In the previous blog posts, we've learned how to set up Carbon (caches) and Whisper, publish metrics and visualize the information and the behavior of the Carbon processes. In this blog post, I'll present another feature of Carbon - the aggregator.
Read MoreIn this blog post, I'll go through the process of stress testing a single carbon cache process and analyze the behavior as more and more metrics are published. I will also introduce the Stresser, a simple metric publishing tool.
Read MoreNow that we have the back-end components up and running and storing numeric time-series data in the formats that we have specified, it's time to take a look at the front-end components of Graphite. Specifically, we need a way to query and visualize the information that is stored.
Read MoreIn the previous blog post, we installed Carbon and Whisper - the backend components of Graphite. We then spun up a carbon-cache process to listen for incoming data points and store them using Whisper. In this blog post I describe in more detail how Whisper stores the data points in the filesystem and how you can control these details.
Read MoreGraphite is composed of multiple back-end and front-end components. The back-end components are used to store numeric time-series data. The front-end components are used to retrieve the metric data and optionally render graphs. In this blog post, I'll focus on the back-end components: Carbon and Whisper.
Read MoreFirst and foremost we need hardware on which to run the Graphite stack. For simplicity, I will be using Amazon Web Services EC2 hosts. However, feel free to use any type of computer that you might have laying around in your office or at home.
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There exists a paradox: Graphite is a real-time metric graphing tool yet it provides no metrics about itself! A few minor code additions to the graphite-api project, an ELK stack, and you'll have all the information that you need.
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