Have you ever had to purchase a CPU or a GPU? If so, you have probably come across the term “bottlenecking”. There is a certain threshold where output exceeds ability to process, and that can prevent optimal system functionality. One of the methods used in computing to overcome these bottlenecks is multi-threading, where requests are processed simultaneously by multiple threads. We can apply a similar principle to downtime monitoring.
With progressive delivery, DevOps, scrum, and agile methodologies, the software delivery process has become faster and more collaborative than ever before. Scrum has emerged as a ubiquitous framework for agile collaboration, instilling some basic meetings and roles into a team and enabling them to begin iterating on product increments quickly. However, as scrum teams grow and systems become more complex, it can be difficult to maintain productivity levels in your organization.
The software testing data provided by CI/CD tools is valuable, but it is not always comprehensive enough to give managers the insights they need to make improvements. To make effective business decisions, managers need visibility into the entire testing process, in a way that will help them understand what needs to be done and how.
Last year we had a look at managing local groups with the custom groups promise type. As you may or may not recall, we used JSON-strings to imitate CFEngine bodies. This was due to the fact that the promise module protocol did not support bodies at that time. Today, on the other hand, we’re happy to announce that as of CFEngine 3.20, this will no longer be the case. In this blog post we’ll introduce the long awaited feature; custom bodies.
Enterprises are dealing with a deluge of observability data for both IT and security. Worldwide, data is increasing at a 23% CAGR, per IDC. In 5 years, organizations will be dealing with nearly three times the amount of data they have today. There is a fundamental tension between enterprise budgets, growing significantly less than 23% a year, and the staggering growth of data.
