このページは日本語には対応しておりません。随時翻訳に取り組んでいます。
翻訳に関してご質問やご意見ございましたら、
お気軽にご連絡ください。
Database Monitoring (DBM) Recommendations draw attention to potential optimizations and problematic areas across your database fleet.
Datadog analyzes metrics and sample data from DBM to identify your systems’ highest-priority issues. A severity indicator is calculated for each recommendation, highlighting the most impactful areas to focus on. High-severity recommendations may indicate immediate or impending problems, while lower-severity recommendations can be addressed asynchronously to proactively maintain database health.
| Recommendation Type | Description | MongoDB | MySQL | Oracle | PostgreSQL | SQL Server |
|---|
| Function in Filter | The query calls a function on columns being filtered, leading to expensive sequential scans that can’t take advantage of typical column-based indexes. | | | | | |
| High Impact Blocker | The query is causing a significant amount of waiting time for blocked queries. | | | | | |
| High Row Count | The query returns a large number of rows in its result set. | | | | | |
| Long Running Query | The query has durations that have exceeded a threshold of 30 seconds. | | | | | |
| Low Disk Space | The database instance is running low on disk space.
Note: Only available on Amazon RDS. | | | | | |
| Missing Index | The query’s execution plan performs expensive sequential scans. When detected, Datadog recommends using an index to expedite the query. | | | | | |
| Unused Index | The index has not been used in any execution plans recently. | | | | | |
