Xata Agent realizes accurate diagnosis by analyzing multi-dimensional indicators, mainly detecting the following key dimensions:
- Performance benchmarking indicators: Includes hardware resource usage such as CPU utilization, memory consumption, disk I/O throughput, etc.
- Query Performance: By
pg_stat_statementsCapture slow executing SQL statements (default threshold 2 seconds) and analyze their execution plan and resource consumption - Concurrent control: Monitor concurrency-related metrics such as lock wait times, deadlock counts, current active connections, etc.
- Parameter Configuration Rationality: Inspection
shared_buffers、work_memWhether key parameters, such as whether it matches the hardware configuration
The diagnostic process usesRead-only SQL commandsCollecting data, such as checkingpg_locksView analysis lock contention, querypg_stat_activityUnderstand session status. All analysis results are combined with contextual suggestions generated by the AI model to form a complete report of "Problem Phenomenon → Root Cause → Solution".
This answer comes from the articleXata Agent: An AI Assistant for Monitoring and Optimizing PostgreSQL Databases》
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