Operations | Monitoring | ITSM | DevOps | Cloud

Grafana 8 marked a major redesign in the way we do alerting. We created a unified alerting experience that implemented a workflow that operates across all of our products and combined Grafana panel alerts and Prometheus-style alerts into a single pane of glass. We built this as an open source feature first to make sure you could opt in and try it out from day one, regardless of which flavor of Grafana (OSS, Cloud, or Enterprise) works best for you.

Last November, we announced the launch of Grafana OnCall, an easy-to-use on-call management tool that helps reduce toil through simpler workflows and interfaces tailored for developers. Born out of Grafana Labs' acquisition of Amixr Inc., Grafana OnCall began as a cloud-only solution that became generally available to all Grafana Cloud users, on both paid and free plans, in February.

As a software engineer here at Grafana Labs, I’ve learned there are two questions that commonly come up when someone begins setting up a new Loki installation: “How many logs can I ingest into my cluster?” followed by, “How fast can I query these logs?” There are two ways to find out the answers.

When I started at Grafana in January, I was accustomed to working with private clouds and on-prem infrastructure, so nearly everything in my role here as a senior software engineer for the Grafana Mimir customer squad was new to me. I was new to Golang, Docker, Kubernetes, gRPC, public cloud services, etc. Kubernetes has been especially challenging. In my work on Grafana Mimir and Grafana Enterprise Metrics, I experience k8s in one of two extremes.

There is one universal truth about using Grafana: Dashboards are easy to create, but not-so-easy to organize. As organizations scale, there’s a high risk of unchecked dashboard sprawl, when dashboards become an unmanageable mess. As the number of users increase, so does their dashboard output. Our guide to dashboard management gives an overview of features that help with organizing dashboards, but there are still two pain points.

In May, a team from Grafana Labs descended on Valencia, Spain, to share their latest insights on the cloud native landscape at KubeCon + CloudNativeCon EU 2022. Along with diving into the future of Kubernetes monitoring with kubectl alpha events and multi-cloud deployments, Grafanistas presented an overview of the Prometheus ecosystem with an eye towards how sparse high-resolution histograms are going to change the game.

Creating an observability strategy is a lot like playing with Legos: It takes small building blocks to create a bigger picture, but the slightest mistake could throw off an entire build — and often you realize it very late in the process and have to rip and repair the Hogwarts castle infrastructure you spent many days creating.

Having joined Grafana Labs as one of our first data & analytics hires, I spent much of my time in the first few months considering how we should structure our data stack to optimize for a quick path to value, while allowing our small data team to scale going forward.

Here at Grafana Labs, we’re always looking for ways to provide our customers with a choice of platforms where they can run Grafana Enterprise Logs (GEL). As part of that mission, we’re pleased to announce that we’ve added Red Hat OpenShift 4.x support to GEL. GEL, as you may know, is a leading enterprise logs solution.

Most people in the world are familiar with legal tender paper money — also known as fiat currency — and how to access it online through a bank website, ATM, or mobile app. The idea of “digital money” or cryptocurrency — such as Bitcoin — remains a relatively new concept.