---
name: Production Observability
slug: production-observability
category: DevOps
description: Production Observability adds Spring Boot Actuator, Micrometer metrics, tracing, structured logging, health probes, dashboards, and alerts. Use it when instrumenting service-wide operations and external dependencies in production.
github: "https://github.com/rrezartprebreza/spring-boot-skills/tree/main/skills/spring-boot-3/production-observability"
language: Java
stars: 247
forks: 39
install: "npx degit https://github.com/rrezartprebreza/spring-boot-skills/tree/main/skills/spring-boot-3/production-observability ~/.claude/skills/production-observability"
installs_to: ~/.claude/skills/production-observability
source_path: skills/spring-boot-3/production-observability/SKILL.md
collection_size: 24
category_size: 828
collection_url: "https://dirskills.com/collections/rrezartprebreza/spring-boot-skills"
added: 2026-09-02T05:21:24.056Z
last_synced: 2026-09-02T05:21:24.056Z
canonical_url: "https://dirskills.com/skills/production-observability"
---

# Production Observability

Production Observability adds Spring Boot Actuator, Micrometer metrics, tracing, structured logging, health probes, dashboards, and alerts. Use it when instrumenting service-wide operations and external dependencies in production.

**Install:**

```bash
npx degit https://github.com/rrezartprebreza/spring-boot-skills/tree/main/skills/spring-boot-3/production-observability ~/.claude/skills/production-observability
```

## README

# 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.