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Give the anomaly detector its history: Soda anomaly detection needs at least 30 historic measurements for a metric, so let the check collect measurements over time, or seed the history from past scan results, before expecting anomaly verdicts. Use when a Soda Core anomaly detection check on a metric that is new or new…
Fixes the the anomaly detector settings failure "agent hallucinating seasonality period as 7 for hourly metric caused detector failure error" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outag…
Fixes the ADTK failure "AdtkModel requires a pandas DataFrame with DatetimeIndex" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors, which must be resolved first.
Vectle found the following relevant skills: - Kats detector failed error "detector model requires at least 30 data points" - forecasting model failed error "input DataFrame must have exactly two columns: ds and y"
Fixes the the seasonal detector failure "seasonal detector breaks after business switches to four day work week error" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors…
Fixes the the detector comparison failure "when agent tried to compare detectors side by side agent failed error mismatched time ranges" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or…
Fixes the the anomaly detector failure "anomaly alerts stop entirely after metric switched from sum to average aggregation error" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permis…
Vectle found the following relevant skills: - Chronos forecast failed error "prediction length exceeds context window" - context overflow when agent tried to diff full run artifacts and the diff failed with a length error
Vectle found the following relevant skills: - agent hallucinating threshold values error failed to use configured detector settings - Error: Invalid value for variable: input failed the variable validation block
Fixes the Prophet failure "Dataframe has less than 2 non-NaN rows" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors, which must be resolved first.
Fixes the the anomaly detector failure "baseline keeps absorbing recurring outage so real drop no longer alerts failure" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission erro…
Vectle found the following relevant skills: - Grafana status panel not reflecting incident: data source query failed error - Grafana dashboard variable query failed: label values error for Prometheus fix
Fixes the the LOF detector failure "n_neighbors must be greater than 0" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors, which must be resolved first.
Fixes the Kats failure "detector model requires at least 30 data points" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors, which must be resolved first.
Vectle found the following relevant skills: - Azure anomaly detector failed error "EntireSeriesNotMatched: series key not in training data" - detector training failed error "Not enough data points to train anomaly model"
Fixes the Datadog failure "anomalous: function requires at least 2 days of data" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors, which must be resolved first.