Q: Your monitoring dashboard shows that a server's memory usage has been steadily climbing 1% per day for two weeks. The application developers say "it's fine." How do you approach this as an SRE?

A steady, linear increase in memory usage is a classic memory leak pattern. Even if the application functions today, at 1%/day, the server will OOM in approximately 2–3 weeks.

• Quantify the risk:
• Current usage: 70% → OOM in ~30 days
• Calculate the exact date the server will hit critical threshold (e.g., 95%)
• Present a clear timeline to developers: "This server will crash on [date] without intervention"
• Gather evidence:
• Identify the leaking process: Compare RSS (Resident Set Size) growth across processes. The one growing linearly is the culprit.

SRE approach: Never dismiss a linear trend—it's a countdown timer to an outage.

# Track per-process memory growth
   ps aux --sort=-%mem | head -20
   # Check for growing heap
   pmap -x <PID> | tail -1
   # Monitor over time
   pidstat -r -p <PID> 60

• Short-term mitigation:
• Schedule periodic application restarts during off-peak hours
• Set up memory-based alerts at 85% and 95%
• Implement cgroup memory limits to prevent one process from OOMing the entire server
• Long-term fix: Work with developers to profile the application using language-specific tools (Valgrind for C/C++, heap dumps for Java, memory profilers for Python/Go).