Showing archive results for 2026

Agentic Platform Engineering for SaaS.  Accelerating the Path to Market with Git-APE If you are an ISV building SaaS on Azure, the first demo is usually the easy part. The harder work is turning that proof of concept into a secure, scalable, commercial-ready service that can be operated confidently in production. That gap shows up quickly. T...

Grounding an assistant in runbooks is straightforward. The harder part begins when the model proposes an action that requires authorization. An operations assistant needs stronger controls as soon as it can act. Answering "which runbook covers this alert" is a search problem. Opening an incident from that same conversation is a control...

Frameworks mean nothing, until they change what gets built! In this article we discuss how Git-Ape turns architecture and governance into delivery controls on Azure because, if frameworks do not shape delivery decisions, they are just decoration. Cloud teams do not have a framework problem. They have an execution problem. The industry is...

At Microsoft Build, we are sharing how Microsoft Marketplace brings development, distribution, and monetization together— so apps and agents move beyond prototyping into real-world usage at scale. Microsoft Marketplace connects tens of thousands of cloud and AI solutions built by software development companies to millions of commercial customers. ...

Removing The Monkey Work of Migration; in this post we show how Git-Ape analyses an AWS deployment repo and generates an Azure-native replacement, with design critique built in. This post walks through a real migration workflow: start with an AWS deployment repo and end with an Azure deployment repo. The goal isn’t a 1:1 syntax conversion. I...

~1,900 lines of Python. Zero dependencies. Saves you an hour a day. GitHub → ·  Now give Copilot CLI enhanced context recall. Point it at  and let it cook. 🍳 Are you tired of using the slash /compact command every 10 min? The Context Window Is a Lie Every AI coding agent ships with a big number on the box. 200K tokens. Sounds massive...

This post is the first in a 3-part series: Bookmark this post for quick reference as you start exploring Agentic DevOps. It will be updated as the 3 parts become available. Getting started with Agentic DevOps Agentic DevOps is a new approach to software development where AI-powered agents work alongside your team across the entir...

Legacy codebases frequently contain hardcoded logic and complex build scripts that depend on specific filesystem structures, making them notoriously difficult to modernize in isolated environments. Docker Sandbox addresses this challenge through a bidirectional workspace sync that preserves the same absolute paths inside the sandbox as on the host....

AI agents are quickly moving from experiments to production‑critical components of modern applications. But while many teams know how to build agents, far fewer are confident they’re hosting them on the right foundation. Most organizations start by deploying agents the same way they deploy microservices—containers, functions, or app services. ...

Practices, Principles, and Strategic Direction Software delivery has entered a new phase. AI agents are no longer confined to autocomplete suggestions in the editor. They are opening pull requests, generating code across multiple files, proposing infrastructure changes, responding to issues with working implementations, and executing multi-step en...