Around the world, thousands of DevSecOps teams are shipping software faster and more reliably by integrating Mattermost with their self-hosted GitLab deployments. When combined, these platforms connect developer toolchains with real-time communications, audio calling, screen sharing and collaborative workflows.

Mobile learning consists of learning on the go, via your smartphone or tablet. In a business setting, mobile learning offers the possibility for employees to follow their training wherever they are, with online courses and other content being accessible at all times. This learning method is available on many learning management system (LMS) platforms but, as we will see later, it is necessary to be vigilant in the choice of the latter because mobile learning comes with some technical constraints.

One of the most challenging aspects of running a SaaS business is dealing with highly variable costs. Every service you provide needs resources, and the demands for those resources fluctuate. Just when you think you’ve got this quarter’s budget nailed down, an engineer makes a restructuring decision or a new feature launch exceeds expectations (or falls flat). Suddenly, your bill looks totally different than what you were expecting.

D2iQ and Gitlab have partnered to help Kubernetes DevOps teams deliver higher-quality code faster through automation, integration, and verification of code. DKP provides a fully automated and integrated Kubernetes platform for developing and managing container deployments.

Data is the lifeline of modern businesses, and losing it can have serious consequences. That’s why backup and recovery strategies are crucial for any organization. Azure Storage is one of the most reliable and secure cloud storage solutions available, making it an excellent option for storing backups. In this article, we will explore the benefits and challenges of using Azure Storage as a backup location and provide you with a step-by-step guide to set up and manage your backups.

Even in the most structured environments with clear operational strategies, complexity build-up in infrastructure and operations is unavoidable as businesses grow. To help these environments thrive in a consistent, reliable way, it’s vital to optimize the IT function: the backbone that supports every business application and ensures service excellence across all other functions. Automating operations is the only way for IT to scale and support today’s business demands.

Platform teams are expecting an increase in Kubernetes cluster count within their environments. This is clear from the hyper-growth of cluster implementation that was reported in our latest State of Kubernetes survey (read this blog for more information), as well as the fact that we heard it directly from our customers during VMware Explore 2022.

We’ve all seen the news about tech layoffs. If you’re an engineering manager, are you having to squeeze more out of existing teams, because adding staff anytime soon is unlikely? Maybe you’re tempted to micromanage your developers, thinking that if you know every aspect of their work, it’ll boost productivity. But, that approach doesn’t feel right, and you know your devs would hate you for it. What’s an engineering manager to do?

OpenShift is a platform that allows developers and operations engineers, or even DevOps professionals, to run containerized applications and workloads. Under the hood, it’s powered by Kubernetes, but there’s an additional architectural layer that makes life simpler for DevOps teams. OpenShift is from enterprise software specialist Red Hat and provides a range of automation options and lifecycle management, regardless of where you choose to run your applications.

When an incident occurs, it's important to take the time to review what happened, understand all the contributing factors, and identify systemic changes to prevent similar incidents from happening in the future. This process is known as an incident retrospective. However, conducting incident retrospectives can be time-consuming and difficult, especially when dealing with multiple stakeholders and a large amount of data.