Application Metrics (Perfcounter | Performance Metrics | Operational data | Monitoring )

About

This section is about the collection and calculation of metrics in the monitoring context.

These (counter|numbers) are or we will derive averages from them. There is no way to figure out from the data, if you got from one point to another in an horizontal and constant line.

Type

Primitives Metrics Type are called statistical collector

Characteristics

Registry

They are generally locally grouped in a registry in order to batch the data collection.

Dimensionality

Time serie data may be classified via:

  • dimension - the event is enriched with tag key/value pairs. (AppOptics, Atlas, Azure Monitor, Cloudwatch, Datadog, Datadog StatsD, Dynatrace, Elastic, Humio, Influx, KairosDB, New Relic, Prometheus, SignalFx, Sysdig StatsD, Telegraf StatsD, Wavefront)
  • hierarchy - the name is a flat hierarchical metric name (Graphite, Ganglia, JMX, Etsy StatsD)
  • or both

dimensions are also known as tags

Hierarchy Example :

  • Atlas (CamelCase)- httpServerRequests
  • Graphite (Point separator)- http.server.requests
  • InfluxDB and Prometheus separated by _ - http_server_requests

Aggregation Processing

The aggregation of a set of samples over a prescribed time interval (Rate aggregation) may be performed:

  • Client Side (AppOptics, Atlas, Azure Monitor, Datadog, Elastic, Graphite, Ganglia, Humio, Influx, JMX, Kairos, New Relic, all StatsD flavors, SignalFx)
  • or Server-side (Prometheus, Wavefront)

Example: conversion of discrete samples (such as counts) to a rate.

Not all measurements are reported or best viewed as a rate. For example, gauge values are not rates.

Metrics Collection

The collection of metrics may be done:

  • client side via client pushes (AppOptics, Atlas, Azure Monitor, Datadog, Elastic, Graphite, Ganglia, Humio, Influx, JMX, Kairos, New Relic, SignalFx, Wavefront)
  • server side via server polls (Prometheus, all StatsD flavors)

Steps / Lifecycle

They are:

Alerting:

Category

Machine data example:

Sensor

  • temperature,
  • speed,
  • voltage,
  • number of printouts
  • …

Service Metrics

See SLI: Service Level Indicators:

Event

Some monitoring systems can also capture events:

  • Changes: Internal code releases, builds, and build failures
  • Alerts: Internally generated alerts or third-party notifications
  • Scaling events: Adding or subtracting hosts

Property

Scale and Persistence

  • last 2 hours at 1 minute resolution,
  • last 24 hours at 10 minute resolution,
  • last 3 days with 1 hour resolution,
  • last 7 days at 2 hours resolution

X-scale (Minor/Major Tick)

Scale Counter Graph

Reference

Task Runner