The Tool Desk
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Find out whether memory pressure actually stopped the stream
A stopped stream is a symptom, not proof that the VPS ran out of RAM. First establish the failure time, then look for a matching out-of-memory (OOM) event. A kernel OOM record can name the process it selected as a victim, but the record needs to be interpreted alongside the memory limit and the surrounding system state.
1. Search the kernel journal around the failure
On a system that uses the systemd journal, inspect the kernel messages for the relevant time window. For example, replace the timestamps with the period when the stream stopped:
sudo journalctl -k --since "2026-10-03 14:00:00" --until "2026-10-03 14:30:00"Look for OOM or “killed process” messages. If a kill record identifies a process name and PID, record both, along with its timestamp and the memory details printed nearby. That identifies the victim named in that event; it does not by itself prove that the named process caused the underlying memory pressure.
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The journal may not contain the incident if logs were not retained or the VPS rebooted and its journal was not persistent. Check whatever system logs your distribution retains as well. The journalctl manual describes journal queries and filters, including filtering by unit and PID.
2. Correlate the victim with the stream service
Find the actual systemd unit that runs the streaming command; do not assume its name. Then inspect its journal over the same time window:
sudo journalctl -u your-stream.service --since "2026-10-03 14:00:00" --until "2026-10-03 14:30:00"Replace your-stream.service with the unit name on your VPS. Compare the service messages and timestamps with the kernel entry. If the PID in the OOM record belongs to the streaming service, that links the victim to the service; if it belongs to a different process, the stream may have stopped as a consequence of another event or a separate connection failure.
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Check the service’s current state and configured restart behavior:
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sudo systemctl cat your-stream.serviceSystemd can also be involved through systemd-oomd, which may terminate services under memory pressure. Check available system logs for its messages too. The installed systemd version and the VPS’s policies are unknown, so the records and configuration on the server determine what happened. See the systemd service documentation for the relevant OOM and restart behavior.
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Check the VPS or cgroup memory limit
An Indian VPS’s effective memory allowance may be smaller than the physical RAM in the host machine. The relevant limit may be applied to the VPS or to a cgroup, so do not infer that the whole host ran out of memory from a process kill on your instance. Check your provider’s stated VPS allocation and any configured cgroup limits, then compare them with the kernel event and available memory history.
Linux OOM selection depends on memory use and the memory pool available to the process; memory or swap limits can define that pool. The oom_score_adj setting can also influence selection. The kernel documentation explains OOM handling and scoring. The live files /proc/<pid>/oom_score and /proc/<pid>/oom_score_adj show current values for an existing process, but they generally cannot establish the score of a process that has already exited. For a past incident, retained event logs are more useful.
Use memory trends to find the pressure source
If you have monitoring data or recurring measurements, compare memory over time with service restarts and the stream’s failure times. A gradual rise can be consistent with a leak or growing cache, but it is not enough by itself to identify either one. Interpret memory alongside CPU, disk, and network activity. Tools such as free, top, and vmstat can help when observing the system; Microsoft’s guidance on Linux VM OOM troubleshooting is Azure-specific, so treat it as general diagnostic guidance rather than evidence about your VPS.
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Low disk use does not rule out a memory problem: disk capacity and RAM are different resources. Conversely, apparent memory pressure does not establish that the streaming process was the victim. Match the event record, PID, service behavior, and memory trend before assigning blame.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.If there is no matching OOM event, check the stream connection
A stream can stop because the connection to YouTube failed, even when no process was killed. Review the streaming application’s logs and any available network or service logs for dropped frames, reconnection attempts, and disconnection times. OBS says dropped frames can indicate an unstable connection or an inability to sustain the configured bitrate; enough dropped frames may lead to a disconnection. Its connection troubleshooting guide, dated 2024-09-30, describes those symptoms.
Compare the OBS or stream log timestamps with kernel and systemd entries. A network warning near the stop time is evidence to investigate, not proof that no OOM event occurred. If both an OOM entry and a connection problem appear, report their order and timing rather than forcing one explanation.
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Common diagnostic mistakes
- Blaming OBS or FFmpeg without a victim record: the title of the incident does not establish which program stopped or why. Use the OOM entry and service logs.
- Treating a killed process as the cause of memory pressure: an OOM victim is the process selected for termination, not necessarily the process that consumed the memory over time.
- Assuming host RAM is the VPS limit: verify the instance’s applicable allocation and any cgroup limit.
- Relying on current
/procvalues after the process is gone: current process files are not a substitute for historical kernel logs. - Calling every stream stop an OOM: check application and connection logs if the system records show no matching memory event.
What can be concluded from the information available
No VPS journal, unit file, distribution version, provider, memory limit, OBS log, or FFmpeg command line is available here. That means the process cannot be named responsibly. The evidence that would settle it is a timestamped kernel OOM entry with its victim name and PID, correlated with the streaming unit’s journal and state. If those records do not show an OOM event, connection and application logs are the next place to look.
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