What's New in postgres-checkup 1.1 "Young Owl"

New Features and Improvements

  • New CLI options: --html, --pdf to get reports in HTML (static) and PDF, respectively.
  • New CLI option: --list-limit to limit rows in tables in markdown (as well as HTML and PDF) reports. It does not affect JSON reports (!298, !308).
  • Official Docker images (https://gitlab.com/postgres-ai/postgres-checkup/container_registry) to run postgres-checkup from a Docker container (contribution by @binakot 👍, !274, !318).
  • [Experimental] Sections "Conclusions" and "Recommendations" are now automatically filled for the following reports (!297, #379, !317):
    • A002 Version information;
    • A008 Disk usage and file system type;
    • F002 Transaction ID wraparound check;
    • F004 Autovacuum: Heap Bloat (Estimated);
    • F005 Autovacuum: Index bloat (Estimated).
  • Table formats are reworked in reports "F004 Autovacuum: Heap Bloat (Estimated)" and "F005 Autovacuum: Index bloat (Estimated)" to be more informative and unified (https://gitlab.com/postgres-ai/postgres-checkup/issues/360).
  • Report "A004 Cluster information" reworked: all nodes are presented in a single table (https://gitlab.com/postgres-ai/postgres-checkup/issues/360).
  • "G002 Connection and Current Activity": new columns "tx age >1m" and "tx age >1h" (#350).
  • "H002 Unused and Redundant Indexes": performance improved (!288).
  • "No data" renamed to "Nothing found" in all templates (!304).

Bugfixes

Limitations

  • no binaries for now, Go part is to be compiled;
  • reports are partially automated: only "Observations" sections; "Conclusions" and "Recommendations" are generated only for selected reports, for other reports they are to be completed by an expert;
  • reports in K group (Query Analysis) work only with the last two snapshots;
  • there is no integration with cloud APIs yet: "infrastructure" reports are generated only for on-premise Linux setups, where ssh is available; SQL-level reports can work with any cloud setups such as Amazon RDS, Google Cloud SQL, Azure.

Useful Links