Features

High Scalability

Jaeger backend is designed to have no single points of failure and to scale with the business needs.

Cloud Native

Jaeger backend is distributed as a container image or a raw binary, available for multiple platforms. The behavior of the binary can be customized via YAML configuration file. Deployment to Kubernetes clusters is assisted by Alauda Build of OpenTelemetry v2 Operator.

OpenTelemetry

Jaeger can receive trace data in the standard OpenTelemetry Protocol (OTLP).

Multiple storage backends

Jaeger can be used with a growing number of storage backends:

WARNING

Alauda Distributed Tracing only supports Elasticsearch 8.x.

  • It natively supports popular open source NoSQL databases as trace storage backends: Cassandra 4.0+, Elasticsearch 7.x/8.x, and OpenSearch 1.0+.
  • There is embedded database support using Badger and simple in-memory storage for testing setups.

Sampling

To control the overhead on the applications and the storage costs, Jaeger supports multiple forms of sampling: head-based with centralized remote configuration (static or adaptive) and tail-based sampling.

Modern Web UI

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

Observability

All Jaeger backend components expose Prometheus metrics by default. Logs are written to stdout using the structured logging library zap.

Service Performance Monitoring (SPM)

SPM allows monitoring and investigating trends in the performance of the services by computing aggregate metrics from traces and visualizing them as time series charts. It is a powerful tool to identify and investigate performance issues,

See Service Performance Monitoring (SPM) for more details.

Zipkin Compatibility

Although we recommend instrumenting applications with OpenTelemetry, 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 a Zipkin backend is just a matter of routing the traffic from Zipkin libraries to the Jaeger backend.