Operations | Monitoring | ITSM | DevOps | Cloud

During the Toronto KCD (Kubernetes Community Days), I attended an insightful talk on AI resource optimization that highlighted a staggering Gartner study: “AI infrastructure is adding $401 billion in new spending this year alone. Yet, real-world audits tell a much darker story, revealing that average GPU utilization in the enterprise is stuck at a dismal 5%”. While many people in the audience were shocked by that number, the data didn’t come as a surprise to us.

You’ve deployed Karpenter or Cluster Autoscaler and tightened your resource requests, but while you saw an initial dip in your cloud bill, your savings have flatlined. Organizations that thought they had the fundamentals of cloud cost under control are now seeing stagnation. The problem isn’t that they need another FinOps tool or better visibility. The problem is that the current state of enterprise cloud cost optimization strategy is fundamentally reactive.

AI SRE Platform’s new capabilities resolve structural blockers and optimize workload placement, eliminating cloud waste to drive up to 80% in total cost savings.

Prometheus is a wildly popular open source monitoring tool typically used for monitoring Kubernetes environments and containerized workloads. But how do you turn the mountains of metrics into a clear picture of health and performance? SquaredUp plugs directly into your Prometheus database to visualize and monitor your data. What sets SquaredUp apart from other Prometheus visualization options like Grafana and Perseus is just how easy it is to visualize, monitor and share Prometheus dashboards.

MSPs operate in high-pressure, customer-first environments where understanding exactly what is happening across client environments is the difference between proactive service and constant firefighting. Yet, many still struggle to get a unified view across their customers, tools, and teams.

Production secrets should live in one place and stay there, whether your next deployment is triggered by a developer or an AI agent. The Secret Manager integration connects AWS Secrets Manager, AWS SSM, or GCP Secret Manager to Qovery so secrets are referenced, never copied, and enterprise governance holds regardless of who deploys. Alessandro leads product at Qovery. He drives the changelog, roadmap, and product strategy - turning customer feedback into platform capabilities.

Cisco Live 2026 showed where networking is headed next. Explore the top announcements shaping cloud, AI, security, and more. Cisco Live 2026 just wrapped up in Las Vegas, and if there was one message that came through loud and clear, it was this: Infrastructure is becoming more autonomous.

A container reporting “up” tells you the process is running, not that the workload is healthy – but that caveat is true of any service, on a container or a bare server.

Building custom middleware monitoring appears cost-effective but creates expensive maintenance debt, fragmented visibility, and operational risk. Enterprise teams spend 60-80% of IT budgets on software maintenance while unified platforms deliver immediate, production-ready capabilities.