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You cannot tell which process stopped a YouTube 24/7 stream from the symptom alone. Check the kernel journal for an OOM-kill record, note the victim process and PID, then correlate its timestamp with the systemd service running the stream. If there is no matching out-of-memory evidence, investigate connection drops and the stream application’s logs instead. Without the VPS logs, the process remains unidentified.
1. Check whether an out-of-memory event occurred
Start with the time the stream stopped. Search the retained kernel journal around that time for messages mentioning an out-of-memory condition or a killed process. A kernel kill record may name the victim and PID; record both, along with the event timestamp. Linux’s OOM documentation explains that victim selection depends on memory use and the memory pool available to the process. Limits on memory or swap can define that pool, and oom_score_adj can change a process’s score.
The title does not establish which distribution, VPS provider, service, or memory limit is involved, so there is no single provider-specific command or log path to assume. Use the journal tools available on the server and the actual incident time. The journalctl manual documents filtering journal entries by time and structured fields such as unit and PID.
Interpret the record, not just the word “OOM”
- A kill entry that names a process and PID is evidence of the kernel’s selected victim, not necessarily the only process involved in the memory pressure.
- Check whether the relevant limit belongs to the VPS, a cgroup, or another configured resource pool. A VPS can be constrained below the physical RAM of its host.
- For a past incident, do not rely on
/proc/<pid>/oom_scoreor/proc/<pid>/oom_score_adjas historical records: those files describe a process that currently exists and may be unavailable after it exits. Retained journal messages are more useful for identifying an earlier victim.
2. Correlate the victim with the streaming service
Find the systemd unit that launches the streaming process, then compare the OOM timestamp and PID with that unit’s journal entries and state. Filter the journal using the real unit name and a time window around the event; do not assume the unit is named after OBS or FFmpeg. If the process was started outside systemd, identify its actual supervisor or launch method before drawing a conclusion.
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Systemd’s service documentation describes how OOMPolicy= affects a unit when a process is OOM-killed. Depending on the configured policy, other processes in the unit may remain running, be stopped, or be killed as a group. The unit may enter an OOM-kill-failed state, after which its configured Restart= behavior can apply. The installed systemd version and the unit’s actual settings are unknown, so inspect the service configuration and journal rather than assuming a restart policy.
Consider systemd-oomd as well as the kernel
Systemd’s service documentation also covers systemd-oomd, which can terminate services under memory pressure. A service termination associated with memory pressure therefore does not, by itself, prove that the kernel selected and killed the process. Review available system and unit journal messages and the unit’s resulting state to establish which mechanism acted.
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3. Check the memory trend and applicable limit
Compare memory observations before the stop with the configured limit that applied to the service. A steadily rising process or service footprint can suggest a leak or cache growth, but that trend alone does not prove either cause. Interpret memory alongside CPU, disk, and network behavior; Microsoft Learn’s Linux VM performance guidance gives examples of tools such as free, top, and vmstat. That guidance is for Azure VMs, so treat it as general diagnostic guidance, not evidence about a particular Indian VPS.
Disk space is not a substitute for RAM or swap capacity. If the event record shows memory exhaustion, having free disk space does not rule it out. Conversely, a low memory reading taken after the service stopped does not establish what the limit or usage was at the time of failure.
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4. Rule out a stream connection failure
A stream can stop without a process being killed. OBS’s official connection troubleshooting guide, dated 2024-09-30, says dropped frames can indicate an unstable connection or that the connection cannot sustain the configured bitrate; excessive dropped frames may lead to disconnection. Check OBS or other stream-side logs for dropped frames, reconnect attempts, and connection-loss messages around the stop time, and compare them with the system and unit journals.
A connection problem does not explain a matching OOM-kill record, and an OOM record does not automatically explain every stream symptom. If both appear, report their order and timestamps rather than forcing a single cause.
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5. Use a simple evidence table
| Evidence | What it supports | What to check next |
|---|---|---|
| Kernel journal names a killed process and PID near the stop | A kernel OOM kill occurred; the record identifies its victim. | Correlate the PID and timestamp with the streaming unit and inspect the applicable memory limit. |
| Unit journal or state records an OOM-related termination, but no matching kernel victim record is available | Systemd policy or systemd-oomd may be involved; the actor is not established by the unit symptom alone. | Inspect available system journal messages, OOMPolicy=, restart settings, and the unit’s state. |
| Stream logs show dropped frames or connection loss, with no matching OOM evidence | A network or bitrate-related disconnection is a plausible explanation. | Compare the connection symptoms with the exact stop time and service logs. |
| Both memory-termination and connection evidence appear | More than one event may have contributed, or one may have preceded the other. | Build a timestamped sequence; do not attribute the stop to one cause without supporting evidence. |
6. Troubleshoot common dead ends
- “The stream stopped, so OBS must have been killed.” A stopped stream does not identify a victim. Find a kill record and PID, then link that evidence to the unit.
- “The server has RAM, so it cannot be an OOM event.” The relevant VPS or cgroup limit may be lower than the host’s physical memory. Check the limit that applied to the service.
- “The service restarted, so there was no OOM.” Systemd restart behavior may follow a termination. Check the unit journal and its OOM and restart configuration.
- “There is no current process score, so the past victim cannot be found.” The
/procscore files are current-process information. Look for retained journal records from the incident. - “Dropped frames prove RAM ran out.” OBS associates dropped frames with connection instability or inability to sustain bitrate. Match those logs against system evidence instead.
- “One OBS report proves a general OBS memory leak.” A GitHub issue opened 2022-01-19 describes one user’s Ubuntu 20.04 and OBS Studio 27.1.3 setup, with steadily rising RAM and a reported OOM kill. The report also describes plugins, browser sources, and RTMP streaming to an internal server; it is one user’s account, not proof of a general defect or of what happened on another VPS.
7. If the logs were not retained
If the VPS has rebooted or journal retention did not preserve the incident, the historical victim may no longer be recoverable from the current process table. Check whatever system, unit, and application logs remain, and record timestamps and memory measurements during a subsequent incident. Whether journal entries survive a reboot depends on the server’s configuration. Without a retained kill record or equivalent service evidence, report the cause as unconfirmed rather than naming OBS, FFmpeg, or another process.
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