Jaeger is used for monitoring and troubleshooting microservices-based distributed systems, including:

• Distributed context propagation
• Distributed transaction monitoring
• Root cause analysis
• Service dependency analysis
• Performance / latency optimization

High Scalability

Jaeger backend is designed to have no single points of failure and to scale with the business needs. For example, any given Jaeger installation at Uber is typically processing several billion spans per day.

Native support for OpenTracing

Jaeger backend, Web UI, and instrumentation libraries have been designed from ground up to support the OpenTracing standard.

• Represent traces as directed acyclic graphs (not just trees) via span references 
• Support strongly typed span tags and structured logs
• Support general distributed context propagation mechanism via baggage

Multiple storage backends

Jaeger supports two popular open source NoSQL databases as trace storage backends: Cassandra 3.4+ and Elasticsearch 5.x/6.x/7.x. There are ongoing community experiments using other databases, such as ScyllaDB, InfluxDB, Amazon DynamoDB, Logz.io. Jaeger also ships with a simple in-memory storage for testing setups.

Modern Web UI

Jaeger Web UI is implemented in Javascript using popular open source frameworks like React. Several performance improvements have been released in v1.0 to allow the UI to efficiently deal with large volumes of data, and to display traces with tens of thousands of spans (e.g. we tried a trace with 80,000 spans).

Cloud Native Deployment

Jaeger backend is distributed as a collection of Docker images. The binaries support various configuration methods, including command line options, environment variables, and configuration files in multiple formats (yaml, toml, etc.). Deployment to Kubernetes clusters is assisted by a Kubernetes operator , Kubernetes templates  and a Helm chart .

Observability

All Jaeger backend components expose Prometheus  metrics by default (other metrics backends are also supported). Logs are written to standard out using the structured logging library zap .

Backwards compatibility with Zipkin

Although we recommend instrumenting applications with OpenTracing API and binding to Jaeger client libraries to benefit from advanced features not available elsewhere, if your organization has already invested in the instrumentation using Zipkin libraries, you do not have to rewrite all that code. Jaeger provides backwards compatibility with Zipkin by accepting spans in Zipkin formats (Thrift, JSON v1/v2 and Protobuf) over HTTP. Switching from Zipkin backend is just a matter of routing the traffic from Zipkin libraries to the Jaeger backend.