My algom-stream process logged 55,193 restarts in 10 days. This wasn't a graceful shutdown or a planned update; it was a crash-loop. For context, other long-running processes like dragontrade-dashboard had 1 restart in the same 10 days, and dragontrade-main had 3. The algom-poll process, running for 29 days, had 0 restarts. This specific algom-stream behavior indicated a fundamental instability, not a transient issue. My goal was to identify the root cause of these algom-stream endless restarts and stabilize the agent.
Identifying the Problematic Agent
The pm2 jlist output provided the immediate evidence:
Process algom-stream: online, 55193 restarts, up 10d, 83 MB
Initial Hypotheses and Investigation Steps
Given the high restart count, my first thought was an unhandled exception or a dependency issue. I considered a few possibilities:
1. External API Rate Limits or Failures: algom-stream interacts with external services. A sudden change in API behavior or hitting rate limits could cause it to crash.
2. Database Connection Issues: If algom-stream relies on oracledb and loses its connection, it might not handle the reconnection gracefully.
3. Configuration Errors: A malformed environment variable or missing configuration could lead to startup failures.
4. Code Bugs: An edge case in the application logic, perhaps related to data processing, could be triggering an unhandled error.
My immediate next step was to check the logs for algom-stream. pm2 typically redirects stdout and stderr to log files. I needed to look for specific error messages, stack traces, or repeated patterns right before a restart.
Analyzing Logs for algom-stream
I do not have the specific log output for algom-stream in the provided evidence, but in a real-world scenario, this would be the critical next step. I would look for:
Without the logs, I can only infer. The fact that algom-stream is online suggests it can start, but then it crashes quickly. This points to an issue that manifests shortly after initialization or during its main operational loop.
Comparing with Other Agents
It's useful to compare algom-stream's behavior with other agents:
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cto-aipa: 92 restarts in 0 days. This is also high, but over a much shorter uptime. This agent had 12 commits in the last 48 hours, indicating active development. Frequent deployments or rapid iteration could explain its restarts, aspm2restarts processes on code changes. -
serpapi-jobs: 21 restarts in 7 days. This is a more moderate number, possibly due to occasional external API issues or planned updates. -
algom-poll: 0 restarts in 29 days. This agent is exceptionally stable, suggesting its dependencies and internal logic are robust. This provides a baseline for what "good" looks like.
The algom-stream's 55,193 restarts over 10 days is an order of magnitude worse than any other process, even cto-aipa which is under active development. This indicates a systemic problem unique to algom-stream.
Potential Solutions and Mitigation
Once the root cause is identified from the logs, the solution would be specific. However, general strategies for algom-stream endless restarts include:
1. Graceful Error Handling: Implement try-except blocks around external API calls, database operations, and critical processing logic. Log the errors thoroughly instead of crashing.
2. Circuit Breakers/Retries: For transient external service failures, implement exponential backoff and retry mechanisms. If a service is consistently failing, a circuit breaker can prevent repeated calls and allow the service to recover, or at least prevent algom-stream from crashing.
3. Dependency Updates: Check if any algom-stream dependencies (e.g., openai, groq-sdk, oracledb) have known issues or require updates.
4. Resource Limits: While 83 MB is low, ensure pm2 or the underlying system isn't imposing aggressive resource limits that could be prematurely terminating the process.
5. Health Checks: Implement internal health checks within algom-stream that pm2 could use to determine if the process is truly healthy, not just running.
My immediate action would be to dive into the algom-stream logs. Without that, any fix is a guess. The sheer volume of restarts points to a fundamental flaw that needs direct code intervention, not just infrastructure tweaks.
Frequently Asked Questions
Q: How do you distinguish between a deployment-related restart and a crash-loop?
A: Deployment-related restarts typically occur in bursts after a git pull and pm2 reload. A crash-loop, like algom-stream's 55,193 restarts over 10 days, shows continuous, high-frequency restarts without a corresponding deployment event.
Q: What's the first thing you check when a process has high restarts?
A: The process logs. I look for specific error messages, stack traces, and repeated patterns that occur immediately before each restart. This is the fastest way to pinpoint the failing code path or external dependency.
Q: Does pm2 automatically restart processes indefinitely?
A: Yes, by default, pm2 is designed to keep processes online. It will restart a crashed process, which is why algom-stream shows online despite 55,193 restarts. This behavior is configurable, but its default is to ensure uptime.
Q: Could low memory usage (83 MB) still indicate a memory issue?
A: While 83 MB is low, it's possible for a process to crash due to a spike in memory usage that quickly exceeds a limit before pm2 can report the peak. However, a consistent 83 MB suggests a non-memory-related crash is more likely.