Operations | Monitoring | ITSM | DevOps | Cloud

Introducing Cloud Provider Observability in Grafana Cloud | Demo | Grafana Labs

Learn how multi-cloud monitoring just got easier with Cloud Provider Observability in Grafana Cloud. In this video, you'll get glimpse at how the new app can enhance your observability strategy for all your major cloud providers. Plus you'll get a quick walk-through of the app.

How to Reduce Metrics Costs with Grafana Cloud Adaptive Metrics | Grafana Labs

Grafana Cloud Adaptive Metrics has helped users save up to 70% on observability costs by automatically aggregating unused and partially used metrics. This video features a demo on Adaptive Metrics, where you’ll learn what we mean by “adaptive” — automating the process of recommending which metrics to drop while giving you the flexibility to determine any exemptions. This boils down to maintaining effective observability while reducing costs.

Grafana Cloud updates: new data visualization options, enhancements to Grafana Cloud k6, and more

We consistently roll out helpful updates and fun features in Grafana Cloud, our fully managed observability platform powered by the open source Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics). In case you missed it, here’s a roundup of the latest and greatest updates for Grafana Cloud this month. You can also read about all the features we add to Grafana Cloud in our What’s New in Grafana Cloud documentation.

New Grafana k6 features: TypeScript support, async APIs for browser, and more

About every two months, the Grafana k6 team releases a new version of the open source load testing tool to deliver new features and further enhance the user experience. In case you missed them, here’s a recap of recent k6 releases and some of the exciting updates they brought to our user base. Many of the features highlighted in this post relate to new web APIs that the community has been asking for, and that are widely used by JavaScript developers.

Getting started with GitHub Data source plugin - Visualize your repos | Grafana

Learn step-by-step how to monitor and visualize your GitHub data by using the Grafana GitHub Data source plugin. It provides a lot of features such as query Commits, Pull Requests, Workflows, Vulnerabilities etc. Join Senior Developer Advocate Syed Usman Ahmad in this complete video tutorial and learn to use the GitHub plugin.

All about span events: what they are and how to query them

If you’re already familiar with distributed tracing, you know that spans are the building blocks of traces. But are you sleeping on what span events can do for you? First, you may need a wake-up call as to what a span event even is. While spans represent units of work or operation within a trace, a span event is a unique point in time during the span’s duration.

How to Query Span Events with TraceQL | Tempo Tutorial | Grafana Labs

Span events provide many benefits and can help you improve your distributed tracing game. In this video, the Grafana Tempo team goes over when to add span events to your traces. We will show you how to use TraceQL to query for span events to get useful information about your services to help you track down bugs and chase down bottlenecks faster. Grafana Cloud is the easiest way to get started with Grafana dashboards, metrics, logs, and traces.

Getting Started with Grafana Plugin Development | Grafana Plugin Development

Learn how to get started creating Grafana plugins with this comprehensive guide that covers the tools you will need, the different types of plugins to choose from, the anatomy of a Grafana plugin, how to run your Grafana plugin in development mode, as well as outlines the next steps.

Why companies choose Adaptive Metrics and how they save time and (a lot of) money

Let’s cut to the chase: Managing metric volumes at scale is hard. In fact, when we asked the open source observability community about their biggest concerns in this year’s Grafana Labs Observability Survey, the top four responses — cost, complexity, cardinality, and signal-to-noise ratio — can all be tied back to exponential growth in telemetry data.