Greetings! This is Eldin and Ronald reporting in from the Solutions Engineering team at Grafana Labs. You’ve probably seen some previous posts from our colleagues Christine and Aengus or maybe some of the fantastic Loki videos that Ward has put up on YouTube. This week, Ronald and I will walk through how to leverage Prometheus and Loki as data sources to create a simple but awesome Grafana dashboard that enables quick searches of logs.

This blog post will pit Grafana vs Graphite against each other, two of the most popular observability tools on the market today. R&D organizations typically implement a wide technology stack. They include varying services, systems, or tools to support their production and development environments. Most, if not all, of these companies have SLAs requiring R&D to provide high availability solutions and the ability to respond to incidents in real time.

In this article, learn: Given that enterprises use a mix of physical, virtual, and cloud native infrastructure, it can be a struggle to maintain the availability and performance of digital services. OpsRamp's Topology Explorer delivers visual representations of dependency relationships between application components and hybrid infrastructure that feed into both service maps and service-centric AIOps.

Even though search is the primary function of Elasticsearch, getting search right can be tough — and sometimes even confusing. To retrieve your data in the most efficient way from Elasticsearch, sometimes you’ll need to overcome some Lucene’s obstacles. While you need to familiarize yourself with Lucene Query Syntax for advanced Kibana use, Lucene’s implementation within Elasticsearch still has some challenges.

We’re happy to announce that Cortex v1.0 has been released! The horizontally scalable, durable, and fast Prometheus implementation is now generally available for production use. At Grafana Labs, we’ve been using Cortex in production for almost three years, including to power the Prometheus backend for the Grafana Cloud managed logging and metrics platform.

Microservices and containers have taken the tech industry by storm. Kubernetes is one of the tools that has evolved to manage these new aspects of software development. It is an open-source system for automating deployment, scaling, and management of containerized applications. One of the biggest challenges that organizations face when adopting Kubernetes is performing monitoring tasks in this dynamic environment.

It has been a little over 2 months since 1.3.0 was released. We started prepping for the 1.4.0 release several weeks ago; however, when I was writing this very blog post for the release, we discovered some confusing stats from the new statistics objects (which we’ll talk about in a bit). After sorting that out, we played the usual game of, “Wait, don’t release yet!