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🧠 Docket Technical Changelog

May 2026

  • Universal modules. One module is reusable across every browser viewport, iOS device, and Android device. The viewport_width, viewport_height, browser_zoom, device_type, and device_name fields have been removed from the module API.
  • Per-config step caches. Recorded and self-healed steps stay sharp on every device / viewport / zoom they’ve been run against. list-modules adds a config_key query param to scope what’s returned.
  • New Start Screen launcher. The Start Screen button now opens a device picker grouped by platform with per-resolution entries and inline mobile app selection. Defaults follow the test you’re viewing.
  • Screen Out of Sync overlay. When the running worker drifts from the test’s config, the stream shows an overlay listing the specific drifts and a single Restart Screen button. Run and Record are disabled until they match.

October 2025

  • Optimized AWS + Porter cluster configuration, cutting average browser-worker CPU/memory usage by ~22%.
  • Tuned pre-check confidence threshold and CPU allocation logic per site for more stable agent runs.
  • Added automatic weekly dependency vulnerability scans in CI/CD pipeline.
  • Improved S3 object storage configuration with versioning + Object Lock for data integrity.
  • Refactored internal monitoring to surface agent latency, memory, and timeout metrics in dashboard.

September 2025

  • Enhanced self-healing agent behavior for broken selectors, delayed elements, and network retries.
  • Introduced usage analytics pipeline capturing test latency, pass/fail counts, and error codes.
  • Benchmarked and tuned Playwright concurrency profiles across different CPU classes to reduce cold-start time.

August 2025

  • Deployed full AWS + Porter environment with staging + production clusters and load-balanced worker pool.
  • Launched new vision model for Docket
  • Introduced system health dashboard showing session errors, retries, and agent restarts.
  • Improved Docker image build flow — reduced image size and deployment time by >30%.