Operations | Monitoring | ITSM | DevOps | Cloud

A preview of leadership insights shaped by real-world experience Estate-wide clarity for leaders who still need technical depth As data estates grow, the role of technical leaders changes. Visibility becomes harder. Communication becomes more important. Decisions have broader consequences. Many leaders start their careers focused on the technical details.

Q1 2026 has been one of our most eventful quarters yet for VictoriaMetrics Cloud. We shipped something we have been building towards for a long time, crossed a few infrastructure milestones, and started clearing the path for what is coming next to the most performant observability stack.

The shift from legacy middleware to open-source innovation promises agility and cost savings, but introduces the 'Modernization Tax'—operational complexity that requires new approaches to observability, governance, and management across hybrid messaging environments.

Organisations are re-evaluating their VM infrastructure. The economics have shifted, the tooling has matured, and the case for running two separate platforms, one for containers, one for VMs, is getting harder to justify. Platform teams that spent years managing hypervisor infrastructure are being asked to consolidate, and most are landing on the same answer: Kubernetes. KubeVirt makes running VMs on Kubernetes possible.

Over the past few months, Puppet has partnered with Bryxx to host a series of leadership lunches across Europe, bringing together infrastructure, operations, and security leaders for candid, peer‑to‑peer conversations. These sessions weren’t marketing briefings. They were grounded discussions about what teams are facing right now: tighter regulation, rising security pressure, shifting cloud strategies, and the practical realities of automation and AI.

Enterprise boardrooms are not debating whether to adopt agentic AI anymore. The debate has moved to a harder question: why do so many agentic deployments stall between pilot and production? ServiceNow's Enterprise AI Maturity Index 2026 puts a number to it. Most enterprises that have invested in AI tooling report that their biggest obstacle is not model quality or compute cost. It is the infrastructure that those agents are expected to operate within. The models are capable.

Most of us run multiple virtual private servers (VPS) at a time. That’s why it’s important to keep an eye on the CPU usage and memory. However, since this step often slips our minds, there is room for automated monitoring. Open-source tools tend to be a default choice, and for a good reason. The problem is that they don't provide everything you need for monitoring in a single place. As a result, you may find yourself writing custom shell scripts for automation.

Managing Terraform across dozens of AWS accounts becomes a maintenance nightmare fast. Teams end up copy-pasting the same backend configurations, provider blocks, and variable definitions hundreds of times. Terragrunt acts as an orchestrator above Terraform, eliminating this duplication through shared configuration inheritance and dependency management. When financial services teams manage 200+ microservices across multiple environments, these DRY patterns become essential for governance and consistency.