Operations | Monitoring | ITSM | DevOps | Cloud

How to build sustainable AI infrastructure on GPU cloud

AI's environmental cost is real, and it's growing. Training a large language model can consume the electricity of hundreds of households for weeks. Inference at production scale runs continuously, with GPU clusters drawing power around the clock. The data centers that house all of this are some of the most concentrated energy consumers in the modern technology stack.

The Best AI Coding Agent Sandboxes Compared (2026)

AI coding agent sandboxes compared for 2026: OpenAI Codex, Cursor cloud agents, Claude Code, GitHub Copilot agent and Qovery. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Stop Managing Endpoints: The Power of AI Automation

In just two minutes, learn how our AI-powered platform unifies control across Windows, Mac, Linux, Mobile, and even VR/XR headsets. Discover how to eliminate tedious tasks with automated patching, zero-touch onboarding, and self-healing capabilities—allowing your team to focus on strategy instead of firefighting. What you’ll see in this video.

How AI-Powered Monitoring is Transforming IT Operations

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.

The Best Tools for Integrating AI Agents with Kubernetes in 2026

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.

How Kubernetes AI Agents Improve Cluster Management

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.

Working as a remote engineer at Cribl | Building the AI Platform for Telemetry

Learn what it’s like to work as an engineer at Cribl, a remote-first company building the AI platform for IT and security data. In this recruiting video, Cribl’s engineering and support leaders share how fully distributed teams collaborate, solve hard data problems, and grow their careers while working from around the world. You’ll hear from managers and leaders in site reliability engineering, security incubation, and technical support about.

Chunk sidecars: Inner Loop Validation for AI Coding Agents

Your agent writes code fast, but you shouldn't have to see it until it's right. Chunk sidecars are lightweight microVMs that work inside the agent loop, requiring agents to pass pre-push validation in a CI-like environment before they declare they're "done." That means no massive CI pile-ups, no long round-trips that risk resetting your agent's context. You're sending code you already know is good.