Operations | Monitoring | ITSM | DevOps | Cloud

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.

We are introducing a change to the pull request merge checks that will make them more reliable. Specifically, we will no longer allow pull requests to be merged while a build is in progress. It was possible for a pull request to be merged while some of its builds were still in progress and for those builds to fail after the merge has completed. This created an undesirable situation if build merge checks were enabled.

Reliability and chaos might seem like opposite ideas. But, as Netflix learned in 2010, introducing a bit of chaos—and carefully measuring the results of that chaos—can be a great recipe for reliability. Although most software is created in a tightly controlled environment and carefully tested before release, the production environment is harsher and much less controlled.

I’ve written extensively about the technical aspects to consider when expanding your horizons and embracing the Mac platform. What I haven’t covered much up to now is why. Why bother learning an entirely new skillset, targeted at supporting a minority platform, when you’ve got your hands full just keeping up with Windows?

Instrumental has made the decision to shut down its platform starting August 2022 including its application, servers, and all related APIs being shut down. Users will need to migrate to another solution or risk all their data being permanently deleted! But Instrumental users need not fret!

Recently I heard one of our prospects talk about a competitor who was promoting their data lake and ask, how are we different than that? His question got me thinking about why a data lake alone does not provide the depth of observability you really need. The goal of observability is to help SREs, IT Ops and DevOps teams run their IT systems with close-to-zero downtime. Consolidating data from across your environment into a data lake is certainly a good step.