📊 Observability in Distributed Systems

Welcome back to The Code Hut Distributed Systems series! In this post, we’ll explore how to gain insight into distributed systems using logging, metrics, and distributed tracing.

Why Observability Matters

Distributed systems are complex. Observability allows you to understand system behavior, troubleshoot issues, and improve reliability.

1. Logging

Centralized logging helps track events across multiple services:

• Use structured logs (JSON) for easy querying
• Centralize logs using tools like ELK Stack (Elasticsearch, Logstash, Kibana) or Graylog

// Example with SLF4J
private static final Logger logger = LoggerFactory.getLogger(OrderService.class);

logger.info("Order created with id {}", orderId);
logger.error("Failed to process order {}", orderId, exception);

2. Metrics

Metrics provide numerical insight into system performance:

• Track response times, throughput, error rates
• Use libraries like Micrometer with Prometheus/Grafana

// Micrometer example
Counter orderCounter = Counter.builder("orders.created")
    .description("Number of orders created")
    .register(meterRegistry);

orderCounter.increment();

3. Distributed Tracing

Tracing helps follow a request across multiple services:

• Identify latency bottlenecks
• Popular tools: Jaeger, Zipkin, OpenTelemetry

// OpenTelemetry example
Span span = tracer.spanBuilder("processOrder").startSpan();
try (Scope scope = span.makeCurrent()) {
    orderService.process(order);
} finally {
    span.end();
}

Next in the Series

In the next post, we’ll explore Security in Distributed Systems, including authentication, authorization, and data protection.

Label for this post: Distributed Systems