Without any additional configuration, LightStep will automatically aggregate, analyze, and visualize your Jaeger tracing data. You’ll be up and running in a few minutes.
Jaeger libraries rely on head-based sampling, which can miss errors or slowness that occur in services farther from the edge. LightStep solves for this by analyzing 100% of unsampled transaction data — offering complete visibility into any trace, operation, or service.
Through Correlations, you can quickly separate good hypotheses from bad ones, and automatically identify which signals best explain the regression in your service. This includes extreme outliers, low-frequency events, and performance issues upstream, downstream, or from a third-party dependency.
LightStep surfaces non-performant requests in context — no matter how narrow the search criteria — to explain why, where, and how issues arise. Aggregate, navigate and explore any segment of your service with unlimited cardinality, by specific user, release version, experiment id, and more.
Easily share a comprehensive view of system behavior for a given point in time — including detailed latency histograms, historical layers, and hundreds of relevant example traces to help explain the symptoms observed — all of which durably persist for historical review.
Link traces in LightStep to whatever tools you use — query engines, git repos, CI systems, internal dashboards, relevant logs, etc, — to improve your workflow. (For example, when connecting LightStep to time-based tools, your links pull timestamps directly from the span, allowing you to go directly to the time when the event occurred.)
You can also create hyper-specific, customizable alerts through Slack, Pagerduty, and other incident management and communication tools to manage SLIs, monitor VIP customers, and improve RCA.