Correlations produces root cause insights almost immediately — aggregating and analyzing thousands of traces in seconds — to identify which signals best explain the regression in your service.
With unlimited cardinality and a high-fidelity dataset uncompromised by head or tail sampling, Correlations reveals issues unavailable to conventional monitoring solutions. This includes extreme outliers, low-frequency events, and performance issues related to any specific tag, trace, service, geography, release version, operation, or individual customer.
Leveraging the complete end-to-end traces produced by LightStep’s unique satellite architecture, Correlations not only surfaces likely root causes, it provides evidence to support those conclusions.
As soon as a non-performant signal is identified, LightStep provides immediate access to the exact spans, traces, and tags related to that signal — all of which can be shared with your team via Snapshots.
When you’re trying to rapidly restore service — and time is of the essence — how do you separate good hypotheses from bad ones?
By revealing the relationship between system attributes and performance, Correlations immediately rules out signals (and related hypotheses) that are not along the critical path.
This allows you to focus on work that is likely to restore service, while simultaneously eliminating unnecessary disruption to teams who are not needed for incident resolution, but might otherwise have been involved.