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Tools / Monitoring and Observability Interview Questions

What is Jaeger and how does it work as a distributed tracing backend?

Jaeger is an open-source distributed tracing platform originally developed by Uber and now a CNCF graduated project. It collects, stores, and visualizes distributed traces from microservices, making it possible to reconstruct the end-to-end journey of any request.

Jaeger's architecture consists of several components:

Jaeger Agent: A network daemon deployed alongside each application (typically as a sidecar or DaemonSet) that listens for spans via UDP (using the compact Thrift or compact binary protocol) and batches them to the Collector. The UDP protocol is chosen to be non-blocking — sending a span should never block the application thread.

Jaeger Collector: Receives spans from agents or directly from applications via gRPC/HTTP, validates them, processes them through a pipeline (sampling, indexing), and writes them to the storage backend.

Storage backends: Jaeger supports Elasticsearch (for full-text search on tags and logs), Cassandra (for high-write-throughput production deployments), and in-memory storage (for development/testing only). For production, Elasticsearch is the most common choice.

Jaeger Query and UI: Exposes an HTTP API and web UI for searching traces by service, operation, duration, and tags, and renders the waterfall view showing span hierarchy and timing.

Jaeger supports OpenTelemetry natively via OTLP, making it straightforward to migrate from proprietary Jaeger client libraries to the OTel SDK while keeping Jaeger as the backend.

Why does the Jaeger Agent use UDP rather than TCP to receive spans from applications?
Which Jaeger storage backend is most commonly used in production for its full-text tag search capabilities?

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