Operations | Monitoring | ITSM | DevOps | Cloud

One of the first decisions teams face when adopting Konstruct is whether to run the control plane themselves or have it managed for them. While this can look like a simple deployment choice, it is really a question of operational responsibility, control, and how your platform needs to evolve over time. Both models exist to solve the same underlying problem: providing a consistent, GitOps-driven platform across teams and environments.

In preparation for launching CertKit last week, I browsed the websites of a lot of related cybersecurity services. I don’t really understand what any of them do, but apparently, “trust” is a thing that can be sold now.

Kosli gives your organization a complete picture of software delivery - every build, scan, deployment, and compliance event tracked. Until now that picture was most useful to the people managing governance. However, developers shipping code had to ask someone else what versions of their code were running, how long it was taking to get to production, or what their deployment frequency was. Repositories change that.

Custom dashboards in Netdata have always let you pull charts together on-the-fly into a single view. That’s useful, but it’s also limited. In practice, when you’re running an incident or reviewing a service, you don’t just want charts. You want to see the output of top alongside your CPU metrics. You want slow query logs next to your database latency charts.

The regulatory landscape governing UK sovereign cloud security has shifted more dramatically in the past 12 months than in the preceding decade. New legislation, tightened procurement frameworks, and an intensifying cyber threat environment are collectively raising the compliance floor for organizations running cloud workloads in the UK.

The shift from AI copilots to autonomous agents is redefining infrastructure requirements. Discover how to build secure, stateful, and compliant Agentic AI systems using Kubernetes, sandboxing, and observability while meeting EU AI Act standards.

Not long ago, adding a new cost connector to CloudZero was a serious undertaking. We’d task multiple engineers, build in extended review cycles, run a private preview period. But a single connector could take up to two months from kickoff to customer hands. For the major cloud providers, that timeline was acceptable. The size of the investment matched the scale of the integration. But the tools landscape has changed. Our customers’ teams don’t just run on AWS and Azure.

Security teams face overwhelming amounts of data and complex interfaces, making it hard to access critical insights. AI tools promise solutions, but integration remains difficult as time ticks away and leadership wants the latest data to inform risk decisions. Most security platforms lack seamless integration, slowing access to important data and hindering AI-powered workflows.

If you’ve ever opened the alerts tab during a busy period, you know the problem. There are alerts you’ve already looked at, alerts someone on your team is handling, and alerts that fired on a known issue that’s being worked on. They all sit together in the same list alongside the new ones you haven’t seen yet.