PgAssistant

Features Introduced SQL Advisor, a new safe-by-design advisor focused on SQL query analysis and guidance. It is designed to provide helpful recommendations while staying conservative and avoiding risky automated actions. Improved Top queries are now displayed as cards, making them easier to scan, compare, and review visually. New docker image is available on dockerhub Take a look at DockerHub image tag docker pull bertrand73/pgassistant:latest Enjoy ! Docker image security advices No any security advice from github or docker scouts or Grype. ...

Features UI improvement of tables, minor changes of icons, colors and sizes Bug fixes UI : issues with text and icons alignment in Dashboard, generic header and left menu New docker image is available on dockerhub Take a look at DockerHub image tag docker pull bertrand73/pgassistant:latest Enjoy ! Docker image security advices No any security advice from github or docker scouts or Grype.

UI UX Many changes on UI UX - Sidebar menu refactoring, new color schema. Postgresql 18 Postgresql 18 top queries : adjust column orders New docker image is available on dockerhub Take a look at DockerHub image tag docker pull bertrand73/pgassistant:latest Enjoy ! Docker image security advices No any security advice from github or docker scouts or Grype.

Code Suggestions Section When pgAssistant generates recommendations, the form now includes a dedicated “Code suggestions” section grouping all actionable statements. A convenient “Copy” button lets users export them instantly. (Thank you Manon for the great idea!) Bgwriter & Checkpointer Insights The reporting API now exposes pg_stat_bgwriter (and pg_stat_checkpointer for PG17+) metrics along with detailed recommendations to improve checkpoint and background writer performance. Database Uptime on Dashboard The main dashboard now displays the database uptime, with a clean human-readable format. ...

I’m excited to announce the release of pgAssistant 2.0, a major milestone for the project. This new version marks a strategic shift toward API-first integration, making it easier to embed pgAssistant into existing workflows — from code review pipelines to production compliance checks. The first available API in this release focuses on automated database health reporting. It generates a Markdown report that provides : • A global health overview of your PostgreSQL database • Key performance and metrics • Identified issues and improvement suggestions Since its beginning, pgAssistant’s mission has been to help developers design better, faster, and more maintainable databases — while also providing educational insights, references, and explanations for every metric. ...

This release is coming with this a new AI feature : Use AI to verify table compliance with your SQL guide lines (like naming conventions) - Just provide a valid URL to your guidelines. It is strongly recommanded to use the Markdown format for SQL guide lines. This new functionnality is added on the Table definition helper menu. Enjoy ! New docker image is available on dockerhub Take a look at DockerHub image tag ...

This release is coming with this news features : pgTune : docker-compose yaml file is using a healthcheck and the shm_size parameter pgTune : a Kubernetes deployment descriptor has been added New docker image is available on dockerhub Take a look at DockerHub image tag docker pull bertrand73/pgassistant:1.9.8 Enjoy ! Docker image security advices No any security advice from github or docker scouts or Grype.

This release is coming with this news features : Re-factoring LLM API Calls to detect the use of ollama. Tested with the lastest ollama version With Lighthouse, optimize the UI Re-factoring the LLM settings form New docker image is available on dockerhub Take a look at DockerHub image tag docker pull bertrand73/pgassistant:1.9.7 Enjoy ! Docker image security advices No any security advice from github or docker scouts or Grype.

Following the release of OpenAI’s open-source model gpt-oss, I set out to benchmark its performance in conjunction with PostgreSQL, focusing specifically on integration with pgAssistant. All evaluations were conducted locally on a MacBook Pro M4 Pro (24 GB RAM), using Ollama as the model runtime environment. gpt-oss installation To install this new model, first download the latest version of ollama, then run this : ollama pull gpt-oss:20b Ollama should now serve the API at: http://localhost:11434 ...