Three years ago, Tom Wilkie and Frederic Branczyk sketched out the idea for Prometheus monitoring mixins. This is a jsonnet-based package format for grouping and distributing logically related Grafana dashboards with Prometheus alerts and rules. The premise was that the observability world needed a way for system authors to not only emit metrics, but also provide guidance on how to use those metrics to monitor their systems properly.

Grafana Cloud is the easiest way to get started observing metrics, logs, traces, and dashboards. When we say “easiest,” we mean it: Grafana Cloud is designed so that even novice observability users can use it. As a new user, you are not required to dive into the complexity of setting up Prometheus and figuring out how to create Grafana dashboards from scratch. Integrations are the reason why.

Oftentimes users of open source are told to go download it and figure it out… or pay for a managed solution in the cloud. So the typical choice is free and do-it-yourself or expensive and easy. With our new changes to Grafana Cloud, we are making it both free and easy to have a real, composable observability solution.

In my ongoing Loki how-to series, I have already shared all the best tips for creating fast filter queries that can filter terabytes of data in seconds and how to escape special characters. In this blog post, we’ll cover how to use metric queries in Loki to aggregate log data over time.

You’ve probably heard about Prometheus, the leading open source project focused on metrics and alerting, and how it has changed the way the world does monitoring and observability. But if you’re brand-new to the technology, how can you dip your toes in and get started? I was in this position not long ago myself. I am a very hands-on type of learner, and usually when I want to explore new technologies, I start with “hello world” apps and small toy projects.

Smart State Technology (SST) is a company based in the Netherlands that develops advanced technological and future-proof solutions for smart grids. Their mission is to reinforce critical energy infrastructures by providing innovative energy solutions that connect industry and research, while ensuring society can fully benefit a sustainable energy future.

In my ongoing Loki how-to series, I have already shared all the best tips for creating fast filter queries that can filter terabytes of data in seconds. In this installment, I’ll reveal how to correctly escape special characters within a string in Loki’s LogQL. When writing LogQL queries, you may have realized that in multiple places you have to write strings delimited by double quotes.

In 2014, the Mazia (Matsch) research site in the Italian Alps was officially accepted as a Long Term Socio Ecological Research LT(S)ER site. The monitoring infrastructure is operated by Eurac Research and the University of Bolzano and consists of 24 automatic microclimatic stations in a mountain ecosystem across an elevation gradient ranging from 1,000 m to 2,700 m, logging several meteorological and biophysical variables every 15 minutes.

What a year 2020 has been for Grafana Loki! Just a little more than a year ago, we announced Loki’s 1.0.0 GA release. We’re excited to report that 2020 brought a big uptick in its adoption (users have quickly realized the advantages of a small index—plus, Loki has non-technical advantages, too); significant performance enhancements; and the recent release of Loki 2.0.

2020 is coming to an end, and we can definitely say it was an amazing year for Cortex. Dare I say, it has been the best year so far! It was a year filled with huge milestones for the project. We released the first major version 1.0.0 back in April, along with introducing some versioning rules to avoid breaking changes to our users.