This page covers log files uploaded as complete files. Logs streamed live from the desktop app’s
Tool Log Streamer integration are processed differently. See Live Tool Logs From the
Desktop App.
Anomaly detection must be enabled for your deployment and configured for your organization.
When it is not enabled, parsing and signal analysis can still run, but anomaly scores,
classifications, and forecasts described below are not generated. Contact
Atomscale support about availability.
- Overview
- Technical
What It Does
The tool state pipeline takes raw log files uploaded from an instrument and produces structured timeseries that you can plot, compare across runs, and monitor for anomalies. The pipeline handles format parsing, data cleaning, signal analysis, and, where enabled and configured, anomaly detection.Supported Formats
The pipeline supports three input formats:Outputs
For tool logs, the pipeline produces the following outputs. Anomaly-related outputs are conditional on detection being enabled and configured:For generic CSV files, the pipeline produces a timeseries for each numeric column in the file, plus anomaly detection metrics where enabled and configured.
Live Tool Logs From the Desktop App
The Tool Log Streamer integration watches a folder on your tool’s control computer and streams each log file to Atomscale while the tool is still writing it. Streamed logs do not use the pipelines described above:
Atomscale keeps the original bytes of each streamed file, so the raw log is preserved even if some rows fail to parse. For help writing a parsing schema for your tool’s logs, contact support@atomscale.ai.