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If your YouTube stream ended while a Linux VPS was low on memory, do not assume that memory caused it. Check kernel and system-manager logs from the time of the outage, establish whether the kernel or a service-level memory limit triggered an OOM event, and confirm that the affected process was actually your encoder. If those links are missing, treat memory as an unconfirmed possibility and investigate the encoder, network, provider, and YouTube connection separately.
Start with evidence from the outage time
Record when the stream stopped, including the timezone, the encoder command or service name, and whether the process restarted. Inspect logs promptly: they may rotate, and journal entries may not survive a reboot depending on the system’s persistence settings.
The most useful evidence is usually in kernel messages and the systemd journal. An encoder killed by the kernel may not get a chance to write a final error to its own log, so an empty or abruptly ending encoder log does not rule out OOM.
Search kernel and journal messages
Use journalctl -k to inspect kernel journal entries and dmesg to view the kernel ring buffer. Search around the recorded outage for terms such as out of memory, killed process, or oom, and read surrounding entries for context. Exact filtering flags and available fields vary with the installed journal and distribution; check the local journalctl manual before relying on a particular command-line option.
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Kernel OOM behavior and journal filtering are documented in the Linux kernel’s Control Group v2 documentation, kernel virtual-memory documentation, and the systemd 255 journalctl manual.
Do not infer OOM from a memory graph alone
A host-wide memory display is not enough to explain a process failure. A service can hit a cgroup memory cap even when an aggregate host view appears to show memory available elsewhere. Conversely, a message about an OOM kill does not prove the stream ended because of that event. You need to match the event’s time and affected process or service to the encoder that was streaming.
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Determine whether the limit was host-wide or service-level
There are two important scopes to distinguish: a global kernel OOM event and an OOM event confined to a cgroup. Look for a named cgroup, unit, or process in the logs. Then compare its resource controls and memory accounting with the event.
Inspect cgroup v2 memory accounting
If the workload uses cgroup v2, inspect the files for the encoder’s relevant cgroup:
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memory.current: current memory usage for the cgroup.memory.max: the hard memory limit. The kernel documentation says that if the limit is reached and usage cannot be reduced, the cgroup OOM killer is invoked.memory.events: event counters that can help show whether the cgroup encountered memory pressure or an OOM condition.memory.stat: breakdowns of memory use that help put the current usage in context.
Find the cgroup path from the process or service rather than inspecting an unrelated directory. Cgroup layout, available files, and the meaning of observed counters depend on the system’s cgroup version and configuration. See the kernel’s cgroup v2 documentation for the interface and semantics.
Check systemd limits for the encoder unit
If systemd manages the encoder, identify its unit and inspect the effective unit configuration and journal around the outage. Pay particular attention to resource-control settings such as MemoryHigh= and MemoryMax=. Check the installed systemd version and whether systemd-oomd is active: available directives and OOM-handling behavior depend on version and configuration.
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Systemd documents service execution and resource-control settings in systemd.exec and system-wide manager configuration in systemd-system.conf. Do not raise a limit before comparing it with the VPS’s actual capacity and the needs of other services on the machine.
Prove that the OOM event explains the stream outage
Build a timeline using the kernel or journal entry, the encoder’s own logs, and any service restart record. Check that the process name, PID, cgroup or unit, and timestamp correspond to the actual streaming process and the moment the stream ended.
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- Strong connection: the OOM record identifies the encoder process or its cgroup, and its time aligns with the stream ending.
- Incomplete connection: an OOM record exists near the outage, but names a different process or unit. It may be incidental; find out whether the encoder was also affected.
- No recorded connection: no relevant OOM event appears in the available logs, or the evidence is too incomplete to match it to the encoder. Memory remains a hypothesis, not a diagnosis.
Also note whether the encoder restarted automatically. A restart can restore the process without explaining why the stream disconnected, and an unrelated helper process being killed may coincide with an outage without causing it.
If the logs do not show OOM, investigate other failure paths
Do not force a memory explanation when the evidence does not support one. Compare timestamps across these sources:
- Encoder: inspect its error output, exit status, and service logs for an encoder crash or an intentional stop.
- Network: check for connection interruptions between the VPS and YouTube around the failure.
- VPS provider: look for host or instance events that could have interrupted the workload.
- Platform: review the stream’s available YouTube status information. No specific YouTube dashboard message or platform-side signature is established here, so do not treat any particular message as proof of VPS OOM.
Compare the outage time, process and unit identity, host-wide versus cgroup-scoped memory evidence, configured limit versus observed usage, and encoder logs versus kernel and system-manager logs. The likely memory requirement depends on the encoder, resolution, frame rate, codec, software, and concurrent workloads; there is no universal RAM threshold that diagnoses this failure.
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