Operations | Monitoring | ITSM | DevOps | Cloud

A year ago, we hit a wall. Our Grafana OSS releases were excruciating to execute. The process was confusing and hard to follow, security patches were non-trivial, and many engineering hours were lost to an overly manual process. We needed to move fast, cut through ambiguity, and pull in just the right people without waiting on roadmaps or org charts.

Since its launch in 2020, the Infinity data source for Grafana has become the go-to solution to seamlessly query and visualize data from JSON, CSV, XML, and GraphQL endpoints within Grafana. Allowing users to integrate diverse data formats via HTTP-based APIs, the Infinity data source has enabled a wide range of use cases within our community over the years — from visualizing cloud computing costs to popular Pokémon games.

There’s a new way to ingest AWS metrics into Grafana Cloud that makes observing your AWS resources more cost-effective, easier to operate, and more accurate. You can now stream metrics into the AWS Observability app in Grafana Cloud in near real-time thanks to our new integration with Amazon CloudWatch and Amazon Data Firehose. We’re already using it internally, and we’re finding that it’s not only easier to operate—it’s at least five times more cost-effective.

One of the biggest challenges in frontend development is identifying when and why users encounter performance issues, whether it’s slow page loads, JavaScript errors, or failed HTTP requests. With Grafana Cloud Frontend Observability — a hosted service for real user monitoring (RUM) — you get immediate, clear, and actionable insights into the end-user experience of your web applications.

Note: A version of this post originally appeared on the OpenTelemetry blog. Victoria Nduka is user experience designer and open source contributor making her way into the cloud native space. She writes about design, accessibility, and open source with the same curiosity she brings to her work. On May 29, I wrapped up my mentorship with Prometheus through the Linux Foundation mentorship program.

Imagine you’re a frontend engineer monitoring the user experience for an e-commerce app. You notice your checkout flow has a 15% abandonment rate. Your API responses are inconsistent. Your users are frustrated, and you’re drowning in data and complex queries trying to figure out why. Sound familiar? You can use real user monitoring (RUM) to determine what has happened, looking at page load times, error counts, user sessions, etc.