As many of you already know, we created Grafana using AngularJS, but we have been migrating to React for about two years now. One of the big missing pieces in our migration puzzle was the templating system. This post starts in late 2019 when I first got my hands on this mysterious and complex area of the Grafana code base.
Got the basics down and ready to move on to more advanced aspects of Kusto? You’ve come to the right place! Here you will learn how to use aggregation functions, visualize query results and put your data into context. If you’re just getting started with Kusto, check out our ‘Jumpstart Guide to Kusto’ before starting on this one. Let’s get into it!
The task of monitoring and managing an entire network, including all the servers and applications that run on it, is by no means easy. With so many components of varying complexity, the volume of performance data coming at you can be overwhelming. This information overload increases the chances of missing data that could help discover performance inefficiencies.
Visualization and Analytics are two of the most important aspects of monitoring without which the entire data stack could just mean NOTHING. Considering the plethora of graphing tools available in the market today, selecting the right one could often be confusing. In our blogs at Metricfire, we break down the best tools in terms of their setup efforts, usage, market competitors, pricing models, best practices, and many more. Grafana and Chronograf both are among the best tools available today.
Since Petr Slavotinek created the Carpet plot plugin in 2017, it’s been one of the most popular community plugins for Grafana. Unfortunately, even though the Carpet plot plugin continues to be useful to many users, it’s no longer being maintained. Grafana 7.0 introduced a brand new React-based platform, along with a set of improved APIs for building plugins.
We’ve deployed a major overhaul of how you create dashboards and graphs in AppSignal. Using dashboards is now way easier and smoother, and we’re a bit too excited about this. 🚀
At Grafana Labs, we’re all big fans of the Prometheus and Grafana combination. To an extent, we just won’t shut up about it. We strongly believe in simplicity and think you shouldn’t need any extra effort to understand the metrics of your service(s) holistically. Yet we’ve all been in that situation where it is challenging to fully grasp what the metrics of our service(s) are and what they do. While naming conventions exist, at times they are not followed or enforced.
Earlier this year, we added a Dashboard API to Cloud Monitoring, allowing you to manage custom dashboards and charts programmatically, in addition to managing them with the Google Cloud Console. Since then, you’ve asked us to provide more sample dashboard templates that target specific Google Cloud services. Many of you have also asked us to provide a Terraform module to help you set up an automated deployment process.
Among the many new features introduced in Grafana 7.0, one of the most exciting ones is transformations. The concept of data transformation is not new to Grafana, but prior to Grafana 7, it was fairly rigid and available only in the Table panel.
