Operations | Monitoring | ITSM | DevOps | Cloud

We spoke to data professionals from a range of industries about the impact of unreliable database deployments — not just on their systems, but on their workload, time, and well-being. From delayed releases to weekend firefighting, and the fallout for teams and customers, they share the day-to-day pressures they face and the small changes that help make deployments, and life, a little less stressful. What stood out from these conversations?

Global demand for data center capacity is skyrocketing. From 2023 to 2030, power consumption across data centers is expected to grow by up to 22% annually, driven primarily by generative AI (GenAI) workloads. By 2030, AI workloads are predicted to account for 70% of total demand. This demand doesn’t just mean more hardware; it necessitates high-density computing environments to support training large language models like GPT and real-time inference systems.

Previously, we showed you how to securely pull Docker images from Cloudsmith to Kubernetes using OIDC with a CronJob-based approach. We concluded the post discussing credential provider plugins from Kubernetes 1.20 and an enhancement in Kubernetes 1.33 that offers a new approach for external registries like Cloudsmith. We have now built a credential provider that takes advantage of this new capability. This article explores what this means for the future of pulling images from Cloudsmith on Kubernetes.

Yes. You can grab the full 3‑year AWS Reserved Instance (RI) discount but only pay for a few remaining months by purchasing through the RI Marketplace. Combine that with Compute Savings Plans for maximum coverage, cost control, and minimized risk.

Many IT teams underestimate the true cost of managing infrastructure themselves. At first glance, DIY tools may seem like a cost-effective and flexible solution — but the workflows you build and manage with in-house tooling reveal a host of hidden expenses, inefficiencies, and risks as your IT scales. While it’s not a new problem, it’s one that’s revealing itself more and more clearly as time goes on.

When troubleshooting with the Elastic Stack, Kibana is often the interface you’ll rely on to query and visualize logs. It doesn’t change the data—it just makes it searchable and a bit easier to work with under pressure. If you’re investigating an outage, tracking performance issues, or trying to correlate events across services, Kibana’s log exploration tools can speed up the process, assuming they’re configured and used well.

In the simplest of terms, container orchestration is the automated process of deploying, managing, scaling and networking containers. Containers are lightweight, portable self contained units that include an application or the processes needed to run applications. Docker is a great example of a project that helps to containerize or package applications, and was a large reason why containers gained such popularity around 2013. Before Docker there were Linux Containers (LXC).