The volume of data that IT systems generate nowadays is overwhelming, and without intelligent monitoring and analysis tools, it can result in missed opportunities, alerts, and expensive downtime. However, with the advent of Machine Learning and Big Data, a new category of IT operations tool has emerged called AIOps. AIOps can be defined as the practical application of Artificial Intelligence to augment, support, and automate IT processes.

Your release management process is one of the most critical processes in your organization’s toolkit. An excellent release management process can accelerate software release workflows, allowing your team to deliver software consistently and predictably and ensuring that your customers have an optimal brand experience. But release processes can have weaknesses that slow your team down and can even introduce risk to every release.

Artificial intelligence for IT operations (AIOps) is an umbrella term for the use of big data analytics, machine learning (ML) and other artificial intelligence (AI) technologies to automate the identification and resolution of common IT issues. The systems, services and applications in a large enterprise produce immense volumes of log and performance data. AIOps uses this data to monitor assets and gain visibility into dependencies within and outside of IT systems.

A digital platform may have billions of messages flowing through it each day, with real-time updates considered the standard by customers and enterprises. Ensuring that messages aren’t duplicated or lost in the process is an arduous task, and one that is the focus of IBM MQ, an enterprise-grade messaging solution that has been on the market for over 25 years.

Welcome to the November 2022 edition of Open Source Matters where we cover the latest news in open source technology. I’m your host, Ben Lloyd Pearson, let’s dive in.