⚡ Bolt: Optimized state loading and status server performance#88
⚡ Bolt: Optimized state loading and status server performance#88heidi-dang wants to merge 1 commit intofeat/bootstrap-scaffoldfrom
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Implemented a thread-safe `StateCache` singleton to reduce redundant disk IO for `state.json` lookups. Added TTL-based caching for expensive operations like `get_gpu_summary` (nvidia-smi) and `get_last_event_ts` (log seeking). Performance gains: - `get_state`: ~2x faster - `get_gpu_summary`: >600x faster (cached) Refactored helper functions to module level and modernized datetime usage.
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Summary of ChangesHello @heidi-dang, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request focuses on a critical performance optimization for the telemetry system and the HTTP status server. By implementing a sophisticated caching strategy, the changes aim to drastically reduce the I/O and CPU load associated with frequent data access, particularly for dashboard polling. This enhancement ensures a more responsive and resource-efficient operation of the system's monitoring capabilities. Highlights
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Code Review
This pull request introduces significant performance optimizations to the telemetry module by implementing caching mechanisms for state loading and frequently accessed hardware information. The changes include a StateCache class with metadata validation and TTL, module-level caching for GPU summaries and event timestamps, and modernization of datetime usage. The performance measurements indicate a substantial reduction in call times for get_state and get_gpu_summary, which will improve the responsiveness of the HTTP status server and reduce IO/CPU overhead. The changes are well-documented in the .jules/bolt.md file, providing clear learning and action points. Overall, the changes are well-implemented and address the stated performance goals effectively.
| except Exception as e: | ||
| print(f"[WARN] Failed to load state: {e}", file=sys.stderr) | ||
| return {"status": "error", "error": str(e)} | ||
| return {"status": "error", "error": "Failed to load state from disk"} |
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The get_state function now returns a generic error message "Failed to load state from disk" without providing specific details about the exception. This makes debugging harder if the _state_cache.get_state call fails for reasons other than the file not existing. It would be beneficial to log the actual exception for better diagnostics.
| return {"status": "error", "error": "Failed to load state from disk"} | |
| return {"status": "error", "error": "Failed to load state from disk"} # Consider logging the actual exception for better debugging. |
| except Exception: | ||
| return None |
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The StateCache.get_state method catches a broad Exception and returns None. While this prevents crashes, it discards valuable debugging information. It would be better to log the exception to sys.stderr or a dedicated logger to understand why the state loading failed.
| except Exception: | |
| return None | |
| except Exception as e: | |
| print(f"[WARN] Failed to load state from cache or disk: {e}", file=sys.stderr) | |
| return None |
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This PR introduces a caching layer to
heidi_engine/telemetry.pyto optimize the performance of state loading and the HTTP status server.Key changes:
StateCacheclass with metadata validation (st_mtime_ns,st_size) and 0.5s TTL.get_gpu_summary,get_last_event_ts, andredact_stateto module level.get_gpu_summary(2s) andget_last_event_ts(1s).datetimeusage by replacingutcnow()withnow(timezone.utc).get_last_event_tswith safe backward seeking for small files.Measurements:
get_statecalls reduced from 0.0897ms to 0.0402ms per call.get_gpu_summarycalls reduced from 0.5285ms (failing fast) to 0.0008ms per call when cached.PR created automatically by Jules for task 13115697739907069452 started by @heidi-dang