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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Ubuntu Core 26 fleet observability

What is Ubuntu Core? Ubuntu Core is a minimal and strictly confined variant of Ubuntu powering devices around the world. Ubuntu Core 26 now integrates with the Canonical Observability Stack, streaming device logs and metrics to centralized Grafana, Loki, and Prometheus infrastructure, deployable in the cloud or on-premise, without burdening the device's primary workloads.

Devart Brings AI Agents Closer to Enterprise Data with New MCP Server Product Line

We are excited to announce the release of the brand new line of MCP Servers (Model Context Protocol), designed to connect AI assistants, AI agents, and large language models directly to enterprise databases and cloud business platforms. The release includes 19 specialized MCP Servers and the flagship Universal MCP Server, which enables AI access to virtually any data source through the ODBC standard.

Why AI economics needs a financial control plane

Runtime guardrails and control towers govern AI activity — but without a financial control plane connecting spend to outcomes, enterprises can't tell which AI bets are worth it. Most enterprises can answer exactly one question about their AI rollout: what did we spend?

Civo AI: Strategy over complexity

Most cloud providers think AI is just a hardware problem. They focus on the GPUs, the racks, and the raw compute, but they leave the strategy up to you. At Civo, we do AI differently. We don't just provide the hardware; we guide you through the full life cycle of AI adoption, from initial planning to scaling production workloads. By leveraging best-in-class NVIDIA models and GPUs, we give you the performance to unlock AI at scale without the fear of being bogged down by complexity. It's more than infrastructure, it’s cloud freedom with AI built-in.

Self-host AI on Kubernetes: GPU clusters, private models, and the GitOps Catalog

Spin up a GPU workload cluster using Konstruct's new GPU cluster templates, deploy a self-hosted LLM, and use it in your organization — all live on stream. This hands-on session shows how shipping AI workloads to GPU clusters is just as easy as deploying to Konstruct physical or virtual clusters, and how open source apps in the GitOps Catalog make it even faster. Walk away knowing how to cut your token spend by running models privately on your own infrastructure.

From Watching AI Search to Engineering for It: What Q1 2026 Taught Us About Real Digital Demand

Last year, I wrote about how AI-driven search trends reshaped my digital marketing strategy in ways I hadn’t seen in two decades. At the time, the story was mostly observational: traffic patterns were changing, conversions were holding, and AI-generated search answers were clearly influencing buyer behavior. Fast-forward to the first quarter of 2026, and one thing is clear — this shift didn’t slow down; it accelerated.