Why does my critical process keep dying?

If your critical process keeps crashing or exiting unexpectedly, there are a few potential causes to investigate:

Hardware Failure

Hardware problems like bad RAM, failing hard drives, overheating CPUs, loose connections, or power supply issues can all cause processes to crash or die unexpectedly. Check for overheating, run diagnostics like memtest86 to check RAM, and monitor disk health. If it’s a physical server, re-seat components and check connections. Replace failing hardware components like hard drives or power supplies.

Software Bugs

Bugs in the critical process’s code or in linked libraries can also cause crashes. Review the logs for any exception messages or stack traces that point to a particular code path. Enable core dumps or memory dumps if possible to get more details. Reproduce the crash in a dev environment if you can. Update to the latest versions of libraries. Have developers review the code and fix any bugs found.

Resource Exhaustion

If the process is dying because it’s running out of memory, file handles, network sockets or other limited resources, then look for leaks or other bottlenecks. Profile the application’s resource usage over time to identify exhaustion issues. Tune limits like ulimits, VM memory settings, open file limits appropriately. Check for and fix any resource leaks in the application code.


Multi-threaded processes can deadlock where two threads end up waiting on each other indefinitely. This leads to the process hanging and becoming unresponsive. Identify potential deadlock conditions like shared mutexes. Use thread dumps to view blocked threads. Rework the synchronization logic to avoid deadlocks.


A livelock occurs when threads are busy responding to each other but unable to make progress. This can manifest as a process that consumes 100% CPU but is unable to complete any work. Identify parts of the code that may be repetitively retrying operations. Limit retries with timeouts. Make sure threads yield when appropriate.


Starvation happens when a thread isn’t able to gain regular access to shared resources and is effectively ignored by other threads. This could prevent it from completing critical tasks. Review synchronization logic around shared resources like mutexes and semaphores to ensure fair scheduling.

Security Violations

If the process tries to access resources or perform operations beyond its permissions, the operating system may forcibly kill it. Make sure the process is running under the expected user with the right privileges. Validate all input and parameters carefully to avoid buffer overflows or command injections that could allow unintended access.

Excessive Load

Running under very high load for sustained periods can also lead to unpredictable process deaths. Tune the load balancing configuration to avoid overwhelming any single process instance. Resize your server capacity to handle the expected load. Set up auto-scaling groups to automatically add more capacity during spikes.

Cascading Failures

Failures in one part of a system can sometimes cascade to bring down other dependent processes. Setup monitors and alarms for key services so you can respond quickly to outages. Implement circuit breakers and bulkheads to limit failures from spreading. Have fallback mechanisms and degraded modes so processes can stay running as much as possible despite failures in other parts of the system.

How to investigate process crashes

When a process crashes unexpectedly, here are some steps you can take to troubleshoot further:

Check the logs

Review application and system logs to look for exception messages, stack traces, or other clues about what happened right before the crash. For example, logs may show a fatal error occurred in a linked library or dependent service.

Get a core dump

Having a core dump or memory dump of the crashed process can hugely help debugging. It records the process state and contents of memory at the moment of the crash. Enable core dumps in your environment if not already, then analyze the dump using a debugger.

Reproduce the crash

Try to trigger the crash again, ideally in a dev/test environment. Repeat the same actions leading up to the failure. Make the slightest changes to reproduce it more easily if needed – e.g. reduce timeouts or other delays.

Stress test the system

Perform stress or load testing around the circumstances of the failure. Increase load, starve resources like RAM or file handles, or trigger more concurrent threads. This may reveal issues like deadlocks, livelocks or resource exhaustion more readily.

Attach a debugger

Use a debugger like gdb to attach to the running process. Then you can set breakpoints, examine stack traces and monitor variables when crashes occur while the process is running under the debugger.

Monitor resource usage

Use profiling tools to monitor how CPU, memory, file handles, network sockets or other resources are consumed over time. Sudden spikes may point you to leaks or a spot where resource exhaustion occurs.

Analyze usage patterns

Review usage analytics to see if crashes correlate with specific workflows, numbers of concurrent users, high request volumes or other patterns. This may highlight the conditions most likely to trigger crashes.

Mitigations to prevent process crashes

Once root causes have been identified, here are some mitigations to prevent future crashes:

Upgrade hardware

If hardware resources are overloaded or components are faulty, upgrade to more robust servers with faster CPUs, more cores, increased memory and redundancy like RAID disk arrays.

Fix bugs

Have developers fix any bugs identified that lead to crashes. This may require making code changes, then thoroughly testing them before redeploying the fixed application.

Improve error handling

Robust error handling can allow the application to recover gracefully in the face of failures. Ensure critical exceptions are caught so they don’t crash the whole process.

Tune OS limits

Adjust operating system limits like max open files, max processes, network socket limits to accommodate application needs. Prevent crashes from hitting limits.

Add retry logic

Build in fail-over retry logic so the application can retry operations that fail initially due to transient issues like network blips.

Limit concurrent requests

Applying throttling may alleviate pressure if concurrent user requests or jobs are overwhelming. Limit to a sustainable level to keep load manageable.

Partition work

Break up large processing tasks into smaller partitioned work streams if possible. Crashes are less likely to take down the entire application if failures are compartmentalized.

Autoscale capacity

Setup auto-scaling of additional application instances during peak loads so that traffic and work is distributed across a larger resource pool to avoid overtaxing any single process.

Circuit breakers

Implement circuit breaker patterns where downstream failures trigger a state change to stop calling the failing service to allow it time to recover, preventing cascading crashes.

Rate limiting

Adding rate limiting can smooth out traffic spikes and prevent surges overwhelming the application and resources.

Chaos testing

Proactively simulate failures like crashes to test the system’s resilience. Diverse testing exposes weaknesses and proves effectiveness of mitigations.

Monitoring to quickly detect crashes

To minimize downtime from crashes, implement monitoring that can rapidly alert you when a process dies unexpectedly:

Heartbeat monitoring

configure each process to emit a heartbeat or health check signal every few seconds. The absence of this signal triggers an alert.

Resource monitoring

Monitor key system resources like CPU, memory, disk, network bandwidth for the server running the processes. A sudden spike or drop may signify a crash.

Metrics monitoring

If the process produces business metrics like transactions processed, track these stream and alert on an unexpected halt in metrics.

Log monitoring

Ship logs to a centralized analysis tool. Watch for increasing ERROR, WARN messages leading up to crashes or patterns associated with known crash causes.

External user monitoring

Monitor external user traffic hitting the application. If visits or transactions suddenly stop, it likely signifies an outage.

Synthetic monitoring

Set up synthetic user journeys that mimic real usage and paths through the site. Failures in these can confirm trouble and pinpoint the issue.

Speeding recovery after crashes

To minimize downtime after a failure occurs:

Crash recovery scripts

Automatically start, stop and restart the process using a script or configuration management tool for rapid, consistent recoveries.

Decoupled components

A microservices approach with independent components can allow parts of the system to be restarted without full site outages.

Hot swappable standbys

Maintain warm standbys or mirrored backups that can seamlessly take over in the event of a failure, minimizing interruption.

Revision control

Use source control with ability to roll back and redeploy previous versions quickly in an emergency until deeper fixes can be made.

Chaos engineering

Incorporate frequent drills to practice failures and speed up response. Understand how long full recovery takes and optimize where possible.

Post-mortem reviews

Formal reviews of each major incident to identify root causes and learnings for preventing future occurrences.


Unexpected crashes of critical processes can be frustrating and disruptive. However, a thorough investigation process, robust monitoring, and automated recovery procedures can minimize both the frequency of crashes and their impacts. Look for root causes like hardware failures, software defects, deadlocks, and resource exhaustion. Implement mitigations like upgrading capacity, fixing bugs, and adding redundancy. With proper tools and practices, critical process crashes can be quickly dealt with to limit downtime and data loss.