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First, identify what “crashing” means
That description can refer to several different events: the container’s main process exits once, Docker restarts it repeatedly, an orchestrated service reports an unhealthy state, or the Docker daemon or host itself stops. These are not interchangeable, and the phrase “multi-agent system” does not identify a particular framework or failure mechanism.
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Before changing the deployment, preserve the stopped container and collect its state. By default, its filesystem remains after exit, which may help with debugging. Start with the container list, then inspect its state and logs:
docker ps -a
docker inspect <container>
docker logs <container>Use the container name or ID in place of <container>. Record the exit code, whether it is currently running, restart count, last-start information, and any configured resource limits. Compare the timestamps in the logs with the exit or restart time; the last visible application message may be more useful than the restart status alone.
What the exit code and logs can tell you
Docker’s running containers guide distinguishes some Docker-level errors from the command’s result. Exit code 125 indicates an error with the Docker daemon; 126 means the specified command could not be invoked. Other exit codes may be the container command’s own exit status, so interpret them with that command’s logs and context rather than assuming a universal meaning.
In particular, do not treat exit code 137 alone as proof of an out-of-memory kill. The evidence here does not establish that interpretation. Check the container state, application output, resource use, and host or daemon evidence together.
If the logs show the application reporting a configuration error, failed dependency, or other explicit problem, investigate that service’s command and configuration before changing Docker limits. If the logs end abruptly, that is a clue to correlate with resource and host events, not a diagnosis by itself.
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Check memory limits and host memory pressure
Docker’s resource constraints documentation says containers have no resource constraints by default: they can use resources as allowed by the host kernel scheduler. A configured hard memory limit caps a container’s memory. A memory reservation is a soft limit that matters under host contention; it is not a guaranteed ceiling.
Docker documents a minimum hard memory limit of 6 MB. That is a CLI constraint, not a recommended allocation for an application. Choose a limit only after measuring what the workload needs and checking what the host can supply. An undersized hard limit can result in termination; raising it without considering host capacity can shift pressure onto other workloads or the host.
During an out-of-memory event, the kernel can kill processes in a container. If the host runs out of memory, the kernel’s OOM killer can stop a container or the Docker daemon. Check host memory pressure alongside container-level limits rather than assuming the container is the only affected component. Docker recommends allowing adequate host memory, testing application requirements, and setting limits where appropriate.
Disabling OOM killing is not a general fix. Docker warns that using --oom-kill-disable without a memory limit can put host processes at risk.
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Docker’s --memory-swap setting represents total memory plus swap when used with --memory. In Docker’s documented example, --memory=300m and --memory-swap=1g allow 300 MB of physical memory plus 700 MB of swap. Frequent swap use can hurt performance, and swap-limit support may be unavailable in a kernel; Docker notes that this can produce a warning. Do not assume swap is enabled or available on a particular host.
Check CPU constraints without mistaking slowness for a crash
CPU shares are relative weights that affect allocation when CPU-intensive containers compete. They do not reserve a fixed amount of CPU when there is no contention. By contrast, --cpus or a CPU quota imposes a limit. These settings can constrain throughput or increase latency, but CPU pressure alone does not prove why a process exited.
Compare the container’s configured CPU settings with observed host contention and the application’s behavior around the exit. If the process is slow but remains alive, that is a different problem from an exit-and-restart cycle; do not use a crash fix for a performance symptom.
Use restart counts to understand the loop
A restart policy determines what Docker does after a container exits; it does not explain why the process exited. Docker documents four choices in Start containers automatically:
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| Policy | What it does |
|---|---|
no |
Default; does not automatically restart the container. |
on-failure[:max-retries] |
Restarts after a non-zero exit status; an optional maximum caps retries. |
always |
Restarts the container automatically after it exits, subject to Docker’s documented behavior for manual stops and daemon restarts. |
unless-stopped |
Restarts automatically unless the container has been manually stopped; its behavior differs from always after manual stops and daemon restarts. |
Docker adds a delay between repeated restart attempts: it begins at 100 milliseconds, doubles up to a maximum of one minute, and resets after the container has run successfully for at least 10 seconds. Inspect the restart count with:
Best Value
docker inspect -f '{{ .RestartCount }}' <container>Also inspect the container’s start-time information to place the attempts on a timeline. A rising count tells you Docker is retrying, not whether the cause is a failing command, resource pressure, or something else. Changing the policy can alter retry behavior, but it will not repair an application bug, missing configuration, resource shortage, or failed dependency.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.For Compose deployments, inspect the service view
If the workload is defined with Docker Compose, use its service-level status and logs to see how the multi-container application is behaving:
docker compose ps
docker compose logsCompose is a tool for defining and running multi-container applications. Its overview describes commands for starting, stopping, and rebuilding services, viewing service status, streaming logs, and running a one-off command. These checks are relevant only if this deployment uses Compose; “multi-agent” does not establish whether it does.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsChoose an intervention that matches the evidence
| Evidence | Intervention to consider | Scope and trade-off |
|---|---|---|
| Exit status and application logs point to the process or its configuration. | Fix the affected command, application, configuration, or dependency. | Targets the failing service rather than changing the entire host. |
| Measurements show the container’s memory cap is below demonstrated workload needs, and the host has capacity. | Adjust the hard memory limit based on measured need. | A higher cap gives the container more headroom but does not create host memory; an undersized cap can lead to termination. |
| Host measurements show insufficient capacity for the workload. | Evaluate host capacity or workload placement. | Additional capacity is relevant only when measurements establish a host shortfall; it is not a default fix for an unexplained exit. |
| The container exits and Docker retries it, but the cause is still unknown. | Use the restart count and timeline as diagnostic evidence before changing policy. | Restart policy changes post-exit behavior, not the underlying failure. |
| Daemon, runtime, kernel compatibility, or kernel-module evidence points below the application layer. | Investigate the Docker daemon and host configuration. | Keep this branch evidence-led; it is not the usual first assumption for every container exit. |
When to investigate Docker or the host
If the evidence points to daemon or kernel behavior rather than an application process, consult Docker’s daemon troubleshooting guidance. It discusses kernel compatibility and missing kernel modules; its linked compatibility-check script works only on Linux. The documentation also covers swap-accounting support and notes host overhead from enabling memory and swap accounting in its Ubuntu and Debian guidance.
Use those checks when the observed error or host configuration makes them relevant. A container exit by itself does not establish a kernel compatibility problem.
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