Operations | Monitoring | ITSM | DevOps | Cloud

If you manage more than a handful of monitors, you have probably wanted to define them in code rather than clicking through a dashboard. Terraform is the standard tool for that in the infrastructure world, and now there is a Terraform provider for Hyperping. Develeap, a DevOps consultancy, built this provider while managing monitoring for 57 tenants at scale. They needed infrastructure as code for monitors, status pages, and incidents, so they built it, tested it in production, and open-sourced it.

PayPal runs six data centers, each with around 60,000 containers. Their 30,000 employees spin up nearly 10,000 test environments every day — roughly 6 to 10 every minute. Each environment requires three config updates: one to create the virtual service, and additional calls to configure and deploy the applications. Do the math and you get a staggering 30,000 config updates per day.

Regular DR testing is no longer a compliance checkbox — it is a critical engineering discipline that determines whether an organisation can survive a real cloud outage with its services and revenue intact. As the AWS Middle East incident demonstrated, regional cloud failures can strike without warning and defeat standard redundancy models, making untested DR plans dangerously unreliable.

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.