How is Grafana like an invisibility cloak? At Adobe, it’s one of just four tools they’re using to build observability directly into their CI/CD pipeline, making it essentially invisible — but nonetheless impactful — to thousands of developers across the organization who use it in their day-to-day lives.
In November 2021, we announced a strategic partnership with Microsoft to develop a Microsoft Azure managed service that lets customers run Grafana natively within their Azure cloud platform. Azure Managed Grafana, which became generally available in August 2022, makes it simple for Azure customers to deploy secure and scalable Grafana instances and connect to open source, cloud, and third-party data sources for visualization and analysis.
Grafana Loki is designed to be cost effective and easy to operate for DevOps and SRE teams, but running queries in Loki can be confusing for those who are new to it. Loki is a horizontally scalable, highly available, multi-tenant log aggregation system inspired by Prometheus. It doesn’t index the content of the logs, but rather a set of labels for each log stream.
A little over a year ago, we released Grafana Machine Learning, enabling Grafana Cloud Pro and Advanced users to easily view forecasts of their time series. We recently enhanced Grafana Machine Learning with Outlier Detection, which allows you to monitor a group of similar things, such as load-balanced pods in Kubernetes, and get alerted when something starts behaving differently than its peers.
David Calvert is a site reliability engineer working remotely from the south of France. He’s currently focused on observability, reliability, and security aspects of cloud infrastructure. You can find him as dotdc on GitHub and @0xDC_ on Twitter. Over the past three years, I’ve built and operated Kubernetes clusters for two different companies — the first one on-premises, and the second on a public cloud platform for my current job at Powder.
Anyone who is trying to set up monitoring for multiple machines knows how tough it can get to manage multiple Grafana Agents across them. To make things easier, we recently added the Grafana Agent role to the Grafana Ansible collection, which will help users manage the Agent across multiple Linux hosts. (Need to know how to get started with the Grafana Ansible collection for Grafana Cloud?
In 2017, Just Eat Takeaway.com (JET) was transitioning from a scrappy startup to a surging scaleup. With a global customer base and workforce, the food delivery marketplace’s front line teams needed to scale the real-time monitoring of the platform. Their initial efforts looked like “NASA’s mission control with Grafana dashboards,” said Senior Technology Manager Alex Murray.
For the team at JPMorgan Chase, the daily stakes of having a stable system are high. “We are in the business of making sure that trades are executed, and systems are stable and up and running for a positive client experience,” said Askari Imam, VP, Asset Wealth Management (Product and Integration Delivery).
One of our favorite things at Grafana Labs is seeing Grafana dashboards in action. Over the past year, members of the Grafana community — from inside and outside of the company — shared the unique ways they have used dashboards to monitor a wide range of projects including an elderly parent’s home, a Tesla, and a python named Pretzel. Let’s take a look back at some of the eye-catching and informative results.
With every new update and feature we introduced to our open source LGTM stack this year, we have also enhanced Grafana Cloud, our hosted offering that is powered by Grafana Loki for logs, Grafana for visualization, Grafana Tempo for traces, and Grafana Mimir for metrics. With Grafana Cloud, “we have curated the open source experience into an easy-to-use, opinionated, and integrated platform,” Grafana Labs VP of Technology Tom Wilkie said in the ObservabilityCON 2022 keynote.
