Percona is happy to announce the general availability of [pg_stat_monitor](https://github.com/percona/pg_stat_monitor).
Pg_stat_monitor provides a deeper and richer set of query analytics than has been available before. In addition to several additional metrics on previously run queries pg_stat_monitor introduces the ability to store query metrics in time series buckets as well as store metadata like explain plans from previous iterations of the queries. **Key features:** * End-to-end traceability: Allowing you to track query times and statistics across the various steps within a queries execution. * Aggregated stats across configurable time windows: Query statistics are aggregated in time series buckets across a variety of dimensions to give finer grain control. * Histogram of query execution time: Track and visualize query execution variability to gain better insight. **Other Features include:** * Multi-Dimensional Grouping: Groups counters by userid, dbid, queryid, client_ip, and planid for higher precision. This allows a user to drill down into the performance of queries on a more granular level. * Capture Actual Parameters in the Queries: pg_stat_monitor allows you to choose if you want to see queries with placeholders for parameters or actual parameter data. This simplifies debugging and analysis processes by enabling users to execute the same query. * Query Plan: Each SQL is now accompanied by its actual plan that was constructed for its execution. That’s a huge advantage if you want to understand why a particular query is slower than expected. * Tables Access Statistics for a Statement: This allows us to easily identify all queries that accessed a given table. You can read more about the features in our release [blog](https://www.percona.com/blog/understand-your-postgresql-workloads-better-with-pg_stat_monitor/).
