Investigate SQL Server WRITELOG Waits

Compare `WRITELOG` waits with log-file latency and transaction volume. Use moon to monitor changing write pressure continuously.

2026-09-08 · 2 min read

Why this problem matters

WRITELOG indicates waiting for log records to be hardened to stable storage. Elevated waits can stem from log-storage latency, very frequent commits, or high log-generation volume.

How to diagnose it

Inspect write count and cumulative write stall for log files by database. Correlate the result with transaction rate, commit pattern, and wait deltas from the same interval.

The query reads cumulative write counters for log files and changes no setting. Sound interpretation requires deltas between two samples and transaction volume for the same period.

SELECT DB_NAME(vfs.database_id) AS database_name,
       mf.name AS log_file_name,
       vfs.num_of_writes,
       vfs.io_stall_write_ms,
       CASE WHEN vfs.num_of_writes = 0 THEN NULL
            ELSE 1.0 * vfs.io_stall_write_ms / vfs.num_of_writes END AS avg_write_stall_ms,
       vfs.num_of_bytes_written
FROM sys.dm_io_virtual_file_stats(NULL, NULL) AS vfs
JOIN sys.master_files AS mf
  ON mf.database_id = vfs.database_id
 AND mf.file_id = vfs.file_id
WHERE mf.type_desc = 'LOG'
ORDER BY avg_write_stall_ms DESC;

A safe solution approach

Reducing unnecessary tiny transactions without changing application semantics and validating log storage are possible improvements. Durability options must not be changed without understanding their data-loss implications.

Why continuous monitoring matters

Log latency may become visible only during commit-heavy periods and disappear inside cumulative averages. moon can track short- and long-term trends and route alerts through Slack, PagerDuty, or webhooks.

Frequently asked questions

Does WRITELOG come only from slow storage? Does enlarging the log always reduce the wait?

No, commit frequency and log-generation volume can also be important. Pre-sizing may reduce growth events, but it does not by itself fix steady write latency.

How does moon help with this problem?

moon continuously observes SQL Server, PostgreSQL, and MongoDB signals, helping teams evaluate the problem as a trend instead of relying on a one-time check.