Dynamic

Custom Metrics vs Traces

Developers should learn and use custom metrics to monitor application-specific KPIs that standard metrics don't cover, such as conversion rates, feature usage, or custom error types, enabling proactive issue detection and performance optimization meets developers should learn and use traces when building or maintaining distributed systems, such as microservices, serverless applications, or cloud-based platforms, to gain visibility into request flows and identify latency issues, errors, or dependencies. Here's our take.

🧊Nice Pick

Custom Metrics

Developers should learn and use custom metrics to monitor application-specific KPIs that standard metrics don't cover, such as conversion rates, feature usage, or custom error types, enabling proactive issue detection and performance optimization

Custom Metrics

Nice Pick

Developers should learn and use custom metrics to monitor application-specific KPIs that standard metrics don't cover, such as conversion rates, feature usage, or custom error types, enabling proactive issue detection and performance optimization

Pros

  • +They are essential in microservices architectures, e-commerce platforms, and SaaS applications where business logic requires tailored tracking for debugging, scaling, and improving user experience
  • +Related to: monitoring, observability

Cons

  • -Specific tradeoffs depend on your use case

Traces

Developers should learn and use traces when building or maintaining distributed systems, such as microservices, serverless applications, or cloud-based platforms, to gain visibility into request flows and identify latency issues, errors, or dependencies

Pros

  • +They are essential for observability practices, helping teams troubleshoot performance problems, ensure reliability, and improve user experience by pinpointing where delays or failures occur across interconnected services
  • +Related to: observability, distributed-systems

Cons

  • -Specific tradeoffs depend on your use case

The Verdict

Use Custom Metrics if: You want they are essential in microservices architectures, e-commerce platforms, and saas applications where business logic requires tailored tracking for debugging, scaling, and improving user experience and can live with specific tradeoffs depend on your use case.

Use Traces if: You prioritize they are essential for observability practices, helping teams troubleshoot performance problems, ensure reliability, and improve user experience by pinpointing where delays or failures occur across interconnected services over what Custom Metrics offers.

🧊
The Bottom Line
Custom Metrics wins

Developers should learn and use custom metrics to monitor application-specific KPIs that standard metrics don't cover, such as conversion rates, feature usage, or custom error types, enabling proactive issue detection and performance optimization

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