You cannot identify the killed process from the fact that a YouTube stream stopped. Check the VPS’s retained kernel and systemd logs around the failure time: an out-of-memory (OOM) record may name the victim process and PID. Then correlate that evidence with the stream service’s journal and OBS or other streaming logs. Without those records, it is not possible to say whether OBS, FFmpeg, another process, or a network interruption caused the stop.
First, establish whether memory pressure actually stopped the stream
A stopped stream is a symptom, not proof that the VPS ran out of RAM. The kernel may choose an OOM victim when the memory available within the applicable resource pool is exhausted; that pool can be affected by a VPS or cgroup limit, not just the physical memory installed in the host. Linux also uses an OOM score, which can be influenced by oom_score_adj. See the Linux kernel OOM documentation.
Use the time the stream stopped as the anchor for your investigation. If you do not know the exact time, narrow it down from YouTube’s stream status and the service’s last logs. Work in the VPS’s local time zone when filtering logs, and account for any difference between that and the time shown by YouTube.
Find the process named in an OOM event
Search the kernel journal around the incident
On a system that uses systemd’s journal, inspect kernel messages in a narrow time window. Replace the timestamps with the incident’s actual start and end times:
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sudo journalctl -k --since "2026-10-03 10:00:00" --until "2026-10-03 10:15:00"Look for messages explicitly reporting an out-of-memory condition or a process killed by the OOM killer. When a kill record names a process and PID, record both, along with its timestamp and the surrounding messages. Do not infer that OBS or FFmpeg was killed unless the event actually identifies it.
The example dates above are placeholders for the command; use the date and time of your incident. journalctl supports time and structured-field filtering; its manual explains the available options.
Check whether the records survived
If the VPS rebooted after the stream stopped, the relevant entries may be in a previous boot’s journal, if persistent journal storage is enabled. Check available boots with:
sudo journalctl --list-bootsThen query the relevant boot and time window, for example:
sudo journalctl -k -b -1 --since "2026-10-03 10:00:00" --until "2026-10-03 10:15:00"Here, -b -1 means the previous boot; choose the correct boot for the incident. If the journal was not retained or has rotated away, the current /proc files cannot reliably recover a dead process’s historical OOM score or identity. The kernel’s /proc/<pid>/oom_score and oom_score_adj describe a process that still exists, so they are not substitutes for retained records of a past kill.
Correlate the victim with the stream service
Identify the actual unit and inspect its journal
Find the service unit your setup uses rather than assuming a standard name. If you know part of it, list matching units:
systemctl list-units --type=service --all | grep -iE 'obs|ffmpeg|stream'Once you have the exact unit name, inspect its logs during the same time window:
sudo journalctl -u your-stream.service --since "2026-10-03 10:00:00" --until "2026-10-03 10:15:00"Replace your-stream.service with the unit’s real name. Check its state and recent status details as well:
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sudo systemctl status your-stream.serviceCompare the kernel event’s time and PID with the unit’s messages. A process named in a kernel kill record may or may not be the main streaming process: the unit could also run helper processes, and the stream may have been affected by a service-level policy. Use the unit journal and its configuration to establish the relationship.
Check systemd’s OOM and restart behavior
Systemd’s OOMPolicy= setting controls what happens to a unit after an OOM kill. Depending on the configured policy, remaining processes may be left running, stopped, or killed as a group. A unit can also enter an OOM-kill-failed state; if Restart= is configured, that state may trigger a restart. The actual result depends on the installed systemd version and unit configuration, which are not known here. See the systemd service manual.
Inspect the unit’s effective properties and its file or drop-in configuration. For example:
systemctl show your-stream.service -p OOMPolicy -p RestartAlso review the journal for messages from systemd-oomd, if that service is installed and active. Systemd-oomd can terminate services under memory pressure; an event involving it is distinct from a kernel OOM-killer record. Do not assume either mechanism acted without matching journal evidence.
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Check the memory limit and trend
VPS plans may impose a memory limit that differs from the host’s physical RAM. If your service runs in a cgroup, inspect the applicable limit and usage for that service; the exact cgroup files and commands depend on the system’s cgroup version and layout. Also check whether swap is configured and available, but do not treat spare disk space as spare RAM.
Compare the incident time with memory, CPU, disk, and network measurements rather than reading one metric in isolation. A gradual memory rise can be consistent with a leak or cache growth, but it does not prove either. Tools such as free, top, and vmstat can help observe current behavior; they cannot by themselves reconstruct a past incident. Microsoft’s guidance on Linux VM performance bottlenecks is for Azure VMs, so treat its monitoring advice as general diagnostic guidance, not evidence about your VPS provider.
Rule out a stream connection failure
If the kernel and systemd records do not show an OOM-related event, inspect the streaming application’s logs and YouTube’s stream status. A live stream can stop because the connection is unstable or the configured bitrate cannot be sustained. OBS’s connection guidance, dated September 30, 2024, says dropped frames can indicate these problems and that excessive dropped frames may lead to disconnection: OBS dropped frames and connection issues.
Network trouble is an alternative explanation, not proof that no memory event occurred. Match the timestamps: a kernel kill record, service restart, and OBS disconnection warning may all appear near the same time. If multiple records exist, report their sequence rather than forcing them into one cause.
Best Value
Use this evidence checklist before naming a cause
- Kernel evidence: Was there an OOM message at the relevant time? If so, what process name and PID did the kill record identify?
- Service evidence: Which unit ran the stream, and what does its journal show at that time? Did it stop, restart, or report an OOM-related state?
- Policy evidence: What were the effective
OOMPolicy=andRestart=settings? Was systemd-oomd involved? - Capacity evidence: What memory limit applied to the VPS or service, and what do retained usage measurements show before the stop?
- Streaming evidence: Did OBS or the streaming application report dropped frames, loss of connection, or another error?
If no OOM record or relevant service log was retained, the specific process remains unidentified. State that limitation; do not turn an unverified suspicion into a diagnosis.
What a reported OBS OOM incident can—and cannot—tell you
A GitHub issue opened on January 19, 2022 describes one user’s Ubuntu 20.04 and OBS Studio 27.1.3 24/7 setup. The user reported rising RAM use and an OOM kill, in a configuration involving plugins, browser sources, and RTMP streaming to an internal server: OBS Studio issue #5987. It is an anecdote about that setup, not confirmation of a general OBS defect and not evidence about which process stopped your stream.
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