sensitive health details hidden from unauthenticated callers.

Logging and alerts

  • Emit structured logs correlated with trace and span IDs.
  • Redact credentials, tokens, personal data, prompts, and request bodies by default.
  • Alert on service-objective symptoms: error ratio, latency, saturation, or queue lag.
  • Include a runbook and service/dependency identity in every actionable alert.

Examples

  • See examples/good-observation.java, examples/good-observability.yml, and examples/bad-observation.java.

Official sources

Gotchas

  • Agent uses high-cardinality IDs as metric tags - reserve them for traces or logs.
  • Agent directly configures an OpenTelemetry SDK and disables Boot integration accidentally - prefer Boot and Micrometer support.
  • Agent exposes all actuator endpoints - expose the minimum and secure them.
  • Agent ties liveness to a database or broker - dependency outages can trigger restart loops.
  • Agent loses trace context in @Async work - register context propagation explicitly.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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Use when adding Spring AI-specific model observations, token usage, latency, externally configured cost attribution, advisor telemetry, or protected prompt and completion logging. Use production-observability for general service metrics, health, logs, and OTLP setup.

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