Operations | Monitoring | ITSM | DevOps | Cloud

In this blog series we’ve examined Five Myths of Apache Spark Optimization. But one final, bonus myth remains unaddressed: I’ve done everything I can. The overprovisioned resources that lead to underutilized CPU and memory in my workloads is just the cost of doing business.

As organizations scale their Kubernetes infrastructure, one truth becomes clear: no single team can optimize it alone. Efficiency, resilience, and cost-effectiveness in Kubernetes environments depend on the collective effort of multiple personas, each bringing essential knowledge and responsibility. But it’s not just about division of labor. It’s about active collaboration across roles to unlock the full potential of the platform.

Kubernetes gives you the amazing power to deploy and manage containerized applications. But this power comes with a trade-off. Instead of letting you focus only on writing code and delivering features, Kubernetes also shifts the burden of resource optimization i.e., cost control, performance, and scalability, directly onto your shoulders. The answer to these challenges is automation. Automated optimization takes the guesswork out of resource allocation.

Author Jeff Duntemann said a good tool improves how you work, whereas a great tool transforms your thinking. Companies that want to improve their cloud-based operations can rely on cloud metrics as an effective tool for transforming their cloud operations. You can’t fix what you don’t measure. Cloud metrics are the logs of data that a cloud infrastructure or application generates.

When someone leaves your company, the natural step is to disable their Microsoft 365 account. But what many businesses don’t realize is that they often continue paying for that user’s license — just to retain access to their OneDrive files, Teams chats, and emails. Over time, this adds up to thousands in unnecessary costs. In this article, we’ll explain.

When someone leaves your organization, the first step IT usually takes is to disable their Microsoft 365 account. But have you ever stopped to ask: The answer might surprise you. If you’re not actively managing this, Microsoft will automatically delete that data — often in as little as 30 days. This post explains exactly what gets deleted (and when), why this is a problem, and what you can do to protect that data — without paying for unnecessary licenses.

Easily enable Elastic add-on within the Amazon EKS Console for streamlined monitoring and quick data onboarding. Amazon Elastic Kubernetes Service (EKS) makes running Kubernetes on AWS simple and scalable. But as your workloads grow, so does the need for robust monitoring and observability. Enter Elastic Agent, a powerful, unified way to collect logs, metrics, and security data from your EKS clusters, all managed through Elastic Fleet.

Google Cloud released Google Kubernetes Engine (GKE) as a commercial version of native Kubernetes (K8s). GKE promises a user-friendly, reliable, and cost-effective service. Yet calculating GKE costs can be daunting, including understanding what you’re paying for and maximizing your return on investment. In this GKE pricing guide, we’ll discuss how GKE pricing works, what it costs, and more.

Running Kubernetes on AWS? You're probably using Karpenter, the open-source autoscaler that dynamically provisions new instances as your EKS workloads grow. Karpenter launches rightsized instances in real time in response to pending pods, based on available instance types and the resources applications need. It also terminates underutilized nodes to reduce costs.