Gardener, SAP's Kubernetes-as-a-service open source project, is moving its logging stack to Loki

Kristian Zhelyazkov is a developer at SAP working on Gardener, the SAP-driven Kubernetes-as-a-service open source project. In this guest blog post, he explains why the project is moving its logging stack to Loki.


Loki tutorial: How to set up Promtail on AWS EC2 to find and analyze your logs

Amazon’s Elastic Compute Cloud (AWS EC2) is one of the most popular ways to run applications in the cloud, but finding logs for a given instance is a common struggle. That’s where Loki can help. With Loki aggregation, you can group all your logs from all your virtual machines in one place, and with its search capabilities, you can quickly find and analyze them. It’s a great way to gain visibility in your cloud deployment.


Where did all my spans go? A guide to diagnosing dropped spans in Jaeger distributed tracing

Nothing is more frustrating than feeling like you’ve finally found the perfect trace only to see that you’re missing critical spans. In fact, a common question for new users and operators of Jaeger, the popular distributed tracing system, is: “Where did all my spans go?” In this post we’ll discuss how to diagnose and correct lost spans in each element of the Jaeger span ingestion pipeline.


Grafana and NGINX are partnering to give the open source community a turnkey experience for visibility

Over the past few years, NGINX users have naturally gravitated toward Grafana, and vice versa. These days, it’s not uncommon to see these two open source tools used together in the wild. And for good reason. F5, which acquired NGINX last year, is prioritizing building visibility across the entire product set, to make it easy for customers to quickly gain the insights that they need. Meanwhile, Grafana has evolved into the primary visualization and analysis tool in the open source market.

Grafana Loki sneak peek: Generate Ad-hoc metrics from your NGINX Logs

Get a sneak preview of a future version of Grafana Loki that enables you to generate ad-hoc metrics from your log data. This video features a Loki-based web analytics dashboard, which uses the access logs of the popular open-source web server NGINX. Every panel on this dashboard uses ad-hoc metrics created with Loki, well, besides the Log panel obviously. Would this be useful for your use-case? Let us know in the comments.

New Enterprise features in Grafana 7.0: Usage insights and user presence indicator

Dashboard sprawl is a real problem whether you’re using Grafana or any other tool. When growing to thousands of users – and as many dashboards – you’ll eventually want more information about how the tool is being used in your organization. After all, dashboards don’t help anyone if they aren’t being used. Managing large installations is one of the areas where Grafana Enterprise improves Grafana, and our launch of usage insights in 7.0 is a key part of that.


Getting started with the Grafana Cloud Agent, a remote_write-focused Prometheus agent

Hi folks! Éamon here. I’m a recent-ish addition to the Solutions Engineering team and just getting my feet wet on the blogging side so bear with me. :) Back in March, we introduced the Grafana Cloud Agent, a remote_write-focused Prometheus agent. The Grafana Cloud Agent is a subset of Prometheus without any querying or local storage, using the same service discovery, relabeling, WAL, and remote_write code found in Prometheus.


Why optimizing for MTTR over MTBF is better for business

The classic debate when running a software as a service (SaaS) business is between release frequency vs. stability and availability. In other words, are you Team MTTR (mean time to recovery) or Team MTBF (mean time between failure)? In this blog post, I argue for MTTR, which encourages you to push more frequently, embrace the instability this may introduce, and invest in training and tooling to deal with the pursuing outages.

Getting Started with Grafana Webinar

In this webinar, Marcus will show you how to get started using Grafana. He’ll walk you through the Grafana user interface while showing how to set up monitoring for a web service that uses Prometheus and Loki to store metrics and logs. You’ll learn how to connect, explore, and correlate data in Grafana to gain valuable insights into your application. This webinar requires no previous experience with Grafana.

Monitoring Java applications with the Prometheus JMX exporter and Grafana

We all know that Prometheus is a popular system for collecting and querying metrics, especially in the cloud native world of Kubernetes and ephemeral instances. But people forget that Java has been running enterprise software since 1995, while Prometheus is a relative newcomer to the scene. It was only created in 2012! Even though Java has had its own metric collectors since before Prometheus was born, none of our new environments speak its (metric) language. How can you bridge that gap?