Operations | Monitoring | ITSM | DevOps | Cloud

Mattermost v7.2 is generally available today. The following new features are included (see changelog for more details).

Implemented well, automation can be a powerful tool for accelerating and scaling DevOps processes to keep your team building and shipping code quickly. But knowing what and how to automate DevOps workflows can be challenging; every organization’s DevOps practices are unique, and there’s no one “right” way to approach automation. Let’s look at a few tips for approaching DevOps workflow automation to help your team move faster.

Welcome to the August 2022 edition of Open Source Matters: our regular publication about the latest happenings in open source! Let’s dive into the news.

Machine learning has crossed the chasm. In 2020, McKinsey found that out of 2,395 companies surveyed, 50% had an ongoing investment in machine learning. By 2030, machine learning is predicted to deliver around $13 trillion. Before long, a good understanding of machine learning (ML) will be a central requirement in any technical strategy. The question is — what role is artificial intelligence (AI) going to play in engineering?

Your team has worked hard on a software product for months, and it’s finally ready to release to your users! But then the worst-case scenario happens: a wide release soon indicates that the software is plagued with bugs and performance issues, resulting in poor reviews and widespread user dissatisfaction.

In this article, I’ll provide a guide to Git for non-developers. So, if you are reading this as a full experienced Git user, you may disagree with some of my statements. Don’t bother reading on; we recognize you as the expert! If, on the other hand, you’re new to Git, this piece is for you.

Operations staff get a hard time. The lowly systems administrator (sysadmin), database administrator (DBA) and all the other operations engineering team members from cyber penetration specialists to user acceptance testing (UAT) and so on are generally unloved.

Upgrading your Mattermost server involves a bit of research, preparation, and downtime. The pressure to keep your Mattermost instance healthy and reduce downtime for a core system within your organization can be intimidating. Recently, we worked with a handful of customers who were experiencing issues upgrading from Mattermost v5.37 and v5.39 to v6.x. Unfortunately, migration scripts were required to make significant database changes, and there was an issue in product performance.