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A trace is a group of multiple spans that usually contain “References” to each other. They can be displayed using open source solutions like Jaeger or Zipkin as well as in SaaS offerings like Honeycomb or Datadog.
A trace is a group of multiple spans that usually contain “References” to each other. They can be displayed using open source solutions like Jaeger or Zipkin as well as in SaaS offerings like Honeycomb or Datadog.
Metrics are measurements of something about your system. They are numeric values, over an interval of time, usually with associated metadata (e.g., timestamp, name). They can be raw, calculated, or aggregated over a period of time. They can come from a variety of sources like servers or APIs. Metrics are structured by default and can be stored in open source systems like Prometheus and Riemann or in off-the-shelf solutions like Amazon CloudWatch and Azure Monitor. These optimized storage systems allow you to perform queries, create alerts, and store them for long periods of time.
Metrics are measurements of something about your system. They are numeric values, over an interval of time, usually with associated metadata (e.g., timestamp, name). They can be raw, calculated, or aggregated over a period of time. They can come from a variety of sources like servers or APIs. Metrics are structured by default and can be stored in open source systems like Prometheus and Riemann or in off-the-shelf solutions like Amazon CloudWatch and Azure Monitor. These optimized storage systems allow you to perform queries, create alerts, and store them for long periods of time.
Traces are the record of the execution path of a program or system. They represent the flow of a request through your services and allow you to see the end-to-end path of execution. Distributed tracing is particularly important in modern distributed architectures, like microservices. The primary building block of a trace is the span. In the OpenTracing specification, spans encapsulate the following information: