A cluster is a grouping of similar findings, observations Bento pulled from your runs and bundled because they look alike. In the dashboard they’re the scatter view under Monitoring: each dot is a finding, and dots that sit close together form a cluster. TheDocumentation Index
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clusters group reads that view for the whole workspace.
Where an issue is one tracked problem you work and close, a cluster is the looser, zoomed-out picture: the shapes in your monitoring data before anyone has named them. Each cluster in the workspace view carries a label, a description, a member_count, a trend, and a few sample_quotes. The view returns only active clusters, the ones worth looking at.
Each member is a Finding, extracted from a Trajectory. A Signal is what turns a recurring cluster into a detector, and has its own clusters via signals list-clusters <signal-id>.
The commands
| Command | What it does |
|---|---|
clusters get-workspace | The workspace’s active clusters. Label, member count, trend, sample quotes. |
clusters get-scatter | The raw scatter-plot data. Every finding as a point, plus a center per cluster. |
--workspace and --output.
Read the scatter view
See the clusters, with labels, counts, and a few quotes each:centers gives the labeled middle of each cluster. Unclustered points carry a null cluster_id:
See also
Signals
The detectors a recurring cluster becomes.
Findings
The individual observations that make up each cluster.
Trajectories
The analyzed runs those findings come from.