Browse Azure Blogs (17)

John Edward compares Azure Bicep and ARM templates, explaining their shared deployment engine and differences in syntax, validation, dependencies, and reuse. Practical Azure CLI examples show how to compile templates, preview changes, and deploy resources, while migration guidance helps teams decide when to adopt Bicep or retain existing JSON workflows.

Hidde de Smet's Blog compares Bicep and Terraform for Azure, focusing on resource ownership rather than syntax preferences. The guide explains deletion behavior, deployment previews, ARM API coverage, module defaults, and existing-resource adoption, then outlines a disposable pilot for testing each tool against your team's infrastructure requirements.

John Edward explains how to monitor Copilot Studio agents in production by combining conversation analytics with application telemetry, security controls, and outcome-based metrics. The guide focuses on catching failures early (tool-call errors, latency, unsafe access), setting baselines and alerts, and tying cost and performance back to successful task completion.

Jesse Houwing explains how to harden GitHub Actions OIDC authentication to Azure by switching to immutable subject claims, so federated credentials can’t be hijacked after a repo rename, transfer, or deletion. The post shows what changes in the subject claim and how to fetch the required IDs via the GitHub API.

John Edward explains the planner-executor loop as a practical architecture for building agentic systems on Azure, focusing on how to separate planning from execution, validate model outputs, and run tool calls safely. The article maps the pattern to Azure services and highlights reliability, observability, and access-control decisions needed for production use.

Thomas Maurer announces two NVIDIA GTC Berlin sessions covering Microsoft Sovereign Cloud updates and how to run Sovereign AI from Azure to the edge using Azure Local and Foundry Local, with an emphasis on control, compliance, resilience, and security requirements.

John Edward covers Microsoft and AWS’s Azure Multicloud Interconnect for AWS announcement, focusing on what it changes for private, high-bandwidth connectivity between the two clouds and why it matters for teams running cross-cloud, data-heavy workloads.

Thomas Maurer argues that Azure Local should be evaluated as the infrastructure foundation of Microsoft Sovereign Private Cloud, not just as a hypervisor replacement. He breaks down connected vs disconnected operations, Azure Arc control-plane options, and the platform capabilities (AKS, data services, Foundry Local, GitHub Enterprise Local) that shape sovereignty and resilience.

Pieter Vandenheede breaks down four practical BizTalk migration paths—do nothing (short-term), coexistence, domain-by-domain migration, and big-bang replacement—and provides a decision matrix to help teams choose an approach that fits their constraints and risk tolerance.

Pieter Vandenheede explains how to decide whether to keep BizTalk after Microsoft confirmed BizTalk Server 2020 is the final release, and what conditions make “staying” a deliberate (and limited) choice. He also outlines practical signals that it’s time to move and frames the shift from “if we migrate” to “how we migrate safely.”

Thomas Maurer explains how Adaptive Apps and the open-source Radius control plane help teams engineer, test, and prove application portability across Azure, Azure Local, and other Kubernetes environments by separating app intent from environment-specific implementations.

Pieter Vandenheede breaks down Microsoft’s BizTalk Server lifecycle update, what stays supported through 2028/2030, and why “support isn’t strategy” for long-term integration platforms. He outlines practical next steps: inventorying your integration landscape, planning timelines, and evaluating Azure Integration Services (including Logic Apps) as the direction Microsoft is investing in.

Thomas Maurer introduces the new digital sovereignty adoption guidance in the Microsoft Cloud Adoption Framework, explaining the sovereign cloud continuum and a practical three-phase path (planning, architecture/governance, and operations) for building and running controlled Azure workloads across public, private, and partner cloud models.

Thomas Maurer shares takeaways from a discussion at the HPE Customer Innovation Center on Azure Local and Microsoft’s Sovereign Private Cloud vision, focusing on how organizations can meet data residency, compliance, and operational control requirements while still using Azure-consistent capabilities in hybrid and edge environments.

John Edward lays out a practical checklist for taking an AI agent from demo to production using Microsoft Copilot and Azure AI Foundry, focusing on architecture choices, grounding with enterprise data, controlled tool permissions, evaluation, monitoring, and cost/latency controls.

John Naguib lays out a practical architecture for building self-improving AI agents on Azure, focusing on controlled feedback loops (evaluate, learn, test, approve) rather than uncontrolled self-modification. The guide covers agent runtime, tool calling, RAG, memory/experience stores, evaluation, observability, and governance for production use.

John Edward explains how to apply FinOps practices to high-volume Azure AI workloads, focusing on the real cost drivers behind model usage, compute, and request patterns. The article lays out practical tactics—visibility, right-sizing, scaling, batching, caching, and guardrails—to keep AI spend predictable without sacrificing latency or reliability.