Operations | Monitoring | ITSM | DevOps | Cloud

Resource exhaustion at a node remains a critical issue. However, the automation of deployment and management of containerized applications is executed relatively efficiently in Kubernetes. When a node is low on resources—as in CPU, memory, or storage—a workload may suffer from failures, degraded performance, and eviction.

Software development is changing fast, and here at GitKraken, we’re excited to be at the forefront. We’re entering a new era—one where AI is helping developers rather than trying to replace them. Our goal is to put that power to work for developers—embedded in your workflows, on your terms. We’ve been listening closely to feedback from our community—developers, team leads, engineering managers, and our enterprise customers.

Kubernetes autoscalers like Cluster Autoscaler (CAS) and Karpenter have evolved significantly to manage the sprawling Kubernetes ecosystem, which has grown far beyond a simple container orchestration platform to include a vast array of add-ons, operators, CRDs, and third-party integrations. These autoscalers play a crucial role in ensuring K8s workloads get the resources they need, precisely when they need them, without creating excess and waste.

“Dapper is pure speed—EF Core is bloated,” or “Dapper is a nightmare—EF Core keeps things scalable.” We’ve all heard it. Both sides make a point, but neither tells the whole story. The real question? Which one will save you from a world of pain six months from now? Dapper gives you raw SQL execution and total control, but you’re on your own when managing transactions, relationships, and migrations.

If you’ve worked with VMware Horizon (now Omnissa Horizon), you know it’s a common way for enterprise users to connect to remote desktops. But for IT engineers and DevOps teams? It’s a whole different story. Horizon’s custom protocols and complex connection requirements make load balancing a bit tricky. With its recent sale to Omnissa, the technology hasn’t changed—but neither has the headache of managing it effectively.

If you’re new to Kubernetes or looking to modernize your cluster management workflows, Cluster API and SUSE Rancher Prime make it easier than ever to provision and manage clusters declaratively. This guide walks you through enabling Cluster API in SUSE Rancher Prime, deploying your first cluster and exploring advanced features like GitOps. Some helpful documentation can be found here and a few pre-requisites for this hands-on walkthrough.

Google Cloud Platform (GCP) launched in April 2008 with Google App Engine. This developer-centric Platform as a Service (PaaS) offering allowed developers to build and host web applications on Google’s cloud infrastructure. Initially, App Engine only supported Python, but in 2009, Google added Java support, offering more programming flexibility. In 2010, GCP expanded further with Cloud Storage, its second major cloud product.

Breaches in software artifact integrity can have severe consequences. Bad actors poison artifacts by injecting malicious code into software packages, libraries, or container images, tricking developers and users into downloading compromised artifacts. These attacks can lead to data breaches, system takeovers, and widespread supply chain disruptions. Continued artifact poisoning incidents highlight the increasing risk to software supply chains.