Logging

Introduction

Logs are how a running Java service tells you what it's doing. The de-facto stack is SLF4J (the API) + Logback or Log4j2 (the implementation).

Informative example

Idiomatic logging:

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class OrderService {
    private static final Logger log = LoggerFactory.getLogger(OrderService.class);

    public void place(String customer, int cents) {
        log.info("Placing order customer={} cents={}", customer, cents);
        try {
            // ...
        } catch (Exception e) {
            log.error("Order failed customer={} cents={}", customer, cents, e); // include throwable LAST
        }
    }
}

Best practices

• Use parameterised messages ({}) — avoids string concat when level is disabled.
• Log at the right level: ERROR is for actionable failures, INFO for business events, DEBUG for diagnostics.
• Add a correlation ID (MDC) so you can trace a request across services.

Common mistakes

• Logging passwords, tokens or PII — GDPR fines start at 4% of revenue.
• System.out.println in production code — bypasses log config.

Purpose of this lesson

Master Logging so you can apply it confidently in production Java code, technical interviews, and code reviews.

Step-by-step explanation

1. Understand the core idea behind Logging.
2. Walk through the runnable example and tweak it in the playground.
3. Apply the pattern in a small Spring Boot or CLI exercise of your own.
4. Re-read the common mistakes and interview Q&A to lock the concept in.

Interactive workflow diagram

Useful template

private static final Logger log = LoggerFactory.getLogger(MyService.class);
log.info("User {} placed order {}", userId, orderId);

Debugging tips

• Read the full stack trace — Java's exception messages name the offending class and line.
• Reproduce in the smallest possible main() method before fixing in the real app.
• Use IntelliJ's debugger breakpoints and 'Evaluate Expression' rather than scattering System.out.

Optimization strategies

• Profile before optimizing — JFR (Java Flight Recorder) and async-profiler reveal real hotspots.
• Prefer immutable data and stream pipelines over hand-rolled loops when readability matters.
• Reach for the right JDK collection (ArrayList vs LinkedList vs ArrayDeque) before writing custom data structures.

Enterprise example

Teams at Netflix, Uber and Goldman Sachs apply Logging daily — usually wrapped behind Spring Boot services with observability hooks (Micrometer + OpenTelemetry).

Interview questions & answers

Summary

In this lesson you learned Logging — the concept, syntax, a runnable example, and the production pitfalls to avoid. Apply it in the playground before moving on.