Operations | Monitoring | ITSM | DevOps | Cloud

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.

At Grafana Labs, we’ve seen an increasing number of customers who are scraping hundreds of millions of active time series but need a solution to reliably store and query such a huge amount of data. So in March, we announced our new open source TSDB, Grafana Mimir, the most scalable, most performant open source time series database in the world.

Today, we are excited to announce that the MySQL integration has received an important update, which includes a new pre-built MySQL logs dashboard and the Grafana Agent configuration to view and collect MySQL server logs. The integration is already available in Grafana Cloud, our platform that brings together all your metrics, logs, and traces with Grafana for full-stack observability.

Today, we are thrilled to share that the macOS integration has finally arrived for Grafana Cloud! Thanks to the joint efforts of Grafana Labs’ multiple teams, you can monitor your Mac and gather and visualize metrics and logs with ease. The integration is available in Grafana Cloud, our platform that brings together all your metrics, logs, and traces with Grafana for full-stack observability.

The new Sqlyze data source plugin (in beta) allows you to connect your Grafana instance to all your favorite SQL databases, many NoSQL databases, and many other non-SQL data sources — from document databases, to ERP systems, to even Slack. You don’t have to know the native query syntax for these data sources; you can just use SQL. The Sqlyze plugin uses ODBC at its core. Hundreds of ODBC drivers are available for various databases/data sources.