Logz.io is a SaaS (software as a service) provider with an observability offering made up of various managed open source technologies. These technologies include the Elastic Stack for logging and SIEM (security information and event management), Prometheus, for monitoring, and Jaeger for tracing. The company positions itself as an alternative to the Elastic Stack (or ELK Stack), which is made up of Elasticsearch, Logstash, Kibana, and Beats.

I recently wrote about the importance of logging and how developers often overlook it in the software development process. Now that you’re convinced that you should be logging throughout the SDLC, it’s time to choose a reliable and dedicated log management platform.

IT professionals love their metaphors. From “pets vs. cattle” to “post mortems” to “fog computing” and beyond, practitioners tend to use analogies to shape the way they think about complex technical topics. Here’s another analogy: Log looms.

Michele Mancioppi is a product manager at Canonical with responsibility for observability and Java. He is the architect of the new system of Charmed Operators for observability known as LMA2. Jon Seager is an engineering director at Canonical with responsibility for Juju, the Charmed Operator Framework, and a number of Charmed Operator development teams which operate across different software flavors including observability, data platform, MLOps, identity, and more.

We’ve had a busy week in the Splunk Partnerverse! In addition to the new Splunk Partnerverse Program announced last week, we also shared some significant partnership news with one of our longest-standing partners, Accenture.

When teams begin to analyze their logs, they almost immediately run into a problem and they’ll need some JSON logging tips to overcome them. Logs are naturally unstructured. This means that if you want to visualize or analyze your logs, you are forced to deal with many potential variations. You can eliminate this problem by logging out invalid JSON and setting the foundation for log-driven observability across your applications.

We’re all familiar with the typical use cases for log management, such as monitoring cloud infrastructures, development environments, and local IT infrastructure. So we thought it would be fun to cover some of the less usual, more wild use cases for log management, just to show that log management tools are more versatile, and more interesting, than they may seem. If any of these use cases look too interesting to ignore, let us know and we can do a full article on them!