Chunk 9.0

This chunk focused on transforming the vast-manager from a basic monitoring tool into a comprehensive deployment and management platform with a polished user interface. The major UI overhaul added a fully interactive **Offers panel**, allowing users to search, filter, and sort Vast.ai GPU instances with color-coded visual indicators for hardware quality (GPU generation, CPU architecture, RAM, PCIe bandwidth, and network speed). The deployment workflow was refined with a dynamic `min_rate` calculation derived from instance cost (`dph_total / $0.008`), ensuring cost-efficiency is enforced automatically. Additional UX enhancements included an "Ignore" button to blacklist hosts, a clickable "BAD" badge to undo the mark, and a "loading" state to show instances that exist in the Vast cache but haven't yet contacted the manager. Significant improvements were made to instance lifecycle management and data persistence. The critical issue of **lost metadata on killed instances** was solved by adding 12 new columns to the SQLite `instances` table and persisting vast cache data (GPU, location, SSH command, cost) during the monitor cycle. The dashboard now falls back to this stored data when instances are destroyed, and killed instance retention was extended from 24 hours to 7 days. A critical operational bug was also identified and fixed: the `portavailc` tunnel on worker instances was not forwarding port 1234 (hosting the Lotus API), causing `curio` to fail at startup—the entrypoint script was updated to include this port. Throughout this chunk, the vast-manager binary was iteratively rebuilt, deployed, and verified on the controller host (10.1.2.104), and the Docker image was rebuilt to include the entrypoint fixes. The result is a robust, self-tuning system that can automatically discover, deploy, monitor, and manage proving workers based on real-world performance data, with full visibility into the deployment pipeline and persistent historical records.

From Monitor to Platform: The Vast-Manager Transformation 3315 words

Message Articles