Empowering Disaster Recovery for Azure VMs with Azure Site Recovery and Terraform
Discover how to ensure business continuity and achieve disaster recovery for your Azure Virtual Machines with ease. Learn how to integrate seamlessly with Azure Site Recovery using Terraform, providing a simple, secure, and cost-effective way to replicate VMs across regions. Stay prepared for any outage with a failover process that keeps your apps running, all while paying only for storage and traffic to the secondary region. Don't miss this opportunity to fortify your VM infrastructure and maintain uninterrupted operations!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 by modules. I.E.: Just day 1 of AZ-104, using filters in Visio and selecting modules 1-3 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 Released Updated Contents Video Overview Demo Deploy AZ-104 Azure Administrator Associate Blueprint Template 12/14/2023 10/28/2024 Contents Module 01 Microsoft Trainer Demo Deploy AZ-204 Azure Developer Associate Blueprint Template 11/05/2024 11/11/2024 Contents Microsoft Trainer Demo Deploy AZ-500 Azure Security Engineer Associate Blueprint Template+ 01/09/2024 10/10/2024 Contents Microsoft Trainer Demo Deploy AZ-700 Azure Network Engineer Associate Blueprint Template 01/25/2024 11/04/2024 Contents Microsoft Trainer Demo Deploy SC-300 Identity and Access Administrator Associate Blueprint Template 10/10/2024 Contents Specialty PDF Visio Released Updated AZ-140 Azure Virtual Desktop Specialty Blueprint Template 01/03/2024 02/27/2025 Contents Expert level PDF Visio Released Updated AZ-305 Designing Microsoft Azure Infrastructure Solutions Blueprint Template+ AZ-104 AZ-204 AZ-700 AZ-140 05/07/2024 02/05/2025 Contents Microsoft Trainer Demo Deploy SC-100 Microsoft Cybersecurity Architect Blueprint [PDF] Template+ AZ-500 SC-300 10/10/2024 Contents Skill based Credentialing PDF Visio Released Updated AZ-1002 Configure secure access to your workloads using Azure virtual networking Blueprint Blueprint Template 05/27/2024 Contents AZ-1003 Secure storage for Azure Files and Azure Blob Storage Blueprint Template 02/07/2024 02/05/2024 Contents 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. Introduction to Course Blueprint for Trainers [10 minutes + comments] Real life demo AZ-104 Advanced Networking section [3 minutes] Visio stencils Azure icons - Azure Architecture Center | Microsoft Learn AZ-104 Overview of Mod 01 using Azure Course Blueprint __ Practical Scenario Demo with Demo Deploy To enhance your learning experience, we're linking Demo Deploy with Azure Course Blueprints. This tool will allow you to: See Practical Applications: Understand how different portions of the course content are applied in real-world scenarios. Contextual Learning: Visualize where each topic fits within the larger Azure ecosystem and the specific context of the course. This integration ensures a comprehensive and practical approach to learning, making it easier to grasp and apply the concepts covered in the course. Microsoft Trainer Demo Deploy ___ Subscribe if you want to get notified of any update like new releases or updates. My email ilan.nyska@microsoft.com LinkedIn https://www.linkedin.com/in/ilan-nyska/ Please consider sharing your anonymous feedback <-- Thank you for your support!Demystifying Azure OpenAI Networking for Secure Chatbot Deployment
Embark on a technical exploration of Azure's networking features for building secure chatbots. In this article, we'll dive deep into the practical aspects of Azure's networking capabilities and their crucial role in ensuring the security of your OpenAI deployments. With real-world use cases and step-by-step instructions, you'll gain practical insights into optimizing Azure and OpenAI for your projects.
Availability Zone Resiliency on Ecommerce Reference Application
The Resilient Ecommerce Reference Application is a synthetic workload that mirrors a simple, bare-bones, e-commerce platform. The purpose of it is to demonstrate how to use Azure Resiliency best practices to achieve availability during zonal outages or components outages.Announcing comprehensive guidance for AI adoption and architecture
The pace of AI innovation is moving incredibly fast with new models and solutions emerging regularly. To meet the pace of technological advancements, organizations are striving to meet the demand for scalable, efficient AI solutions. The rapidity of change places enormous pressure on organizations to scale quickly while also ensuring reliability, security, performance and cost-efficiency needs are met along the way. According to Rand Research, over 80% of early AI adoptions fail because customers miss critical steps in preparing their organizations to consider all aspects of building and running AI workloads. Microsoft is committed to helping organizations successfully navigate this journey of cloud and AI transformation. Over the past 18 months, Microsoft has published design patterns, baseline reference architectures, application landing zones, and a variety of Azure service guides for Azure OpenAI workloads. We have also developed specific financial best practices, as well as pricing and cost management features to make it easier to optimize AI investments. This guidance and features have been pulled together within Azure Essentials. Azure Essentials brings together curated best practices and product experiences from customers and partners along with reference architectures, skilling, tools, and resources into a single destination to help you maximize the value of your cloud investments. The Azure Essentials resource kit includes detailed guidance tailored to specific use cases and business scenarios including achieving secure migration, activating your data for AI innovation, and building and modernizing AI applications. As you prepare to adopt AI at scale, the guidance within the Azure Essentials resource kit helps you become AI-ready. This week, we are excited to announce industry-leading guidance for AI adoption and architectural design. This guidance ties together all of the content from the past 18 months into a comprehensive methodical approach that sets up the organization for AI success, while ensuring that AI workloads are well-architected. Through thousands of customer engagements focused on AI adoption, teams of Microsoft cloud solution architects, product engineers and content developers have developed specific guidance for the Microsoft Cloud Adoption Framework for Azure (CAF) and Microsoft Azure Well-Architected Framework (WAF). As a result, all of the recommendations and best practices are based on customer-proven experience that future customers can count on. New: Cloud Adoption Framework (CAF) – AI scenario The AI scenario within the Cloud Adoption Framework provides prescriptive guidance that prepares organizations to adopt AI at scale. Over the past nine months, we’ve had over 100 Microsoft’s solution architects contribute their AI adoption knowledge to this guidance. The result of this collaboration is a roadmap comprised of checklists that are segmented for “Startups” or “Enterprises”. These checklists make it possible to start your adoption at any phase, while also double-checking that you haven’t missed anything along the way. One hallmark of this guidance is the technology strategy decision tree. It provides very succinct and consumable logic to decide which AI technology works best for your specific AI strategy. To see the full tree, click on this link. Most (if not all) customers want to implement and adopt AI responsibly. The ramifications and risk of not doing so are just too costly. Thus, the CAF methodologies have also been adapted to Responsible AI principles so organizations can build an AI foundation that supports the design, governance, and ongoing management of responsible AI workloads. It helps users with everything from developing an adoption strategy through managing AI workloads in production. NEW: Well-Architected Framework (WAF) – AI workloads The AI workload guidance within the Azure Well-Architected Framework is a new set of best practices that allows AI architects to meet the functional and non-functional requirements for reliability, security, performance efficiency, operational excellence, and cost optimization. Designed to instill confidence in workload teams to make intelligent decisions when designing their AI workloads, the new WAF guidance for AI workloads takes a broader view covering architectural considerations at all levels of the stack, including infrastructure, data layers, and application logic. Thus, you’ll find guidance about each of the WAF pillars blended into all levels. The WAF AI enhancements we’re announcing this week build upon the Azure Well-Architected Framework refresh we launched last year. We’ve added checklists and tradeoffs to all pillars which helps make the guidance more actionable for workload teams, including solution architects, DevOps engineers, and data scientists. And the WAF components are more actionable through workload designs, reference architectures, assessments, Azure Advisor recommendations, and Azure service guides. The WAF AI workload guidance also covers both traditional machine learning and generative AI architectures – ensuring comprehensive support for your AI projects. Prepare to scale your AI adoption We are confident that this comprehensive guidance will support your organization in building and deploying AI solutions responsibly and effectively. Stay tuned for more updates and resources to help you on your AI adoption journey. The CAF and WAF AI adoption and architecture guidance makes it possible to adopt AI at scale while fully aligning to Trustworthy AI principles. This guidance is also embedded within Azure Essentials which provides detailed step-by-step guidance through the AI adoption journey, thus providing organizations with a clear path to maximize the value of their AI investment. As you prepare to become AI-ready, these are some great resources to get you started. Access the Cloud Adoption Framework for AI scenario documentation to get the guidance you need to ensure you’re ready to adopt AI at scale. Leverage the Azure Well-Architected Framework for AI workloads documentation to obtain the necessary guidance to securely design, build and manage your AI workloads. Discover comprehensive skilling with free, self-paced Azure AI Plans on Learn to further develop your Azure adoption skills so you can begin your AI adoption journey with confidence. Learn more about Azure Innovate and Azure Migrate and Modernize and Azure Essentials to understand how they can help you accelerate AI adoption and drive innovation in your business. Ready to take action? Connect with Microsoft Azure sales or reach out to a qualified partner. If you have a Unified Contract with Microsoft Support, there are multiple engagements opportunities that are based on CAF and WAF to help you accelerate your Azure and AI deployments.
Example Reference Network Topologies for API Management in private mode.
Learn about suggested Network example topologies thought to follow Vnet integration practices within the API management. Therefore, these revolve around API management in internal mode. API Management in internal mode requires a Premium SKU or Development (not recommended for production).AI Studio End-to-End Baseline Reference Implementation
Discover the Future of AI Deployment with Azure AI Studio’s Baseline Reference Implementation Azure AI Studio is reshaping the landscape of cloud AI integration with its commitment to operational excellence and strategic alignment with core business objectives. We are thrilled to introduce Azure AI Studio’s end-to-end baseline reference implementation—a streamlined architecture crafted for seamless, scalable, and secure AI cloud deployments. Embark on a journey to deploy sophisticated AI workloads with confidence, supported by Azure AI Studio's robust baseline architecture. Whether it's hosting interactive AI playgrounds, constructing complex AI workflows with Promptflow, or ensuring resilient and secure deployments within Azure's managed network environment, this implementation is your blueprint for success. Embrace a new era of AI innovation where security and scalability converge with organizational compliance and governance. Join us in deploying tomorrow's AI solutions, today.
