Operations | Monitoring | ITSM | DevOps | Cloud

New IDC study, co-sponsored by Canonical and Google Cloud, reveals the challenges and opportunities for organizations securing their software supply chains. Today, Canonical and Google Cloud released findings from a joint research project conducted by the International Data Corporation (IDC) that sheds light on the critical challenges organizations face in securing their software supply chains. The report, “The State of Software Supply Chains.

You can assess your company’s financial health using a number of SaaS metrics, depending on the type of business you are in. Among the most useful is the SaaS Magic Number. So, why is it called the SaaS Magic Number, and how do you calculate it? And why is it so important to track your SaaS Magic Number regularly?

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.

Cloud migration is a rapidly growing market, projected to reach $1.3 trillion in 2025 (Gartner). Yet, 74% of migrations exceed budget and timeline expectations (IDC). Why? Because cloud migration isn’t just a technical shift—it’s a strategic business transformation requiring coordinated planning across applications, infrastructure, networks, and finances.

As your applications scale and generate more telemetry, it becomes increasingly difficult to sift through the data and analyze it against cost, business functions, and security measures. Logs, events, and other telemetry on their own may not include enough meaningful context or readable details, leading to slower troubleshooting, inefficient business processes, and higher costs.

Recently we introduced support for Failure Strategies, which allows developers to implement more powerful logic and control flow into their workflows. Today, we are excited to announce a new step failure strategy, retry, which can auto-retry your failed steps without requiring any input from the user.

“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.