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.
It’s been a busy year in the world of Prometheus. Some of the 2020 highlights include a new agent; the addition of some great new features; new ways to reduce memory usage and have a faster restart time; and a fresh look at many old decisions and consensus positions.
Amid a year of challenges and change, Grafana made great strides in 2020. Grafana currently boasts more than 600,000 active installations and millions of dashboards in use across the globe. And this year, after 18,000 commits and 3,699 pull requests from 362 contributors, we revealed the next chapter of our observability story.
During a re:Invent keynote on Dec. 15, Amazon announced its AWS Managed Service for Prometheus. The service is built using the CNCF’s Cortex project, the open source, horizontally scalable Prometheus-compatible project that I started with Julius Volz over four years ago. I’d like to take this opportunity to extend a warm welcome to the Prometheus-as-a-Service club! We think you’ve made a good choice choosing Cortex, and see this as a massive vote of confidence in the project.
Over the last several months, there have been a variety of service providers that have launched Managed Prometheus offerings. This is a testament to the rise in popularity of the Prometheus project, and how it’s becoming a de facto standard for metrics. The most recent announcement in the Managed Prometheus landscape came from AWS. During a re:Invent keynote on Dec. 15, Amazon announced its AWS Managed Service for Prometheus.
In collaboration with the AWS team, we have just launched another AWS integration, the AWS IoT SiteWise plugin for Grafana. AWS IoT SiteWise is a managed service that helps users collect, store, organize, and monitor data from industrial equipment, across facilities, at scale.
Cloud native observability is at a watershed moment. The explosion of microservices has created previously unseen amounts of monitoring data, limiting the ability of humans and computer systems to extract meaning from data with last-generation tools. Debugging is often a process of detecting correlation, and then turning correlations into causal connections. This is where modern cloud native tooling comes in.
