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Random MySQL restarts on a small VPS are usually a resource event, not a setting to guess at. Correlate the restart timestamp with MySQL’s error log and the kernel log first. If the Linux OOM killer terminated mysqld, reduce total memory demand or move to a larger VPS; if there is no OOM evidence, investigate disk space, file descriptors, service-manager limits, and any query that consistently appears immediately before the failure.
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Start with evidence, not configuration changes
A restart that looks random is only random until its timestamp is compared with the logs. Changing innodb_buffer_pool_size before identifying the failure mode can hide the symptom, worsen swapping, or leave the actual cause untouched.
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Record the exact outage time
Use your monitoring alert, application log, or user report to establish when connections began failing and when they recovered. Record the timezone and whether the outage was a single restart or a repeating cycle. A one-second difference between the application timestamp and the kernel timestamp can matter when several services are active.
Check MySQL and the operating system together
MySQL’s troubleshooting guidance is to inspect both the server error log and the system log, while checking memory, disk space, and file descriptors with operating-system tools. Look at the final entries before the restart, the first entries after startup, and any stack trace or recovery message.
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Run the initial checks as the account that can inspect service and kernel information:
free -h
swapon --show
df -h
systemctl status mysql
journalctl -k -b | grep -i -E 'oom|out of memory|killed process'The commands provide a snapshot; the logs provide the explanation. Save the output and the relevant log interval before restarting again, because a later restart can overwrite the context you need.
Determine whether mysqld was killed by Linux
An out-of-memory condition occurs when a process cannot obtain memory because the server has none available. Linux can respond by invoking the OOM killer, which terminates a process with SIGKILL. A SIGKILL cannot be caught or handled by MySQL, so normal shutdown cleanup does not run.
What an OOM signature looks like
- The kernel journal contains terms such as
out of memory,oom, orkilled process, often namingmysqld. - The MySQL error log ends abruptly rather than recording a normal shutdown sequence.
- The service manager reports that MySQL stopped and then started again, or shows a restart count.
- Applications see dropped connections and in-flight transactions fail at the same moment.
Do not infer OOM solely from a restart. A service manager can restart a process after another failure, and a health check can report an outage while the database is still running. The kernel evidence and the MySQL error log must agree on timing.
Read memory and swap as operating conditions
free -h shows available RAM and swap totals, while swapon --show confirms which swap devices or files are active. Swap can prevent an immediate kill during a short-lived allocation spike, but sustained swapping is a capacity warning: latency can become extreme even when the process remains alive. A machine that is constantly swapping does not have a healthy memory margin.
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Rule out disk and file-descriptor exhaustion
MySQL can fail without an OOM event. Check df -h for a full filesystem, especially the volume holding the data directory, binary logs, relay logs, temporary files, and MySQL error log. A full filesystem can prevent writes, table creation, log rotation, or recovery work.
Inspect the error log for messages indicating that a filesystem is full or that the process cannot open another file. File-descriptor exhaustion is distinct from RAM exhaustion; lowering the buffer pool will not repair it. Correct log and temporary-file retention, free space, or expand the affected volume before changing memory settings.
Likewise, confirm that the service manager is not imposing a limit that is smaller than the VPS capacity. If systemd constrains the unit, inspect the unit definition and its drop-in override. MySQL documents that some limits belong in an override.conf rather than only in a MySQL option group. A limit applied by systemd can make the database fail even when the host still appears to have free memory.
Build a realistic MySQL memory budget
innodb_buffer_pool_size is the largest familiar allocation, but it is not MySQL’s entire footprint. A useful budget includes:
- The InnoDB buffer pool.
- Per-thread connection buffers multiplied by simultaneously active sessions.
- Temporary-table memory and other feature-specific buffers.
- Replication-related allocations when replication is enabled.
- MySQL process overhead and memory used by plugins or enabled features.
- The operating system, PHP or other application workers, web servers, monitoring agents, and backup processes.
- Kernel memory and a safety margin for short-lived spikes.
Conceptually, the limit is:
total demand = buffer pool
+ (per-session allocations × concurrent sessions)
+ temporary and feature allocations
+ MySQL overhead
+ operating-system and application demand
+ spike headroomThe multiplication by concurrent sessions is why a server can survive at idle and then be killed during a traffic burst. A configured connection limit is not the same as actual concurrency, but it defines how large the worst case can become.
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What the official buffer-pool guidance means on a small VPS
MySQL states that its default configuration is designed to let the server start on a virtual machine with approximately 512 MB of RAM. It also describes 50 to 75 percent of system memory as a typical recommendation. That range assumes the rest of the machine has been accounted for; it is not a rule to apply blindly to a shared VPS.
On a 1 GB VPS, 50 to 75 percent would reserve roughly 512 to 768 MB for the buffer pool and leave only about 512 to 256 MB for the operating system, application workers, connection allocations, temporary tables, and monitoring. If the VPS also runs a web stack, the upper end can leave no useful burst margin. The correct value is the largest pool that still leaves measured headroom for every other workload, not the largest percentage that fits on paper.
Change one contributor at a time
Record the active values of innodb_buffer_pool_size, connection limits, and temporary-table settings before editing anything. Lower the largest contributor first, then restart during a maintenance window. Changing several variables at once prevents you from knowing which change affected memory use or query latency.
Do not assume that a lower buffer pool is always an improvement. It reduces resident memory pressure but can increase disk reads, query latency, and I/O contention. The objective is a stable aggregate footprint with acceptable performance, not the smallest possible pool.
Use swap as a safety margin, not as extra RAM
Swap is useful for absorbing a brief allocation spike that would otherwise trigger an immediate OOM decision. It does not increase sustainable database capacity. When active pages move repeatedly between RAM and disk, MySQL can become so slow that the application times out even though no process is killed.
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Confirm swap with swapon --show and observe whether it is merely present or continuously busy. If the VPS has no swap, adding appropriately sized swap may reduce the chance of a short spike causing an abrupt kill, provided the storage and provider policy make that suitable. If swapping remains persistent after memory tuning, treat it as evidence that the workload needs more physical RAM or fewer competing services.
Follow a controlled tuning runbook
- Capture a baseline. Save
free -h,swapon --show,df -h,systemctl status mysql, the kernel journal output, and the MySQL error-log interval surrounding the restart. - Classify the event. Mark it as OOM, disk or file-descriptor exhaustion, a repeatable query, InnoDB recovery, or an event with no established cause. Do not combine categories just because they occurred near the same time.
- List competing memory users. Include application workers, web services, monitoring, backups, and any scheduled job that runs during the crash window.
- Record active MySQL settings. At minimum, document the buffer pool, connection limits, and temporary-table settings. Include replication-related settings when applicable.
- Apply one conservative change. Lower the largest memory contributor, stop or resize a competing service, or correct the non-memory resource identified in the logs. If systemd imposes a limit, address the unit or drop-in rather than editing an unrelated MySQL option.
- Restart deliberately. Use a maintenance window, verify that the service comes up cleanly, and preserve the new startup log.
- Observe under representative load. Watch memory, swap behavior, latency, and the error log for the period that normally contains the failure. A single successful restart is not proof of a fix.
- Reassess the budget. If the OOM signature disappears but latency becomes unacceptable, the pool may now be too small. If OOM continues, reduce aggregate demand further or move to a larger-memory VPS.
Find out whether a query is causing the crash
MySQL recommends examining the error log for the last event before a restart. If the same statement, table operation, or workload pattern repeatedly appears immediately before death, treat it as a candidate rather than a proven cause.
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Reproduce under controlled logging
- Use the timestamps to identify the statement or request that precedes the failure.
- Enable an appropriate query log only for a controlled reproduction. Query logging can add I/O and overhead, which is especially significant on a small VPS.
- Isolate the statement, its parameters, transaction context, and concurrency level. A query that succeeds alone may fail when several sessions allocate temporary or per-thread memory simultaneously.
- Run the smallest reproducible test that still produces the failure, while preserving the MySQL error log and kernel log.
- Test the reproduction against a current supported MySQL release before filing a bug. Include the statement, schema, configuration values, version, error-log stack trace, and exact failure sequence.
A query log that merely shows activity before an OOM event does not establish that the SQL itself is defective. The query may have supplied the final allocation while an oversized buffer pool or another service consumed the available headroom.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Handle InnoDB recovery messages safely
If MySQL reports InnoDB recovery during startup, preserve the complete error log and follow the documented recovery-failure procedure. Recovery output is evidence about the previous termination and the state of the data files.
Do not delete InnoDB data files, redo logs, or system tablespace files to force startup. Destructive cleanup can turn a recoverable crash into data loss. First establish whether the previous stop was an OOM kill, a storage failure, or another abrupt termination, then apply the recovery procedure appropriate to that finding.
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Choose the remedy by the failure mode
| Remedy | Memory headroom | Throughput and latency | Swap or disk impact | Operational risk | Root cause addressed? |
|---|---|---|---|---|---|
Reduce innodb_buffer_pool_size |
Increases RAM available to the OS and other processes | Can increase reads and query latency if set too low | May reduce swapping; extra disk reads are possible | Requires a restart and post-change observation | Addresses an oversized persistent allocation |
| Reduce connection or per-session memory demand | Limits aggregate growth during concurrency spikes | May reject or delay clients when limits are reached | Can reduce temporary-table pressure | Application changes may be required | Addresses burst-driven memory use |
| Stop or resize competing services | Returns their allocation to the VPS budget | Database performance can improve; other workloads may lose capacity | Usually reduces swap activity | May affect application availability | Addresses contention outside MySQL |
| Add suitable swap | Provides a buffer for short spikes, not permanent capacity | Heavy use can make queries extremely slow | Moves pressure to storage | Lower immediate kill risk, but storage wear and latency must be considered | Only masks brief spikes; does not fix sustained demand |
| Free disk space or correct file retention | Does not change RAM | Restores writes, logging, and temporary-file operations | Directly resolves filesystem exhaustion | Deleting the wrong files can be dangerous; preserve required database files | Addresses disk exhaustion |
| Move to a larger-memory VPS | Provides durable physical headroom | Allows a larger working set and more concurrency | Can reduce swap dependence | Migration or resizing requires planning | Addresses a workload that exceeds the plan’s safe capacity |
Know when tuning is no longer enough
If the kernel continues to record OOM kills after you have reduced the major allocations and removed unnecessary competing services, the VPS does not have a safe memory margin for the workload. Repeatedly shrinking the buffer pool or relying on swap can trade crashes for unacceptable latency. A larger-memory service is the durable option when normal peak demand exceeds physical RAM.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Likewise, if the logs show disk or file-descriptor exhaustion, upgrading memory alone will not fix the outage. Correct retention, limits, or storage capacity first. If no resource signature exists and one query is reproducible, treat it as a software defect or compatibility problem: preserve the stack trace, test a supported release, and prepare a minimal reproduction.
How to prove the fix
Define the observation period before declaring success. It should include the traffic pattern, scheduled jobs, backups, and maintenance tasks that previously surrounded the restart. During that period, verify all of the following:
- No new kernel OOM or “killed process” entries appear.
- The MySQL error log shows clean operation rather than abrupt termination or repeated recovery.
- Swap is not continuously active.
- The filesystem containing MySQL data and logs retains usable free space.
- Connection failures, query latency, and application errors remain within the normal range.
- The service manager is not repeatedly restarting the unit.
Only stable operation over your own representative observation period demonstrates that the change solved the incident. A successful boot, an empty log immediately after a restart, or a temporary drop in memory use is not sufficient evidence.
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