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Spring Boot Actuator

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giuseppe-trisciuoglio
spring-boot-actuator

Provides patterns to configure Spring Boot Actuator for production-grade monitoring, health probes, secured management endpoints, and Micrometer metrics across JVM services. Use when setting up monitoring, health checks, or metrics for Spring Boot applications.

Overview

Publishergiuseppe-trisciuoglio
Repositorydeveloper-kit
Skill namespring-boot-actuator
Stars
345
Forks
41
Bundled files
14
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 14 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by giuseppe-trisciuoglio on GitHub. Read the source before you install it.

Installation

Install the Spring Boot Actuator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git /tmp/developer-kit
mkdir -p .claude/skills
cp -r /tmp/developer-kit/plugins/developer-kit-java/skills/spring-boot-actuator .claude/skills/spring-boot-actuator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spring Boot Actuator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Spring Boot Actuator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Spring Boot Actuator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Spring Boot Actuator Skill

Overview

  • Deliver production-ready observability for Spring Boot services using Actuator endpoints, probes, and Micrometer integration.
  • Standardize health, metrics, and diagnostics configuration while delegating deep reference material to references/.
  • Support platform requirements for secure operations, SLO reporting, and incident diagnostics.

When to Use

  • Trigger: "enable actuator endpoints" – Bootstrap Actuator for a new or existing Spring Boot service.
  • Trigger: "secure management port" – Apply Spring Security policies to protect management traffic.
  • Trigger: "configure health probes" – Define readiness and liveness groups for orchestrators.
  • Trigger: "export metrics to prometheus" – Wire Micrometer registries and tune metric exposure.
  • Trigger: "debug actuator startup" – Inspect condition evaluations and startup metrics when endpoints are missing or slow.

Quick Start

xml
<!-- Maven -->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
gradle
// Gradle
dependencies {
    implementation "org.springframework.boot:spring-boot-starter-actuator"
}

After adding the dependency, verify endpoints respond:

bash
curl http://localhost:8080/actuator/health
curl http://localhost:8080/actuator/info

Instructions

1. Add Actuator Dependency

Include spring-boot-starter-actuator in your build configuration.

Validate: Restart the service and confirm /actuator/health and /actuator/info respond with 200 OK.

2. Expose Required Endpoints

  • Set management.endpoints.web.exposure.include to the precise list or "*" for internal deployments.
  • Adjust management.endpoints.web.base-path (e.g., /management) when the default /actuator conflicts with routing.
  • Review detailed endpoint semantics in references/endpoint-reference.md.

Validate: curl http://localhost:8080/actuator returns the list of exposed endpoints.

3. Secure Management Traffic

  • Apply an isolated SecurityFilterChain using EndpointRequest.toAnyEndpoint() with role-based rules.
  • Combine management.server.port with firewall controls or service mesh policies for operator-only access.
  • Keep /actuator/health/** publicly accessible only when required; otherwise enforce authentication.

Validate: Unauthenticated requests to protected endpoints return 401 Unauthorized.

4. Configure Health Probes

  • Enable management.endpoint.health.probes.enabled=true for /health/liveness and /health/readiness.
  • Group indicators via management.endpoint.health.group.* to match platform expectations.
  • Implement custom indicators by extending HealthIndicator or ReactiveHealthContributor; sample implementations in references/examples.md#custom-health-indicator.

Validate: /actuator/health/readiness returns UP with all mandatory components before promoting to production.

5. Publish Metrics and Traces

  • Activate Micrometer exporters (Prometheus, OTLP, Wavefront, StatsD) via management.metrics.export.*.
  • Apply MeterRegistryCustomizer beans to add application, environment, and business tags for observability correlation.
  • Surface HTTP request metrics with server.observation.* configuration when using Spring Boot 3.2+.

Validate: Scrape /actuator/prometheus and confirm required meters (http.server.requests, jvm.memory.used) are present.

6. Enable Diagnostics Tooling

  • Turn on /actuator/startup (Spring Boot 3.5+) and /actuator/conditions during incident response to inspect auto-configuration decisions.
  • Register an HttpExchangeRepository (e.g., InMemoryHttpExchangeRepository) before enabling /actuator/httpexchanges for request auditing.
  • Consult references/endpoint-reference.md for endpoint behaviors and limits.

Validate: /actuator/startup and /actuator/conditions return valid JSON payloads.

Examples

Basic – Expose health and info safely

yaml
management:
  endpoints:
    web:
      exposure:
        include: "health,info"
  endpoint:
    health:
      show-details: never

Intermediate – Readiness group with custom indicator

java
@Component
public class PaymentsGatewayHealth implements HealthIndicator {

    private final PaymentsClient client;

    public PaymentsGatewayHealth(PaymentsClient client) {
        this.client = client;
    }

    @Override
    public Health health() {
        boolean reachable = client.ping();
        return reachable ? Health.up().withDetail("latencyMs", client.latency()).build()
                         : Health.down().withDetail("error", "Gateway timeout").build();
    }
}
yaml
management:
  endpoint:
    health:
      probes:
        enabled: true
      group:
        readiness:
          include: "readinessState,db,paymentsGateway"
          show-details: always

Advanced – Dedicated management port with Prometheus export

yaml
management:
  server:
    port: 9091
    ssl:
      enabled: true
  endpoints:
    web:
      exposure:
        include: "health,info,metrics,prometheus"
      base-path: "/management"
  metrics:
    export:
      prometheus:
        descriptions: true
        step: 30s
  endpoint:
    health:
      show-details: when-authorized
      roles: "ENDPOINT_ADMIN"
java
@Configuration
public class ActuatorSecurityConfig {

    @Bean
    SecurityFilterChain actuatorChain(HttpSecurity http) throws Exception {
        http.securityMatcher(EndpointRequest.toAnyEndpoint())
            .authorizeHttpRequests(c -> c
                .requestMatchers(EndpointRequest.to("health")).permitAll()
                .anyRequest().hasRole("ENDPOINT_ADMIN"))
            .httpBasic(Customizer.withDefaults());
        return http.build();
    }
}

More end-to-end samples are available in references/examples.md.

Best Practices

  • Keep SKILL.md concise and rely on references/ for verbose documentation to conserve context.
  • Apply the principle of least privilege: expose only required endpoints and restrict sensitive ones.
  • Use immutable configuration via profile-specific YAML to align environments.
  • Monitor actuator traffic separately to detect scraping abuse or brute-force attempts.
  • Automate regression checks by scripting curl probes in CI/CD pipelines.

Constraints and Warnings

  • Avoid exposing /actuator/env, /actuator/configprops, /actuator/logfile, and /actuator/heapdump on public networks.
  • Do not ship custom health indicators that block event loop threads or exceed 250 ms unless absolutely necessary.
  • Ensure Actuator metrics exporters run on supported Micrometer registries; unsupported exporters require custom registry beans.
  • Maintain compatibility with Spring Boot 3.5.x conventions; older versions may lack probes and observation features.
  • Never expose actuator endpoints without authentication in production environments.
  • Health indicators should not perform expensive operations that could impact application performance.
  • Be cautious with /actuator/beans and /actuator/mappings as they reveal internal application structure.

Reference Materials

Validation Checklist

  • Confirm mvn spring-boot:run or ./gradlew bootRun exposes expected endpoints under /actuator (or custom base path).
  • Verify /actuator/health/readiness returns UP with all mandatory components before promoting to production.
  • Scrape /actuator/metrics or /actuator/prometheus to ensure required meters (http.server.requests, jvm.memory.used) are present.
  • Run security scans to validate only intended ports and endpoints are reachable from outside the trusted network.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Spring Boot Actuator AI skill do?

Provides patterns to configure Spring Boot Actuator for production-grade monitoring, health probes, secured management endpoints, and Micrometer metrics across JVM services. Use when setting up monitoring, health checks, or metrics for Spring Boot applications.

Why use Spring Boot Actuator on TypingMind?

Because you install it once and use it with any model. Spring Boot Actuator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Spring Boot Actuator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/spring-boot-actuator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Spring Boot Actuator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Spring Boot Actuator?

As many as you like. As long as a model supports skills, you can use Spring Boot Actuator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Spring Boot Actuator AI skill free?

Yes. It is published on GitHub by giuseppe-trisciuoglio under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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