Phantom Trace: an offline AI that finds the ghosts in your CI/CD logs

说明与用途

Phantom Trace 是一个本地工具，通过语义嵌入模型对 CI/CD 日志进行聚类，识别重复错误并显示原始日志行。

问题

Recurring CI/CD failures often reappear with different wording, making them hard to detect and prioritize.

结果

In a sample run of nine fictional events, Phantom Trace produced three recurring clusters (sizes 3,3,2) and one isolated event, matching the intended pattern.

工作流

• Paste timestamped CI/CD events into the local UI
• Phantom Trace converts each message to a semantic vector using all-MiniLM-L6-v2 via ONNX Runtime
• Vectors are mean‑pooled and L2‑normalised; cosine similarity is computed
• Pairs exceeding a threshold (default 0.55) are connected; connected components form incident clusters
• The medoid event of each cluster is chosen as the title; all supporting log lines are shown
• Users can adjust the similarity threshold with a slider to refine clustering

证据

Phantom Trace is an offline incident‑archaeology tool for CI/CD teams. It uses an open‑weight sentence‑transformer to connect historical failures that mean the same thing even when their exact wording changes, then shows every source event behind each cluster.

来源

The default threshold was 0.72. The UI looked polished, but a real model integration run exposed a problem: it found only one of the three intended recurring families. At 0.55, the model produced the intended 3, 3, 2, 1 cluster sizes.

来源