Several tools are available to integrate Circonus in an environment that is dynamic (elastic with servers being provisioned and deprovisioned as demands change), or contains a mix of virtual, hosted (say AWS), or distributed systems.

Composite Check types

First, there are what we call Composite Checks. These are metrics that are a function composite of other metrics, for example:

  • The transaction rate across 100 web servers, or
  • The average concurrency across a large cluster of databases

  • In the first case, you may have 100 web servers now, but add (provision) 25 new ones tomorrow. Similarly, if your peak traffic occurs on Monday, you may delete (deprovision) 50 on Tuesday. These composite checks can be modified as you add and remove systems to provide a current look at your overall service.

    Chef Cookbook

    If you are using Chef to choreograph your environment, we have a very robust cookbook, available on Github

    The Circonus Cookbook contains resources for:

  • A library class, Circonus, which acts as a Circonus API v2 client

  • Chef Resources for:

  • circonus_check_bundle
  • circonus_metric
  • circonus_rule_set
  • circonus_rule
  • circonus_graph
  • circonus_graph_datapoint
  • A default recipe that uses the node attributes to create the above resources
  • Circonus CMI Tool

    Another option for Chef or AWS users is our Circonus CMI tool, also available at Github. Written in Node.JS, it is a command line tool used to control Circonus checks based on your configuration within AWS or your Chef Server.

    More information can be found here.

    Automatic Configuration from NAD

    NAD has a command-line option to automatically configure checks and graphs in Circonus. If you set your systems to deploy with NAD already present, you can then run the configuration from the newly-deployed system. More information can be found in the NAD Github project.