Operations | Monitoring | ITSM | DevOps | Cloud

This tutorial shows how to use GitHub Copilot with the Puppet Model Context Protocol (MCP) server to generate, validate, and refine a Puppet module—even if you’re new to Puppet development.

I worked in observability for years, and the same pattern showed up across teams. An alert fired, the on-call rotation scrambled, and everyone did what they had to do to stabilize production. Then came the retrospective. Once the immediate pressure was gone, the conversation shifted to one question: how do we make sure this never happens again? My friend Jade Rubick coined a name for that principle: DRI, “don’t repeat the incident”.

We are excited to announce the latest release of SecureBridge, EntityDAC, and the full family of dbExpress drivers. This update delivers expanded IDE compatibility, support for the latest database versions, new security components, and platform improvements that benefit developers across the Delphi and Lazarus ecosystem.

In the modern dev stack, we have mastered the art of the deploy. We have CI/CD pipelines that ship code in minutes and observability dashboards that track every millisecond of latency. Yet, when a P0 incident strikes, the most common phrase in Slack isn’t a solution; it’s "I can’t reproduce this locally." This is the Reproduction Gap. Most engineering teams are world-class at building and monitoring, but they are remarkably fragile at recreating runtime behaviour.

In India, data sovereignty has moved from a technical detail to a boardroom priority, and in some industries, a non-negotiable requirement. Over the past few years, India’s regulatory environment has evolved quickly.

When an employee leaves your organisation, a clock starts ticking. Microsoft begins deleting their data — OneDrive files, Exchange Online emails, Teams conversations — within days of their account being disabled. For most large enterprises this is happening continuously, quietly, and without IT teams necessarily knowing until someone asks for data that no longer exists.

The word “Trillion” never fails to set the tech world on fire. Foundation Capital’s Jaya Gupta and Ashu Garg are two of the most recent firestarters. Late in December, they co-wrote “AI’s trillion-dollar opportunity: Context graphs,” outlining how AI will transition from organizational knowledge to organizational comprehension.

Quick answer: A cloud cost optimization framework is a structured, repeatable system for managing cloud spend across people, processes, and tools. It defines how teams gain cost visibility, allocate spend to the right owners, optimize resources and rates, and measure whether spend is generating business value. The FinOps Foundation organizes this around three phases: Inform, Optimize, and Operate — and the Crawl, Walk, Run maturity model maps directly to how organizations progress through them.

‍Why 90% of AI prototypes never make it to production, and what to do about it. Every week, someone on my team shows me a demo that looks incredible. An agent that writes deployment pipelines. A chatbot that triages incidents. A copilot that generates test cases from Jira tickets. The demo takes 20 minutes. The audience claps. Everyone leaves convinced we're six weeks from shipping it. We're not.