Debugging, Logs, and Production Support: What Java Support Engineers Must Master

 In Java consulting and application support roles, writing new code is often a small part of the job. The real challenge begins when applications fail in production, under real user traffic, with limited information and high pressure.

This is where support roles truly differ from pure development roles.

This post focuses on the core skills every Java support engineer must have: logging, debugging, and handling common production issues.

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✅ 1. Logging: Your First Line of Defense

Logs are the most valuable source of truth in production environments—especially when debugging live systems.

How to Read Stack Traces

A Java stack trace shows:

• The exception type (e.g., NullPointerException)

• The error message

• The sequence of method calls that led to the failure

Best practice:

• Start from the top to identify the exception

• Focus on the first application-level class, not framework code

• Ignore deep Spring or JVM internals unless necessary

Understanding stack traces quickly can reduce resolution time dramatically.

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Configuring Log Levels

Log levels control how much information is written:

• ERROR – Critical failures (production issues)

• WARN – Potential problems

• INFO – Application flow

• DEBUG – Detailed troubleshooting

• TRACE – Very fine-grained details

In production:

• Use INFO or WARN by default

• Enable DEBUG temporarily when investigating issues

• Avoid excessive logging—it can impact performance

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What Is Log Rotation?

Log rotation prevents log files from growing indefinitely.

It:

• Archives old logs

• Creates new log files

• Frees disk space

Without log rotation, applications may crash due to disk exhaustion—a surprisingly common production issue.

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Popular Logging Tools

Most enterprises use centralized logging platforms:

• ELK Stack (Elasticsearch, Logstash, Kibana)

• Splunk

These tools help:

• Search logs across servers

• Filter by time, level, or service

• Identify patterns in failures

Even basic familiarity with these tools is often expected in support interviews.

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✅ 2. Debugging Java Applications

Debugging in production is different from debugging locally. You often don’t have full access—or the luxury of restarting services freely.

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Using Breakpoints

In non-production environments:

• Breakpoints help inspect variables

• Step through execution

• Understand unexpected behavior

In production:

• Breakpoints are rarely used directly

• Logs and metrics usually replace interactive debugging

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How to Debug a NullPointerException (NPE)

NPEs are among the most common Java errors.

Steps to debug:

1. Identify the exact line causing the NPE from the stack trace

2. Determine which object is null

3. Trace how that object is initialized

4. Check recent changes or missing data

5. Add null checks or validation if appropriate

NPEs often point to missing assumptions in the code or unexpected inputs.

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Troubleshooting 500 Errors in Production

A 500 error indicates a server-side failure.

Systematic approach:

• Check application logs

• Identify the failing API or request

• Review recent deployments or config changes

• Verify database and external service availability

• Correlate logs with request timestamps

Avoid guessing—use data and logs to narrow the cause.

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✅ 3. Common Production Issues Every Java Support Engineer Encounters

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Memory Leaks

Symptoms:

• Increasing memory usage

• Frequent garbage collection

• OutOfMemoryError

Common causes:

• Static references

• Unclosed resources

• Caches growing without limits

Solution:
Analyze heap usage and review object lifecycle.

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Thread Leaks

Symptoms:

• Thread count continuously increases

• Application becomes unresponsive

• Requests hang indefinitely

Causes:

• Threads not being closed

• Misconfigured thread pools

• Blocking calls

Solution:
Review thread dumps and thread pool configurations.

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High CPU Usage

Symptoms:

• Slow response times

• Timeouts

• CPU spikes

Possible causes:

• Infinite loops

• Heavy computations

• Excessive logging

• Poorly optimized queries

Solution:
Correlate CPU metrics with logs and recent code changes.

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Connection Pool Exhaustion

Symptoms:

• Database timeout errors

• Requests hanging

• Increased latency

Common reasons:

• Connections not closed properly

• Pool size too small

• Long-running queries

Solution:
Ensure connections are closed, tune pool size, and optimize queries.

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Final Thoughts

Great Java support engineers are not defined by how fast they write code—but by how calmly and systematically they solve production issues.

Mastering:

• Logging

• Stack trace analysis

• Debugging techniques

• Common failure patterns

will make you invaluable in consulting and support roles.