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production-observability

Use when adding service-wide Spring Boot 3 Actuator, Micrometer metrics, distributed tracing, OpenTelemetry 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(4)

  • SKILL.md2.4 KB
  • agents/openai.yaml211 B
  • examples/bad-observation.java201 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 Actuator and one metrics registry selected by the deployment platform.
  • Use Micrometer Observation for application metrics and traces.
  • Use Micrometer Tracing with the chosen bridge; do not mix tracing APIs throughout business code.
  • Export through OTLP when the platform standardizes on OpenTelemetry collectors.
  • Expose only required actuator endpoints and secure every non-public endpoint.

Observation conventions

  • Name observations by stable operation, such as orders.create.
  • Keep metric tags low-cardinality: method, outcome, region, or bounded status.
  • Put request IDs, user IDs, order IDs, and exception messages only in traces or logs.
  • Propagate context across @Async, executor, and Reactor boundaries.
  • Record latency, throughput, failures, and saturation for every external dependency.

Health and readiness

  • Keep liveness independent from remote systems so a dependency outage does not restart every pod.
  • Put required dependencies in readiness groups.
  • Write custom health indicators only for dependencies that affect traffic acceptance.
  • Set explicit timeouts on health checks.

Logging and alerts

  • Emit structured logs with trace and span correlation.
  • Redact credentials, tokens, personal data, prompts, and payloads by default.
  • Alert on symptoms tied to service objectives, not raw metric noise.
  • Include runbook links and enough dimensions to identify the affected service and dependency.

Examples

  • See examples/good-observation.java and examples/bad-observation.java.

Gotchas

  • Agent tags metrics with user or entity IDs - this creates unbounded cardinality.
  • Agent exposes every actuator endpoint publicly - expose the minimum and secure it.
  • Agent makes liveness depend on the database - dependency outages then cause restart loops.
  • Agent logs request bodies and tokens for debugging - redact sensitive data before emission.
  • Agent creates spans but loses context in async work - configure 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.

日本語の概要は準備中です。原文の説明を表示しています。

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日本語の概要は準備中です。原文の説明を表示しています。

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日本語の概要は準備中です。原文の説明を表示しています。

rrezartprebreza/spring-boot-skills3052026年9月21日 更新

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