Metrics and Health Checks
Utilize metrics and health checks to monitor the real-time performance and availability of your microservices and patterns.
Metrics and Health Checks is a free Microservices Communication Patterns (Saga, Circuit Breaker) lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Microservices Communication Patterns (Saga, Circuit Breaker) learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Welcome to Monitoring
In distributed systems, knowing what's happening is vital. That's where metrics and health checks come in!
They help us understand how our services are performing and if they're even alive. This lesson will show you how to use them effectively.
Understanding Metrics
Metrics are numerical measurements collected over time. Think of them as vital signs for your applications.
- Counters: Count events (e.g., requests received).
- Gauges: Show a current value (e.g., current CPU usage).
- Histograms/Timers: Measure distributions and durations (e.g., request latency).
How Metrics are Collected
Metrics need to be gathered from your services. This often involves libraries or frameworks that expose data in a standard format.
Tools like Prometheus or Micrometer (for Java) help instrument your code to collect and expose these metrics for monitoring systems.
Measuring Request Count
Let's see a simple example of a counter. This Java code simulates incrementing a request counter each time a "request" is processed. In a real app, this would be part of a web framework.
public class Main {
static int requestCounter = 0;
public static void processRequest() {
requestCounter++;
System.out.println("Requests processed: " + requestCounter);
}
public static void main(String[] args) {
processRequest();
processRequest();
processRequest();
}
}Measuring Request Latency
Measuring how long an operation takes is crucial. This example uses a basic timer to show the duration of a simulated task. Real-world solutions use more sophisticated timer metrics.
public class Main {
public static void simulateWork() throws InterruptedException {
long startTime = System.nanoTime();
Thread.sleep(100); // Simulate work
long endTime = System.nanoTime();
long durationMs = (endTime - startTime) / 1_000_000;
System.out.println("Work took: " + durationMs + " ms");
}
public static void main(String[] args) throws InterruptedException {
simulateWork();
simulateWork();
}
}Dashboards for Metrics
Raw metrics aren't very useful on their own. They need to be visualized!
Tools like Grafana allow you to create powerful dashboards. These dashboards transform raw metric data into graphs and charts, making it easy to spot trends, anomalies, and performance issues at a glance.
Understanding Health Checks
While metrics tell you about performance, health checks tell you if a service is operational.
They are simple endpoints (e.g., /health) that a monitoring system or orchestrator (like Kubernetes) can call to determine if your application is ready to serve traffic or if it needs to be restarted.
Implementing a Basic Health Check
A basic health check might just return an "OK" status if the application process is running. In a real microservice, this would be an HTTP endpoint.
public class Main {
public static boolean isServiceHealthy() {
// In a real app, this might check database connection,
// external service reachability, etc.
return true; // For now, always healthy
}
public static void main(String[] args) {
if (isServiceHealthy()) {
System.out.println("Service is HEALTHY");
} else {
System.out.println("Service is UNHEALTHY");
}
}
}Liveness vs. Readiness Checks
There are two main types of health checks:
- Liveness Check: Determines if your application is still running and able to make progress. If it fails, the application might be restarted.
- Readiness Check: Determines if your application is ready to accept traffic. If it fails, traffic won't be routed to it (e.g., during startup or while recovering).
Quick Check on Monitoring
You've learned about metrics and health checks. Let's test your understanding!
Recap: Metrics & Health Checks
Congratulations! You've learned how metrics provide deep insights into your service's performance, using counters, gauges, and timers.
You also discovered how health checks (liveness and readiness) are crucial for ensuring your services are operational and available. Together, they form the foundation of robust observability!
Frequently asked questions
Is the “Metrics and Health Checks” lesson free?
Yes — the full text of “Metrics and Health Checks” is free to read here on the web, and the Microservices Communication Patterns (Saga, Circuit Breaker) course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Microservices Communication Patterns (Saga, Circuit Breaker) course, upgrade to CoddyKit PRO.
What will I learn in “Metrics and Health Checks”?
Utilize metrics and health checks to monitor the real-time performance and availability of your microservices and patterns. You practise Microservices Communication Patterns (Saga, Circuit Breaker) with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Microservices Communication Patterns (Saga, Circuit Breaker)?
No prior experience is required. Microservices Communication Patterns (Saga, Circuit Breaker) on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Metrics and Health Checks” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Microservices Communication Patterns (Saga, Circuit Breaker) lesson?
Yes. Every Microservices Communication Patterns (Saga, Circuit Breaker) lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Distributed Tracing Concepts
- Centralized Logging Strategies
- Metrics and Health Checks
- Alerting and SLOs