Troubleshooting Docker Swarm Container Crashes with Exit Code 137

Problem:

The client encountered a recurring issue within the Docker Swarm environment, wherein containers sporadically crashed with exit code 137. This behavior, indicative of potential memory-related issues, was exacerbated by the absence of corresponding container logs, complicating the diagnostic process.

Process:

Initial Inquiry and Investigation:

Prompted by the client’s request for a Root Cause Analysis (RCA), an exhaustive investigation was initiated. Essential components such as the Docker Swarm version, utilization of audit.rules, Dockerfile specifications, and underlying source code were meticulously examined to glean insights into the issue. A comprehensive review encompassed potential Out-of-Memory (OOM) scenarios, firewall configurations, Docker log analysis, memory consumption patterns, and disk usage metrics.

Troubleshooting Efforts:

A systematic approach was adopted, commencing with the reconstruction and reinitialization of Docker Swarm followed by the redeployment of applications. The health and integrity of virtual machines (VMs) were scrutinized, with particular emphasis on firewall logs, network connectivity, and resource utilization metrics. Diagnostic assessments, including the NC command, were conducted to assess Docker node connectivity and responsiveness.

Observations:

Anomalous spikes in resource consumption were noted on specific nodes within the Swarm environment, warranting further investigation.

Potential Solutions Discussed:

Contemplation of Docker version upgrades to potentially mitigate stability concerns and enhance system performance. Consideration of node rebooting within the Swarm post-troubleshooting to rectify underlying issues. Exploration of permissions intricacies to identify potential iptables-related anomalies impacting container stability.

Hypothesized Root Causes:

• JVM Heap Memory Size Issue: Potential discrepancies between JVM heap size and Docker container memory limits leading to memory exhaustion.
• Heap Swelling: Intermittent surges in application memory demand exceeding Docker container memory limits, resulting in abrupt crashes.
• Explicit Resource Limits: Conflict arising from overly restrictive resource limits set within Docker Swarm impacting application performance.
• Swarm Service Update or Rebalancing: Unforeseen repercussions during service updates or rebalancing operations within Docker Swarm leading to service disruptions.
• Underlying Host Issues: Kernel panics, critical resource shortages, or system reboots adversely impacting Docker container stability.
• Container Deadlock or Unresponsive State: Application-level issues precipitating container deadlock or unresponsiveness, necessitating forced termination.
• Ineffective Garbage Collection: Suboptimal garbage collector settings impacting JVM’s memory management efficiency and exacerbating memory-related issues.
• Faulty Seccomp/Docker Config: Potential modifications to the default seccomp profile impacting all VMs within the Docker Swarm environment, leading to container crashes.

Solution:

After meticulous investigation, a pivotal discovery was made, implicating a significant alteration to the Docker Swarm’s default seccomp profile as the primary culprit behind the container crashes. The following recommendations were provided:

• Enable audit logging for seccomp events to monitor rejected seccomp checks and expedite troubleshooting efforts.
• Initiate the deployment of the configuration in a controlled test environment to assess its impact on system performance and refine operational procedures.
• Conduct a pilot test during off-peak hours in the production environment to validate findings and fine-tune deployment strategies.

Conclusion:

The investigation into Docker Swarm container crashes with exit code 137 revealed a complex interplay of factors, primarily centered around potential alterations in the SECCOM profile. Despite the absence of immediate OOM events in logs, the abrupt termination of containers pointed towards restrictive security settings affecting system calls. The swift resolution achieved through the restoration from backup underscored the reversible nature of the configuration changes. Moving forward, proactive measures such as enabling SECCOM logging and conducting pilot testing will fortify the environment against similar incidents. Continuous monitoring of system calls and rigorous testing protocols will bolster the resilience of the Docker Swarm deployment, ensuring the smooth operation of critical services. This case exemplifies the importance of thorough analysis and collaboration in identifying and addressing intricate technical challenges within complex distributed systems like Docker Swarm.