Monitoring

Korvet provides comprehensive monitoring through Spring Boot Actuator and Micrometer.

Health Checks

Korvet exposes health check endpoints:

# Overall health
curl http://localhost:8080/actuator/health

# Liveness probe (for Kubernetes)
curl http://localhost:8080/actuator/health/liveness

# Readiness probe (for Kubernetes)
curl http://localhost:8080/actuator/health/readiness

Metrics

Metrics are exposed in Prometheus format:

curl http://localhost:8080/actuator/prometheus

Available Metrics

Korvet Custom Metrics

  • korvet.produce.messages: Number of messages produced (tags: topic, partition)

  • korvet.produce.latency: Produce request latency histogram (tags: topic, partition)

  • korvet.fetch.requests: Number of fetch requests (tags: topic, partition)

  • korvet.fetch.latency: Fetch request latency histogram (tags: topic, partition)

  • korvet.fetch.messages: Number of messages fetched (tags: topic, partition, tier)

  • korvet.errors: Number of errors (tags: operation, error_type)

JVM and System Metrics

Standard JVM and system metrics from Micrometer:

  • jvm.memory.used: JVM memory used

  • jvm.memory.max: JVM maximum memory

  • jvm.gc.pause: Garbage collection pause time

  • jvm.threads.live: Live threads

  • process.cpu.usage: Process CPU usage

  • system.cpu.usage: System CPU usage

  • system.load.average.1m: System load average

Prometheus Configuration

Add Korvet to your Prometheus scrape config:

scrape_configs:
  - job_name: 'korvet'
    static_configs:
      - targets: ['korvet:8080']
    metrics_path: '/actuator/prometheus'

Monitoring Stack Setup

A complete monitoring stack with Prometheus and Grafana is available in the korvet-dist observability directory.

Quick Start with Docker Compose

The easiest way to set up monitoring is to include the observability stack in your docker-compose.yml:

include:
  - path/to/korvet-dist/observability/docker-compose.yml

services:
  redis:
    image: redis:latest
    ports:
      - "6379:6379"

  korvet:
    image: redisfield/korvet:latest
    ports:
      - "9092:9092"
      - "8080:8080"
    environment:
      - KORVET_REDIS_HOST=redis
      - KORVET_REDIS_METRICS_ENABLED=true
    depends_on:
      - redis

This automatically adds:

  • Prometheus on port 9090 - Metrics collection and storage

  • Grafana on port 3000 - Pre-configured dashboard for Korvet metrics

Accessing the Dashboard

  1. Start your services:

    docker compose up -d

  2. Open Grafana at http://localhost:3000

  3. The Korvet dashboard loads automatically (no login required)

Dashboard Features

The pre-built Grafana dashboard visualizes:

  • Message Rates: Real-time produce/fetch rates using irate() for instant metrics

  • Latency Percentiles: P50, P95, P99 for produce and fetch operations

  • Throughput: Ingress and egress bytes/sec

  • Redis Metrics: Command rates, latency percentiles (when korvet.redis.metrics.enabled=true)

  • JVM Metrics: Heap memory, GC pauses, thread count

  • System Metrics: CPU usage, load average, disk space

The dashboard defaults to a 5-minute time range with 5-second auto-refresh for real-time monitoring.

Standalone Setup

For production deployments, see the observability README for:

  • Prometheus configuration examples

  • Grafana datasource and dashboard provisioning

  • Customizing the dashboard

Alerting

Set up alerts for:

Korvet-Specific Alerts

  • High produce latency: p99 > 100ms

  • High fetch latency: p99 > 50ms

  • Error rate spike: Error rate > 1% of requests

  • No produce activity: No messages produced in 5 minutes (if expected)

System Alerts

  • Memory pressure: JVM heap > 80%

  • High GC activity: Frequent or long GC pauses

  • High CPU usage: Process CPU > 80%

Logging

See Logging for log-based monitoring.

Next Steps