Application metrics

Context

You have applied the [[Microservice architecture]] pattern.

Problem

How to understand the behavior of an application and troubleshoot problems?

Forces

Any solution should have minimal runtime overhead

Solution

Instrument a service to gather statistics about individual operations. Aggregate metrics in centralized metrics service, which provides reporting and alerting. There are two models for aggregating metrics:

• push - the service pushes metrics to the metrics service

• pull - the metrics services pulls metrics from the service

Examples

• Instrumentation libraries:

  • Coda Hale/Yammer Java Metrics Library

  • Prometheus client libraries

• Metrics aggregation services

  • Prometheus

  • AWS Cloud Watch

Resulting context

This pattern has the following benefits:

• It provides deep insight into application behavior

This pattern has the following drawbacks:

• Metrics code is intertwined with business logic making it more complicated

This pattern has the following issues:

• Aggregating metrics can require significant infrastructure