What a year this has been for Logz.io! It’s been an event-packed year for both our users and our community, with a myriad of new capabilities and product features rolled out one after the other. We’ve done the best to update you on the major new additions and have also added a What’s New feature within the UI itself to make sure you don’t miss on the new goodies being introduced.
Jenkins is an extremely popular, open-source, continuous integration tool used for running tests, building code, and subsequently pushing to staging and then production. In a previous post, I outlined instructions for collecting, analyzing and visualizing Jenkins system logs.
As engineers, we are constantly bombarded with complex machine data. In order to better monitor and troubleshoot our environments, we must analyze and gain an accurate understanding of this data to best evaluate how our systems are performing and combat any issues that may occur. Yet, sifting through this data while managing the added intricacies of serverless architecture, microservices, containers, and other technologies make our jobs increasingly difficult to navigate.
Before I hop right in, it’s important to understand a bit about diabetes. Diabetes is what happens when your body cannot produce (type 1) or respond (type 2) to insulin effectively. The impact on the body is frequently quite severe — people who have difficulty controlling their blood sugar levels run the risk of losing feeling in their fingers and/or toes or even going into a coma if their blood sugar is either too high or too low.
A decade ago, an enterprise adopting DevOps was a rare event. In the last decade, some businesses dipped their toes in, others spent big money going all in. Now the question isn’t whether to make the culture shift, but how to be successful as it grows. It’s how to scale the adopted DevOps practices in the enterprise. This article is going to focus on highlighting common missteps and offer advice that can help you make decisions to handle the challenges ahead.
One of the biggest KPIs in the DevOps space is monitoring. There are so many tools to help any organization to complete their monitoring picture, but no tool does everything and most organizations use many tools to help complete their monitoring solution. Mashing tools together often creates a problem of its own — the tool sprawl problem.
It’s nearly the end of 2018 and we still discuss CI/CD and agile as separate concepts. The truth is, the line between them is blurring. Doing either or both well is very difficult. In fact, many organizations struggle to effectively execute an agile workflow, or reach CD because they are so difficult to do well. This article focuses on why it is so important to keep striving toward this gold standard duo because CI/CD and agile result in quality and predictability.
