Operations | Monitoring | ITSM | DevOps | Cloud

If you've ever joined an incident call only to discover the monitor for the affected service was either misconfigured, deleted, or never set up in the first place—you already understand why monitoring as code (MaC) exists.

If you run a platform tools or security team, you have likely heard this request from developers: “I just need a copy of the production database for staging so I can run realistic load and integration tests.” It is a completely reasonable request. Production traffic and data contain the actual request shapes, real-world value distributions, long-tail anomalies, and timing patterns that make tests useful.

For years, monitoring was the gold standard of infrastructure management. Dashboards. Thresholds. Alerts. If everything on the dashboard was green, you didn't need to worry. If something turned red, you responded. It was a model built on predictability, and for a long time, it worked. But modern infrastructure is no longer predictable.

We’re excited to announce the new StatusGator SharePoint integration. Many organizations use SharePoint as the central hub for company resources, communications, and internal tools. Now, you can add real-time service status directly to your SharePoint pages, helping employees stay informed about outages, maintenance, and service disruptions without leaving the platforms they already use every day.

AI agents compress Kubernetes incident diagnosis from 45 minutes to seconds, eliminate YAML authoring toil, and shift resource tuning from static to continuous. Here is what changes concretely when they enter your workflow. Melanie leads content at Qovery. She covers platform engineering trends, Kubernetes operations, FinOps, and the tools that help engineering teams ship faster.

A practical guide to the best tools for both using AI agents to manage Kubernetes (AIOps) and running AI agent workloads on Kubernetes infrastructure in 2026. Melanie leads content at Qovery. She covers platform engineering trends, Kubernetes operations, FinOps, and the tools that help engineering teams ship faster.

As CTO for Teneo, I get the opportunity to meet with many of our customers to talk about plans for the next few years. I often find we spend a lot of time talking about Digital Employee Experience, but far less time is spent fixing the operational friction that quietly erodes it. Slow devices, degraded application performance, and recurring service desk tickets are common themes in many organizations.

Choosing a Platform-as-a-Service (PaaS) is not just an infrastructure decision. It is also a decision about how personal data will be handled over the life of the project. It's a governance commitment made early, with consequences that run late. A PaaS does not remove an organization’s accountability for privacy, security, or regulatory compliance. However, a well-architected PaaS can materially strengthen the control environment in which those obligations are managed.

June 19, 2026 This is not a regular monthly update. DataStream Version 2.0 is a milestone — the result of relentless building, learning from customers, and pushing the platform toward what enterprise-scale security operations actually demand. The core has been rebuilt, new capabilities have been added across the board, and the platform is now faster, more resilient, and more extensible than ever. Here’s what’s new.

Every monitoring vendor on the market now has an AI story. AIOps has moved from category buzzword to standard line-item in IT operations strategy, and the reasoning is sound: as infrastructure spreads across cloud, hybrid, microservices, and virtualized platforms, the volume and velocity of operational data has outrun what human teams can process. AI-powered monitoring is the obvious answer.