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civo

GPU cloud for AI inference in production: How infrastructure requirements change after training

Jun 6, 2026 By Civo Team In Civo
Training a model is a project with an end date. Inference is what happens for the rest of the model's working life. The two workloads share GPUs, frameworks, and a lot of vocabulary, but the infrastructure decisions that make sense during training are usually the wrong ones in production. Teams that treat inference as "training, but smaller" tend to discover the gap somewhere around their first traffic spike.
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MCP Servers Are Becoming a Core Interface Layer in Data Observability and Data Quality

MCP Servers Are Becoming a Core Interface Layer in Data Observability and Data Quality

Jun 6, 2026 By OpsMatters In OpsMatters
Data observability has traditionally been built around human workflows. When data breaks, engineers are alerted, open dashboards, inspect lineage graphs, and manually trace the issue across pipelines. The system is designed for human investigation and interpretation. That model is now being challenged by the rise of AI agents in data operations. As organizations begin embedding AI into analytics, engineering, and decision-making workflows, observability is no longer just about explaining what happened - it must also enable systems to understand and act on it.
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statusgator

API update: Full board management now available

Jun 5, 2026 By Andy Libby In StatusGator
We’re excited to announce expanded functionality for the StatusGator Boards API. You can now create new boards, update existing boards, and delete boards directly through the API. Previously, the Boards API only supported listing boards and retrieving board details. With these new capabilities, you can automate the complete board lifecycle – from provisioning new boards to managing ownership and cleaning up boards that are no longer needed.
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nexthink

Zero Friction, Zero Tickets, Zero Disruption: The New Operational Mandate for IT

Jun 5, 2026 By Shawn Lazarus In Nexthink
For decades, IT operations have followed a familiar model. Specialized teams manage different parts of the environment, from infrastructure and networks to security and endpoint management. When employees encounter issues, they submit tickets to the service desk, which are then triaged, escalated, and resolved. This structure has endured because it provided a reliable way to maintain system health and respond to problems as they arise.
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circleci

Agentic validation needs different infrastructure

Jun 5, 2026 By Michael Webster In CircleCI
Previously, I described some core approaches to validating agent written code: feedforward and feedback techniques. Feedforward techniques are about avoiding errors up front, for example by coming up with better prompts and planning strategies. Feedback gives agents a signal that they have actually achieved a task. Feedback is a key part of common agentic patterns like Ralph loops or the /goal commands in Codex and Claude Code: keep working until some known condition passes.
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