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High mysqld RAM usage is not automatically a leak. MySQL deliberately keeps data in the InnoDB buffer pool, reserves global caches, allocates buffers for each active connection and statement, and may retain Performance Schema memory until shutdown. The safe fix is to measure the VPS as a whole, identify which category is growing, then change one limit at a time.
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Start by comparing MySQL’s resident memory with total and available host memory, swap activity, OOM-killer events, and the memory used by your web server, application runtime, cache, backups, and monitoring agents. Only then decide whether to reduce innodb_buffer_pool_size, cap connection or temporary-table memory, adjust instrumentation, or add capacity.
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There are three different measurements that are often confused:
- Resident set size (RSS): pages of the
mysqldprocess currently resident in physical RAM. This is what competes directly with other VPS processes. - Configured capacity: memory MySQL could use, such as the configured InnoDB buffer pool,
max_connections, and per-session buffer limits. A high theoretical maximum may never be reached. - Host pressure: whether the VPS is short of reclaimable memory, actively swapping, or killing processes. A large RSS can be harmless when the host has ample available memory; a smaller process can be dangerous on a crowded VPS.
Linux may also report memory that is shared, mapped, cached by the allocator, or reserved for later use. Therefore, adding every MySQL variable does not produce an exact RSS prediction. Use the totals to find the dominant contributors and confirm the result under representative traffic.
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First response: check whether the VPS is under pressure
Run these checks before editing MySQL configuration. Save the output so you can compare it after each change.
- Record RAM and swap:
free -hNote total, used, available, and swap figures. “Available” is more useful than “free” for judging whether the kernel can satisfy new allocations. Any sustained swap-in or swap-out indicates pressure even if
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ps -o pid,ppid,rss,vsz,%mem,cmd -C mysqldRSS is shown in kilobytes by most
psimplementations. If MySQL runs in a service manager or container, also inspect the service or cgroup memory limit and current usage; a cgroup can trigger an out-of-memory event before the physical VPS is completely full. - Look for OOM kills:
journalctl -k | grep -i -E 'out of memory|oom|killed process'On systems without a persistent journal, inspect the kernel log with the distribution’s normal log tool. An OOM event identifies an immediate capacity problem, but it does not by itself prove that MySQL was the process that caused the buildup.
- List competing consumers:
Record memory used by Apache or another web server, PHP-FPM or other application workers, Redis, backup and compression jobs, monitoring agents, antivirus scanners, and replicas. A buffer pool that is acceptable on a database-only host may be unsafe when those services share the same VPS.
If available memory is healthy, swap is inactive, and there are no OOM events, do not reduce MySQL memory merely because a dashboard shows a large percentage. Continue to attribute the allocation first.
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Where mysqld memory goes
InnoDB buffer pool
The buffer pool caches table and index pages, reducing disk reads. The Oracle MySQL Reference Manual states: “Typically, a recommended innodb_buffer_pool_size value is 50 to 75 percent of system memory.” That is a starting range for a typical database host, not a promise for a shared VPS. The operating system, web stack, connection spikes, temporary tables, backups, and other daemons all need memory outside the pool.
A pool that is too large can push the host into swapping. A pool that is too small can cause page churn and more disk I/O. The correct value is the largest setting that leaves reliable headroom during peak concurrency, not the largest percentage that fits at idle.
Global buffers and caches
Other process-wide consumers include innodb_log_buffer_size and, for installations using MyISAM, key_buffer_size. Their impact depends on the storage engines and workload. SHOW ENGINE INNODB STATUSG provides buffer-pool information that helps confirm whether the pool is actually the dominant consumer.
Per-connection and per-statement buffers
Every established session consumes connection memory. The connection and result buffers start at net_buffer_length and can grow as needed up to max_allowed_packet. Each session also receives max_digest_length bytes for statement digests. Sort, join, read, and read-random buffers can be allocated per operation or per session, depending on the operation and release.
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Internal temporary tables
Queries that need an internal temporary table can consume RAM up to the applicable limits, including tmp_table_size and max_heap_table_size. Large sorts, grouping, or joins may therefore create short-lived peaks even when the baseline process size is unchanged. Lowering these limits can force oversized results to disk, protecting RAM at the cost of I/O and potentially higher latency. The durable fix is usually to improve the query or add an appropriate index after identifying the workload.
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Performance Schema
Performance Schema may allocate memory at startup and while the server runs. It does not free that memory during normal operation; it releases it when the server shuts down. Autoscaled buffers can be capped with the relevant sizing parameters. A growing Performance Schema category is not automatically a leak, but unexplained, continuing growth after instrumentation is accounted for deserves investigation.
Capture the configuration and real concurrency
Run the following query to record the settings most relevant to memory:
SHOW VARIABLES WHERE Variable_name IN (
'innodb_buffer_pool_size',
'innodb_log_buffer_size',
'max_connections',
'max_allowed_packet',
'net_buffer_length',
'sort_buffer_size',
'join_buffer_size',
'read_buffer_size',
'read_rnd_buffer_size',
'tmp_table_size',
'max_heap_table_size',
'performance_schema'
);Then capture current and historical connection pressure:
SHOW GLOBAL STATUS WHERE Variable_name IN (
'Threads_connected',
'Threads_running',
'Max_used_connections'
);Threads_connectedis the number of currently open sessions.Threads_runningis the number actively executing at the instant of the sample.Max_used_connectionsrecords the highest simultaneous connection count since the server started or the status was reset.
Take several samples during a busy period. A configured max_connections far above observed peaks is a candidate for reduction, but first verify the connection-pool settings and whether short-lived jobs create bursts that your sample missed.
Attribute memory with Performance Schema
If Performance Schema is enabled, use it to identify the code area rather than guessing from RSS. Check the memory/% instruments in performance_schema.setup_instruments, enabling the appropriate instruments according to the manual for your MySQL release. Then query the memory summary tables, including:
SELECT EVENT_NAME, CURRENT_NUMBER_OF_BYTES_USED,
HIGH_NUMBER_OF_BYTES_USED
FROM performance_schema.memory_summary_global_by_event_name
WHERE EVENT_NAME LIKE 'memory/%'
ORDER BY CURRENT_NUMBER_OF_BYTES_USED DESC;Account and thread summary tables can show whether a particular user, connection, or workload is responsible. Instrumented totals will not exactly equal process RSS: allocator metadata, thread stacks, shared libraries, and uninstrumented areas account for the difference. Treat the result as attribution, not as an exact replacement for the operating-system measurement.
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Do not disable Performance Schema blindly. If it identifies a category that grows with a particular workload, investigate that workload or cap the relevant autoscaled sizing parameter. A restart releases Performance Schema memory as containment, but a recurring pattern still requires finding the cause.
Inspect InnoDB before changing its size
Run:
SHOW ENGINE INNODB STATUSGReview the buffer-pool section and compare it with the configured innodb_buffer_pool_size. If the pool consumes most of the VPS and application services are competing for RAM, reduce it in a controlled step rather than cutting it to an arbitrary fraction.
MySQL supports dynamic configuration for some settings, but exact behavior, resize mechanics, and minimums vary by installed release and distribution. Confirm the behavior for your version, schedule changes during a quiet period, and monitor the resize operation. If a setting requires a restart, edit the persistent configuration and plan the outage; do not assume a running-session change will survive a reboot.
Reduce the largest avoidable consumers
1. Resize the buffer pool with headroom
- Establish the VPS’s peak available memory while all non-MySQL services are active.
- Estimate the memory needed for connection bursts, temporary tables, the operating system, and filesystem cache.
- If the buffer pool is the dominant consumer, lower it by a modest, documented step.
- Recheck available memory, swap activity, query latency, buffer-pool hit behavior, and disk I/O during representative load.
- Keep the change only if the VPS gains safe headroom without unacceptable query degradation.
For example, on a small shared VPS, applying the 50–75% guidance to total RAM without reserving memory for PHP workers or backups can still cause swapping. The percentage is a reference point, not permission to allocate every remaining gigabyte to InnoDB.
2. Set a defensible connection ceiling
Compare Max_used_connections with max_connections and the application’s pool limits. If the ceiling is unjustifiably high, lower it in a staged change and ensure the application handles a refused connection gracefully. A lower limit protects the whole VPS from a connection storm, but an excessively low value can cause application errors. Fix connection leaks and right-size pools rather than using a large ceiling to hide them.
3. Keep session buffers proportional to the workload
Review max_allowed_packet, sort_buffer_size, join_buffer_size, read_buffer_size, and read_rnd_buffer_size. These values can multiply across concurrent sessions or operations. Set them for queries you actually run, not for a theoretical maximum. Raising all of them globally is a common way to turn a modest connection spike into an OOM event.
If only one reporting query needs a larger packet or sort area, prefer a targeted session setting or a query/index improvement when supported by your application. Test large imports and legitimate long rows before lowering max_allowed_packet; otherwise, clients may receive packet-size errors.
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If memory summaries, status counters, or query inspection point to internal temporary tables, lower tmp_table_size and max_heap_table_size together so oversized results spill to disk consistently. Monitor temporary-table disk activity and latency immediately afterward. Then identify the queries creating the tables and address avoidable sorting, grouping, or missing indexes. This change protects RAM but deliberately trades memory pressure for storage I/O.
5. Manage Performance Schema deliberately
Use the memory instruments to find the category first. Cap autoscaled buffers only when you understand what data or resolution you are giving up. Keep enough instrumentation to diagnose future incidents. Restarting the service can reclaim retained Performance Schema allocations, but schedule that as maintenance and treat it as containment rather than a permanent fix.
Compare the available remedies
| Remedy | Peak-memory effect | Likely trade-off | Restart requirement | Protects |
|---|---|---|---|---|
Reduce innodb_buffer_pool_size |
Large reduction when the pool dominates | More disk reads and possible query latency | Release-dependent; verify before changing | Whole VPS, by leaving room outside MySQL |
Lower max_connections |
Limits connection-storm peaks | Connection failures if set below real bursts | Release- and configuration-dependent | Whole VPS |
| Lower per-session buffers | Reduces multiplied session allocations | Some sorts, joins, or large results may slow or fail | Often configuration-dependent | Whole VPS during concurrency spikes |
| Lower temporary-table limits | Constrains in-memory query spikes | More temporary files and I/O | Configuration-dependent | Whole VPS |
| Adjust Performance Schema sizing | Controls instrumented growth | Less retained diagnostic capacity | Some limits take effect only at startup | MySQL’s instrumentation footprint |
| Restart MySQL | Releases memory retained until shutdown | Downtime and recurrence if the cause remains | Yes | MySQL process temporarily |
| Increase VPS RAM or move to managed MySQL | Adds capacity without shrinking caches | Higher cost or migration/operational changes | Provider- or migration-dependent | Whole deployment |
Choose based on the measured allocation mix. Resizing the VPS does not cure a runaway workload, while aggressive MySQL limits can merely shift the problem into disk I/O or application errors.
Validate every change and keep a rollback path
After each single change, observe at least one representative busy period. Record:
- Available RAM and swap-in/swap-out activity from the operating system.
mysqldRSS and the VPS or cgroup memory limit.- OOM-killer or service-restart events.
Threads_connected,Threads_running, andMax_used_connections.- Query latency, error rates, connection failures, temporary-table disk activity, and application timeouts.
- InnoDB buffer-pool behavior and disk I/O after any pool reduction.
Write down the old value before editing persistent configuration. If latency or errors worsen, restore that value, apply the required reload or restart, and investigate the workload before trying another change. Avoid changing several global limits at once; otherwise you cannot tell which trade-off caused the result.
When tuning is not enough
If measured settings are reasonable, the VPS still swaps or records OOM kills, and application services cannot be reduced, the host is undersized for the workload. Add RAM or move MySQL to a managed service with an appropriate memory tier. Persistent unexplained growth after Performance Schema and OS attribution warrants investigation for a workload or software defect; a restart may provide temporary relief, but recurring growth should not be accepted as normal operation.
A practical order of operations
- Measure total and available RAM, swap,
mysqldRSS, cgroup limits, and OOM events. - Record competing services and capture MySQL variables and connection-status counters.
- Attribute memory with Performance Schema and inspect
SHOW ENGINE INNODB STATUSG. - Reduce an oversized buffer pool only after reserving host and application headroom.
- Right-size
max_connectionsand per-session buffers against observed concurrency. - Constrain temporary-table memory when evidence points to internal temporary tables, then fix the generating queries.
- Review Performance Schema sizing without disabling useful instrumentation blindly.
- Validate under representative load; if safe settings still leave no margin, add capacity.
The goal is not the smallest possible mysqld process. It is a stable VPS with enough memory for MySQL, the operating system, and every service that must run beside it.
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