Graphite

The purpose today

  • What is Graphite
  • Why it's so great
  • How to graph

What is Graphite?

graphite.ch.meteogroup.net

Definition

ALERTING

METRICS

BOTH

Nagios

Icinga

Graphite

Cacti

Munin

Hyperic

Zenoss

Zabbix

What is Graphite?

Django web application

  • Carbon - relays (receiving data), aggregations, persisting on disk, caches
  • Whisper fixed-size database, similar in design to rrd (round-robin-database)
  • WebUI - simple dashboard, visualization of metrics

Why graphing?

  • Discover trends and patterns
    • What time of the day do we get the most users?
    • When x happened, what was the effect on y?
    • How many hits am I getting per hour?
    • How does this compare to last week? last month?
  • Predict future events
    • When will we need to add more servers? Databases?
  • Negative feedback
    • Did the release into production fix the problem x?

Graphite --

  • No poller
  • No all in one solution
  • No easy backups

Graphite ++

  • Simple
  • Powerful
  • Functions
    • sum, derivatives, integrals, timeshift, scale, averages, etc.
  • Api
    • Nagios integration, 3rd party custom dashboards
  • Scalable
  • Easy to feed data
  • Ecosystem 
    • http://graphite.readthedocs.org/en/latest/tools.html

A Common Graphite Stack

Collectd

Poller(s)

Scripts

Applications

Carbon

Whisper

Graphite web

Dashboards

Collectd

Agent for system/hardware level metrics

Plugins:

  • disk io
  • disk space
  • cpu
  • memory
  • mysql
  • JMX
  • java,
  • load

How to graphite data

Bash

#!/bin/bash

timestamp = `date +%s`

value = 10

echo "identifier.metric.name $value $timestamp" | nc -w l graphite.host.name 2003

 

 

schema.application_name.namespace.metric_name.metric_type

What to collect?

  • Hardware/OS, Load, Disk space, Disk IO, Network activity
  • Application metrics
    • How often function x is called
    • Average value of function x
    • Average running time of function x
  • Database/Datastore
    • ​performance metrics
    • number of slow queries
  • Events
    • Deployments
  • Log files
    • Application logs (exception counts, hits, ...)

Final thoughts

  • You don't know what metrics you need until you need it
  • Identify your KPIs
  • Don't graph everything
    • More graphs === less overview
    • Too many metrics slows down graphing
    • Too many metrics can kill a host
  • Correlate
    • Include other metrics (deployments, failover)
    • Application metrics with database metrics
    • Other influences (marketing campaigns, ...)

 

 

Questions?

Graphite

By Milan Hradil

Graphite

  • 605