Azure Course Blueprints
Overview The Course Blueprint is a comprehensive visual guide to the Azure ecosystem, integrating all the resources, tools, structures, and connections covered in the course into one inclusive diagram. It enables students to map out and understand the elements they've studied, providing a clear picture of their place within the larger Azure ecosystem. It serves as a 1:1 representation of all the topics officially covered in the instructor-led training. Formats available include PDF, Visio, Excel, and Video. Links: Each icon in the blueprint has a hyperlink to the pertinent document in the learning path on Learn. Layers: You have the capability to filter layers to concentrate on segments of the course Integration: The Visio Template+ for expert courses like SC-100 and AZ-305 includes an additional layer that enables you to compare SC-100, AZ-500, and SC-300 within the same diagram. Similarly, you can compare any combination of AZ-305, AZ-700, AZ-204, and AZ-104 to identify differences and study gaps. Since SC-300 and AZ-500 are potential prerequisites for the expert certification associated with SC-100, and AZ-204 or AZ-104 for the expert certification associated with AZ-305, this comparison is particularly useful for understanding the extra knowledge or skills required to advance to the next level. Advantages for Students Defined Goals: The blueprint presents learners with a clear vision of what they are expected to master and achieve by the course’s end. Focused Learning: By spotlighting the course content and learning targets, it steers learners’ efforts towards essential areas, leading to more productive learning. Progress Tracking: The blueprint allows learners to track their advancement and assess their command of the course material. Topic List: A comprehensive list of topics for each slide deck is now available in a downloadable .xlsx file. Each entry includes a link to Learn and its dependencies. Download links Associate Level PDF Visio Contents Video Overview AZ-104 Azure Administrator Associate R: 12/14/2023 U: 04/16/2025 Blueprint Visio Excel Mod 01 AZ-204 Azure Developer Associate R: 11/05/2024 U: 11/11/2024 Blueprint Visio Excel AZ-500 Azure Security Engineer Associate R: 01/09/2024 U: 10/10/2024 Blueprint Visio+ Excel AZ-700 Azure Network Engineer Associate R: 01/25/2024 U: 11/04/2024 Blueprint Visio Excel SC-200 Security Operations Analyst Associate R: 04/03/2025 U:04/09/2025 Blueprint Visio Excel SC-300 Identity and Access Administrator Associate R: 10/10/2024 Blueprint Excel Specialty PDF Visio AZ-140 Azure Virtual Desktop Specialty R: 01/03/2024 U: 02/27/2025 Blueprint Visio Excel Expert level PDF Visio AZ-305 Designing Microsoft Azure Infrastructure Solutions R: 05/07/2024 U: 02/05/2025 Blueprint Visio+ AZ-104 AZ-204 AZ-700 AZ-140 Excel SC-100 Microsoft Cybersecurity Architect R: 10/10/2024 U: 04/09/2025 Blueprint Visio+ AZ-500 SC-300 SC-200 Excel Skill based Credentialing PDF AZ-1002 Configure secure access to your workloads using Azure virtual networking R: 05/27/2024 Blueprint Visio Excel AZ-1003 Secure storage for Azure Files and Azure Blob Storage R: 02/07/2024 U: 02/05/2024 Blueprint Excel Subscribe if you want to get notified of any update like new releases or updates. Author: Ilan Nyska, Microsoft Technical Trainer My email ilan.nyska@microsoft.com LinkedIn https://www.linkedin.com/in/ilan-nyska/ I’ve received so many kind messages, thank-you notes, and reshares — and I’m truly grateful. But here’s the reality: 💬 The only thing I can use internally to justify continuing this project is your engagement — through this survey https://lnkd.in/gnZ8v4i8 ⏳ Unless I receive enough support via this short survey, the project will be sunset. Thank you for your support! ___ Benefits for Trainers: Trainers can follow this plan to design a tailored diagram for their course, filled with notes. They can construct this comprehensive diagram during class on a whiteboard and continuously add to it in each session. This evolving visual aid can be shared with students to enhance their grasp of the subject matter. Explore Azure Course Blueprints! | Microsoft Community Hub Visio stencils Azure icons - Azure Architecture Center | Microsoft Learn ___ Are you curious how grounding Copilot in Azure Course Blueprints transforms your study journey into smarter, more visual experience: 🧭 Clickable guides that transform modules into intuitive roadmaps 🌐 Dynamic visual maps revealing how Azure services connect ⚖️ Side-by-side comparisons that clarify roles, services, and security models Whether you're a trainer, a student, or just certification-curious, Copilot becomes your shortcut to clarity, confidence, and mastery. Navigating Azure Certifications with Copilot and Azure Course Blueprints | Microsoft Community HubHow To Use Okta for Azure API Management Developer Portal Authentication
Today there are many organizations around the world that leverage the rich capabilities of the Microsoft Identity Platform. Often these organizations also need to integrate with third-party identity platforms. In this post, I will demonstrate the flexibility of the Microsoft Identity Platform and how it can be used to integrate a third-party identity provider (Okta) with our Azure API Management service.Build image with containerised self-hosted Azure DevOps agent and private Azure Container Registry
Do you want to know how to use containerized self-hosted agents for Azure Pipelines? In this blog post, you will discover the benefits, challenges, and solutions of running your self-hosted agents in a container. You will also see a proof of concept that demonstrates how to build container images using Azure Container Registry and Azure Container Instances. Read on to find out how you can improve your CI/CD workflow with containerization.
Selecting the Right Agentic Solution on Azure - Part 1
Recently, we have seen a surge in requests from customers and Microsoft partners seeking guidance on building and deploying agentic solutions at various scales. With the rise of Generative AI, replacing traditional APIs with agents has become increasingly popular. There are several approaches to building, deploying, running, and orchestrating agents on Azure. In this discussion, I will focus exclusively on Azure-specific tools, services, and methodologies, setting aside Copilot and Copilot Studio for now. This article describes the options available as of today. 1. Azure OpenAI Assistants API: This feature within Azure OpenAI Service enables developers to create conversational agents (“assistants”) based on OpenAI models (such as GPT-3.5 and GPT-4). It supports capabilities like memory, tool/function calls, and retrieval (e.g., document search). However, Microsoft has already deprecated version 1 of the Azure OpenAI Assistants API, and version 2 remains in preview. Microsoft strongly recommends migrating all existing Assistants API-based agents to the Agent Service. Additionally, OpenAI is retiring the Assistants API and advises developers to use the modern “Response” API instead (see migration detail). Given these developments, it is not advisable to use the Assistants API for building agents. Instead, you should use the Azure AI Agent Service, which is part of Azure AI Foundry. 2. Workflows with AI agents and models in Azure Logic Apps (Preview) – As the name suggests, this feature is currently in public preview and is only available with Logic Apps Standard, not with the consumption plan. You can enhance your workflow by integrating agentic capabilities. For example, in a visa processing workflow, decisions can be made based on priority, application type, nationality, and background checks using a knowledge base. The workflow can then route cases to the appropriate queue and prepare messages accordingly. Workflows can be implemented either as chat assistant or APIs. If your project is workflow-dependent and you are ready to implement agents in a declarative way, this is a great option. However, there are currently limited choices for models and regional availability. For CI/CD, there is an Azure Logic Apps Standard template available for VS Code you can use. 3. Azure AI Agent Service – Part of Azure AI Foundry, the Azure AI Agent Service allows you to provision agents declaratively from the UI. You can consume various OpenAI models (with support for non-OpenAI models coming soon) and leverage important tools or knowledge bases such as files, Azure AI Search, SharePoint, and Fabric. You can connect agents together and create hierarchical agent dependencies. SDKs are available for building agents within agent services using Python, C#, or Java. Microsoft manages the infrastructure to host and run these agents in isolated containers. The service offers role-based access control, MS Entra ID integration, and options to bring your own storage for agent states and Azure Key Vault keys. You can also incorporate different actions including invoking a Logic App instance from your agent. There is also option to trigger an agent using Logic Apps (preview). Microsoft recommends using Agent Service/Azure Foundry as the destination for agents, as further enhancements and investments are focused here. 4. Agent Orchestrators – There are several excellent orchestrators available, such as LlamaIndex, LangGraph, LangChain, and two from Microsoft—Semantic Kernel and AutoGen. These options are ideal if you need full control over agent creation, hosting, and orchestration. They are developer-only solutions and do not offer a UI (barring AutoGen Studio having some UI assistance). You can create complex, multi-layered agent connections. You can then host and run these agents in you choice of Azure services like AKS or Apps Service. Additionally, you have the option to create agents using Agent Service and then orchestrate them with one of these orchestrators. Choosing the Right Solution The choice of agentic solution depends on several factors, including whether you prefer code or no-code approaches, control over the hosting platform, customer needs, scalability, maintenance, orchestration complexity, security, and cost. Customer Need: If agents need to be part of a workflow, use AI Agents in Logic Apps; otherwise, consider other options. No-Code: For workflow-based agents, Logic Apps is suitable; for other scenarios, Azure AI Agent Service is recommended. Hosting and Maintenance: If Logic Apps is not an option and you prefer not to maintain your own environment, use Azure AI Agent Service. Otherwise, consider custom agent orchestrators like Semantic Kernel or AutoGen to build the agent and services like AKS or Apps Service to host those. Orchestration Complexity: For simple hierarchical agent connections, Azure AI Agent Service is good choice. For complex orchestration, use an agent orchestrator. Versioning - If you are concerned about versioning to ensure solid CI/CD regime then you may have to chose Agent Orchestrators. Agent Service still miss this feature clarity. We have some work-around but it is not robust implementation. Hopefully we will catch up soon with a better versioning solution. Summary: When selecting the right agentic solution on Azure, consider the latest recommendations and platform developments. For most scenarios, Microsoft advises using the Azure AI Agent Service within Azure Foundry, as it is the focus of ongoing enhancements and support. For workflow-driven projects, Azure Logic Apps with agentic capabilities may be suitable, while advanced users can leverage orchestrators for custom agent architectures. In Selecting the Right Agentic Solution on Azure – Part 2 (Security) blog we will examine the security aspects of each option, one by one.Creating an Media Upload Workflow using Azure Storage, Logic Apps and Media Services
Over the last two months, I’ve engaged with a few media companies who wanted to learn how to integrate Azure Media Services into their workflow. Azure Media Services (AMS) offers a whole range of media capabilities for content ingest, storage, transcoding, video AI, encryption, dynamic packaging, and delivery – be it for live streaming or VOD through a single or multi-CDN.
