pg_statviz 0.9 released with new features

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Happy New Year! I'm excited to announce release 0.9 of pg_statviz, the minimalist extension and utility pair for time series analysis and visualization of PostgreSQL internal statistics.

This is a significant feature release that expands the scope of analysis to include several new modules and a visualization update:

  • Configuration changes visualization: A major update providing a timeline view of PostgreSQL setting changes, allowing you to correlate performance shifts with configuration updates.
  • Session activity age tracking: The connection module now tracks oldest_xact_age, oldest_query_age, and oldest_backend_age, helping you quickly identify long-running transactions and idle connections that may be holding resources or preventing vacuum cleanup.
  • Replication statistics: A new module provides visibility into high-availability setups, tracking standby lag from pg_stat_replication and replication slot statistics from pg_stat_replication_slots.
  • SLRU cache statistics: New metrics for the Simple LRU buffer efficiency allow for better diagnosis of specific internal bottlenecks (like multixact or pg_xact contention).
  • Checksum failure tracking: Added tracking for checksum failures via pg_stat_database to assist in early detection of data corruption issues.

This release also includes important maintenance and optimizations:

  • Space optimization: snapshot_conf() has been optimized to only store configuration changes rather than saving values for every snapshot. The upgrade path automatically compacts existing duplicate configuration rows to reclaim space.
  • Dependency updates: A GitHub Actions CI pipeline has been added, dependencies have been updated to their latest stable versions, and argh has been pinned to <0.30 for CLI argument compatibility.

pg_statviz takes the view that everything should be light and minimal. Unlike commercial observability platforms, it doesn't require invasive agents or open connections to the database — it all lives inside your database. The extension is plain SQL and PL/pgSQL and doesn't require modules to be loaded, the visualization utility is separate and can be run from anywhere, and your data is free and easy to export.

  • You can download and install pg_statviz from the PostgreSQL repositories or PGXN.
  • The utility can also be installed from PyPi.
  • Manual installation is also possible.