Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteIf a YouTube live stream stops while its Linux VPS appears to run out of memory, confirm the cause in logs before changing RAM or restarting the encoder. Check kernel and systemd records at the outage time, identify whether the encoder was killed, and determine whether the event was host-wide or limited to a service cgroup. A full host memory display alone cannot rule out a per-service memory cap.
First, establish when the stream stopped
Record the approximate outage time and timezone, the encoder process or systemd service name, and whether it restarted. Preserve the relevant logs promptly: retention and persistence depend on the installation, and a reboot or log rotation may remove useful evidence.
- Note the encoder’s command, process ID if available, and unit name.
- Keep the encoder’s own logs and exit status, but do not rely on them alone: a process killed by the kernel may not get a chance to write a final message.
- Record whether other services on the VPS were affected at the same time.
Look for an OOM event in kernel and journal logs
Start with the kernel journal and kernel messages around the outage. Search for terms such as out of memory, killed process, and oom, then inspect the surrounding entries for the process, timestamp, and scope of the event. journalctl -k and dmesg are common entry points; exact options and available output vary by distribution and installed versions. The systemd 255 journalctl manual documents journal filtering.
Do not treat a matching OOM line as proof that the stream encoder caused the outage. Match the recorded process name and PID, cgroup or unit, and timestamp to the encoder that was actually streaming. An unrelated process can be killed at about the same time without being the reason YouTube went offline.
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Determine whether memory pressure was host-wide or cgroup-local
A global kernel OOM event and a cgroup-local OOM event are different findings. A service can hit its own memory cap even when a broad host-level display appears to show capacity elsewhere. If the logs identify a cgroup, inspect the relevant cgroup’s accounting and limits. On cgroup v2, useful files include memory.current, memory.max, memory.events, and memory.stat.
The Linux kernel’s Control Group v2 documentation describes memory.max as a hard limit. If usage reaches that limit and reclaim cannot reduce it, the cgroup OOM killer is invoked. Read memory.events alongside the limit and current usage to understand what happened; a limit value by itself does not establish that it caused this particular outage.
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Check the encoder’s systemd unit and OOM policy
If the encoder runs as a systemd service, identify its unit and inspect the effective configuration and journal around the failure. Look for resource controls such as MemoryHigh= and MemoryMax=, and check whether systemd-oomd is in use. Available directives and behavior depend on the installed systemd version and configuration. Consult the systemd documentation for unit execution and resource-control settings and system-wide configuration.
Before raising a limit, compare it with actual host capacity and the memory needs of other services. Changing a cap without understanding the host’s overall allocation can move the failure rather than solve it.
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Compare the evidence before assigning a cause
| Evidence to compare | What it helps establish |
|---|---|
| Outage timestamp versus kernel, journal, and encoder timestamps | Whether the events line up closely enough to investigate as related. |
| Recorded process, PID, cgroup, or unit versus the actual encoder | Whether the OOM event affected the streaming workload rather than an unrelated process. |
| Host-level evidence versus cgroup memory accounting | Whether the event was global or scoped to a service limit. |
| Configured memory limit versus observed usage and event counters | Whether a limit was reached and whether the cgroup recorded OOM activity. |
| Encoder logs versus kernel and system manager logs | Whether the encoder reported its own failure or was stopped externally. |
There is no universal RAM threshold for this diagnosis. Memory use varies with encoder software, codec, resolution, frame rate, and concurrent workloads; assess the actual process and limit rather than assuming a fixed requirement.
If the logs do not show an OOM event
Keep memory exhaustion as an unconfirmed hypothesis if no relevant memory event appears in available logs. Continue along other failure paths:
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- Encoder: Review its logs, exit status, and restart behavior for errors that coincide with the stream ending.
- Network: Check for interruptions in the VPS’s connection or in the encoder’s connection to YouTube.
- Provider: Look for VPS provider events or service interruptions around the same time.
- Platform: Check the available YouTube stream-health information. The evidence here does not establish a particular YouTube dashboard message or platform-side signature for an OOM event.
Common diagnostic mistakes
- Relying on a single host memory snapshot: It may not reveal a service-level cgroup cap. Inspect the affected cgroup and unit controls.
- Assuming any OOM kill stopped the stream: Confirm process identity and timing against the encoder.
- Increasing limits before checking capacity: Review other workloads and host capacity first.
- Calling the failure an OOM without logs: If evidence is missing, investigate encoder, network, provider, and platform causes separately.
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