🧠 Humans of Cyber | Yuri Shkuro
Open source distributed tracing platform that tracks requests across microservices to diagnose latency, failures, and performance issues in cloud native systems.
Jaeger is an open source distributed tracing platform originally created in 2015 at Uber by Yuri Shkuro to solve observability challenges in rapidly growing microservices architectures.
As Uber expanded from hundreds to thousands of services, traditional logs and metrics could no longer show how a single request moved across the system. Yuri Shkuro led the development of Jaeger to trace the full lifecycle of a transaction across multiple services, enabling engineers to diagnose latency, failures, and dependency issues in distributed environments.
Jaeger models system activity using traces and spans. A trace represents a complete request as it travels through services, while spans record individual operations within that request. Each span contains timing data, tags, logs, and context information. Trace context is propagated through service calls, allowing Jaeger to reconstruct the full execution path and visualize it as a request timeline.
The platform’s architecture collects span data through instrumented applications using client libraries or OpenTelemetry SDKs. Spans are typically sent to a Jaeger Agent, forwarded to Collectors for processing, and stored in backends such as Elasticsearch or Cassandra. The Query service retrieves traces from storage and renders them in the Jaeger UI for analysis.
Jaeger was open sourced by Uber in 2017 and donated to the Cloud Native Computing Foundation the same year. It graduated as a CNCF project in 2019 under the Apache License 2.0. In 2024, Jaeger v2 introduced a major architectural shift by rebuilding the backend on the OpenTelemetry Collector framework and adopting the OpenTelemetry Protocol as its native data model.
Today Jaeger is widely used in Kubernetes and cloud native environments for distributed tracing, root cause analysis, service dependency mapping, and performance optimization across microservices systems.
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