The central part of the above diagram shows the different services in the collection that support the creation of the dashboards. The expected output will be a Grafana dashboard UI and Prometheus time-series collected metrics from the two inputs listed above. The diagram below shows the generic architecture of the observability dashboards we’ll build together: With this approach, it’s quick and easy to develop future dashboards. In order to build a reusable and scalable tool, it’s better to work from common designs and templates as a first step. Generic Observability Dashboard: Design & Architecture However, the steps we’ll show you today should be applicable across a number of tools and deployments. Your in-house data source pipelines may vary – as might your data visualization software. In this article, we’ll walk you through how to build your own observability dashboard using Prometheus, Grafana and Couchbase. In addition, we used Couchbase to store historical data for later use with its Full-Text Search and Analytics tools. We used a combination of Prometheus, which simplifies storing and querying time-series data, and Grafana, which can be used to make stunning data visualizations. Then repeat the cycle until you’ve sufficiently improved.Īt Couchbase, we needed to improve some of our day-to-day operations, so we created observability dashboards to help us identify issues and track improvement. Using those metrics, you can tune the underlying work and analyze the effectiveness of any changes. The key to any improvement is to first identify what to measure and then collect the related metrics. It’s true: what you observe and measure is what you can improve. You’ve certainly heard it before: “What gets measured gets done.”
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