Explain API Observability with Tracing.
API observability with tracing means monitoring APIs by following each request’s path across services, helping teams debug issues and optimize performance.
When to use/Use Cases
Use tracing in microservices architectures, where one API call touches multiple components. It’s ideal for diagnosing latency, identifying bottlenecks, and ensuring reliability in distributed systems.
Example
When you log into an app, the request flows through authentication, database, and notification services. Tracing shows which step slowed down or failed.
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Why Is It Important
Without tracing, errors are “black boxes.” With it, you gain end-to-end visibility into requests, making debugging faster and improving user experience.
Interview Tips
In interviews, explain how tracing complements logs and metrics. Mention real-world use cases (like login flows) and highlight the role of trace IDs in following a request across services.
Trade-offs
Tracing provides deep insights but requires instrumentation effort, can slightly impact performance, and generates lots of data. Teams often mitigate this with sampling strategies.
Pitfalls
Common mistakes include failing to propagate trace IDs or tracing everything (causing data overload). Focus on critical paths to balance value and cost.
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