Debugging Production Memory Leaks

Introduction

Production memory leaks are difficult to diagnose because they often involve subtle object retention patterns that only appear under real workloads. This guide focuses on advanced techniques for diagnosing leaks in managed runtimes without destabilizing production systems.

Detecting the Symptoms

Look for a steady increase in heap usage, rising GC pause times, and out-of-memory restarts. Correlate memory growth with request volume and feature rollouts to narrow the suspect window.

Investigation Workflow

A structured approach reduces time to root cause.

• Capture runtime metrics (heap size, GC count, LOH usage).
• Identify retention via heap dumps or snapshots.
• Compare object graphs between healthy and degraded instances.
• Validate fixes with load tests before deploying.

C# Example: Preventing Event Handler Leaks

Event handlers are a common source of leaks when objects outlive their intended scope. Use explicit unsubscription or weak references.

public sealed class CacheSubscriber : IDisposable {
    private readonly Cache _cache;

    public CacheSubscriber(Cache cache) {
        _cache = cache;
        _cache.Updated += OnUpdated;
    }

    private void OnUpdated(object? sender, CacheEventArgs args) {
        // Handle cache updates
    }

    public void Dispose() {
        _cache.Updated -= OnUpdated;
    }
}

Production-Safe Diagnostics

Prefer lightweight counters and sampling over full dumps when possible. Trigger heap dumps only when the process is already outside of SLO boundaries, and ensure dumps are stored securely.

Conclusion

Memory leak debugging is a blend of telemetry, targeted dumps, and disciplined code fixes. With careful instrumentation and structured analysis, most leaks can be resolved without prolonged downtime.