Jaeger

Jaeger is an open-source

Distributed Tracing System (DTS) (observability) for monitoring and troubleshooting transactions across microservices-based and cloud-native architectures.

• End-to-end distributed request tracing and visualization (observability)
• Root Cause Analysis (RCA), performance and latency optimization for microservices (application performance monitoring)
• Supports multiple data storage backends for trace data retention and querying (data storage and querying)
• Integrates with OpenTelemetry (OTel) and various instrumentation libraries for trace collection (telemetry and instrumentation)
• Query, UI, and backend components for trace sampling, indexing, and analysis (distributed tracing platform)

More About Jaeger

Jaeger is an open-source distributed tracing platform (observability) originally created to trace and analyze requests across microservices-based systems. It focuses on helping engineering and operations teams understand how individual requests propagate through multiple services, identify performance bottlenecks, and debug latency or reliability issues in complex, distributed environments.

At its core, Jaeger provides end-to-end request tracing (distributed tracing). Applications emit spans that describe individual operations, which are then correlated into traces covering complete request paths. These traces enable users to see service dependencies, timing information, and error propagation across the stack. Jaeger supports features such as trace sampling, span tagging, baggage propagation, and context propagation to give detailed observability into production workloads.

The Jaeger architecture typically includes client instrumentation, collectors, a storage backend, a query service, and a web-based user interface (observability platform). Client libraries or OTel SDKs send trace data to Jaeger collectors, which validate, process, and forward the spans to a storage backend such as Elasticsearch, Cassandra, or other supported stores (data storage and indexing). The query service reads from this storage and powers the UI and APIs for searching, filtering, and visualizing traces.

Jaeger integrates with OTel (telemetry and instrumentation), which is widely used for generating and exporting traces, metrics, and logs. This interoperability allows enterprises to instrument services once and route traces to Jaeger for analysis, while also supporting migration from older Jaeger client libraries to OTel. Jaeger can interoperate with service meshes and ingress gateways that emit tracing data, enabling trace collection without modifying all application code.

In enterprise environments, Jaeger is commonly deployed on Kubernetes or other container orchestration platforms (cloud-native infrastructure). It is used to troubleshoot high-latency requests, identify slow downstream dependencies, analyze retry storms, and study the behavior of complex request paths during incidents. Teams use Jaeger’s UI to explore traces, examine critical paths, and correlate trace data with logs and metrics from other observability systems.

From a directory and taxonomy perspective, Jaeger is categorized as a DTS within the broader observability and application performance monitoring domain. It provides trace collection, storage, querying, and visualization capabilities that integrate with instrumentation frameworks and telemetry pipelines, enabling detailed analysis of distributed transactions in cloud-native and microservices-based applications.