ITOps and DevOps are technology management practices that have been around long enough that anyone in IT should have a good grasp of what they mean. Here’s our experts’ take on ITOps vs. DevOps.
Log tracking, trace log, or logging traces… Although these three terms are easy to interchange (the wordplay certainly doesn’t help!), compare tracing vs. logging, and you’ll find they are quite distinct. Logs, traces, and metrics are the three pillars of observability, and they all work together to measure application performance effectively. Let’s first understand what logging is.
In a DevOps environment, continuous testing is essential to success. By automating the testing process, you can release new, bug-free code faster, and more efficiently. In this software development tutorial, we will examine continuous testing, its benefits, and best practices.
Dashboards allow you to visualize and correlate monitoring data from across disparate data sources, technologies, and infrastructure components to understand what’s going on in your environment. In a growing organization, it’s paramount to standardize how teams build their dashboards to ensure their consistency and legibility.
Earlier this year we introduced the world to Grafana Mimir, a highly scalable open source time series database for Prometheus. One of Mimir’s guarantees is 100% compatibility with PromQL, which it achieves by reusing the Prometheus PromQL engine. However, the execution of a query in the Prometheus PromQL engine is only performed in a single thread, so no matter how many CPU cores you throw at it, it will only ever use one core to run a single query.
