Lightstep analyzes 100% of unsampled transaction data from highly distributed, large-scale production software to produce complete end-to-end traces and robust metrics that explain performance behaviors and accelerate root cause analysis. Four main components make that happen: tracers, Satellites, the Lightstep SaaS Engine, and the web application.

Tracers

You implement tracers in the language of your service’s code to create and collect span data used to describe distributed traces in your system. This instrumentation lives in your microservices, functions, web, mobile clients, anywhere your system accesses functionality. For full, broad coverage, you can auto-instrument your framework using one of the auto-installers that instrument frameworks (such as Django and Spring), common protocols (HTTP, gRPC) and data store drivers (MySQL, MongoDB). Or integrate the Lightstep tracer with Istio to instrument the full service mesh.

Lightstep tracers can also ingest data from Jaeger Agents or Zipkin, so if you’ve already instrumented your app to work with one of those, it will work with Lightstep too!

Lightstep tracers are built on top of the OpenTracing library and are fully open source.

Satellites

Satellites are Lightstep components that receive data from your tracers to collect 100% of application data. Satellites store that data for a period of time called the recall window before it’s deleted to make room for new data. Satellites analyze the performance of each segment against historical performance, error rates, and throughput.

Lightstep offers three types of Satellites: a locally run satellite that developers can use during individual coding and testing to speed up instrumentation time, public remote satellites used by development environments to quickly observe your full system pre-production, and on-premise Satellites that you configure and maintain to meet your specific production environment requirements.

Lightstep SaaS Engine

Once Satellites analyze 100% of the unsampled data, they send any data that serves as examples of application errors, high latency, or other interesting events to the Lightstep SaaS Engine. The engine further analyzes the data, builds complete traces and dynamic service diagrams, and deduces correlations among the data.

The SaaS Engine durably stores the data for as long as your Data Retention policy allows. Historical comparisons allow you to quickly see when things are not normal. Post-mortems can contain real data to show exactly what happened and when.

Lightstep Web Application

Here’s where observability can actually be realized. You can view complete traces, from web and mobile clients down to low-level services and back, with the critical path detected for you. The Explorer view makes it easy to discover and isolate distinct performance behaviors. Streams and dashboards allow you to monitor any facet of the system without limits on cardinality. Share your findings using interactive detailed views of the system.