Official Documentation

Getting Started

  1. 8/28/2017, Mva
    This technology-agnostic course begins by explaining the benefits of distributed cloud applications with an emphasis on maintaining high-availability and scalability in a...
  2. 12/8/2017, Ebook
    This guide presents a structured approach for designing cloud applications that are scalable, resilient, and highly available. The guidance in this ebook is intended to help...
  3. 2/10/2017, Video, 0:56:41
    One of the benefits of cloud technology that is only just being realised is the greatly reduced risk profile and timelines it enables when designing and delivering robust,...
  4. 9/23/2015, Ebook
    This guide contains twenty-four design patterns and ten related guidance topics that articulate the benefits of applying patterns by showing how each piece can fit into the...
  5. 12/8/2017, Ebook
    We created The Developer’s Guide to Microsoft Azure to help you on your journey to the cloud, whether you’re just considering making the move, or you’ve already decided and...
  6. 5/20/2016, Ebook
    This guide breaks down the “why” and “how” for scenarios suited to the cloud with a focus on building apps using platform services available in Microsoft Azure. The second...

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Azure Documentation

1. Azure Architecture Center
2. Cloud Fundamentals
     2.1. Application architecture guide
          2.1.1. Introduction
          2.1.2. Architecture styles
      N-tier application
      Event-driven architecture
      Big data
      Big compute
          2.1.3. Choosing a compute service
      Decision tree
      Compute comparison
          2.1.4. Choosing a data store
      Data store comparison
          2.1.5. Design principles
      Design for self-healing
      Make all things redundant
      Minimize coordination
      Design to scale out
      Partition around limits
      Design for operations
      Use managed services
      Use the best data store for the job
      Design for evolution
      Build for the needs of business
          2.1.6. Pillars of software quality
          2.1.7. Best practices for cloud architectures
      API design
      API implementation
      Background jobs
      Content Delivery Network
      Data partitioning
      Monitoring and diagnostics
      Naming conventions
      Transient fault handling
      Retry guidance for specific services
     2.2. Data architecture guide
          2.2.1. Introduction
          2.2.2. Traditional RDBMS workloads
      Online transaction processing (OLTP)
      Data warehousing
      Online analytical processing (OLAP)
      Extract, transform, and load (ETL)
          2.2.3. Big data architectures
      Batch processing
      Real time processing
      Machine learning at scale
      Non-relational data stores
           Advanced analytics
           Data lakes
           Free-form text search
           Interactive data exploration
           Natural language processing
           Time series solutions
           Working with CSV and JSON files
      Technology choices
           Analytical data stores
           Analytics and reporting
           Batch processing
           Cognitive services
           Data storage
           Machine learning
           Natural language processing
           Pipeline orchestration
           Real-time message ingestion
           Search data stores
           Stream processing
          2.2.4. Cross-cutting concerns
      Data transfer
      Extending on-premises data solutions to the cloud
      Securing data solutions
     2.3. Cloud design patterns
          2.3.1. Overview
          2.3.2. Categories
      Data management
      Design and implementation
      Management and monitoring
      Performance and scalability
          2.3.3. Ambassador
          2.3.4. Anti-corruption Layer
          2.3.5. Backends for Frontends
          2.3.6. Bulkhead
          2.3.7. Cache-Aside
          2.3.8. Circuit Breaker
          2.3.9. Command and Query Responsibility Segregation (CQRS)
          2.3.10. Compensating Transaction
          2.3.11. Competing Consumers
          2.3.12. Compute Resource Consolidation
          2.3.13. Event Sourcing
          2.3.14. External Configuration Store
          2.3.15. Federated Identity
          2.3.16. Gatekeeper
          2.3.17. Gateway Aggregation
          2.3.18. Gateway Offloading
          2.3.19. Gateway Routing
          2.3.20. Health Endpoint Monitoring
          2.3.21. Index Table
          2.3.22. Leader Election
          2.3.23. Materialized View
          2.3.24. Pipes and Filters
          2.3.25. Priority Queue
          2.3.26. Queue-Based Load Leveling
          2.3.27. Retry
          2.3.28. Scheduler Agent Supervisor
          2.3.29. Sharding
          2.3.30. Sidecar
          2.3.31. Static Content Hosting
          2.3.32. Strangler
          2.3.33. Throttling
          2.3.34. Valet Key
     2.4. Performance antipatterns
          2.4.1. Overview
          2.4.2. Busy Database
          2.4.3. Busy Front End
          2.4.4. Chatty I/O
          2.4.5. Extraneous Fetching
          2.4.6. Improper Instantiation
          2.4.7. Monolithic Persistence
          2.4.8. No Caching
          2.4.9. Synchronous I/O
     2.5. Build microservices on Azure
          2.5.1. Introduction
          2.5.2. Domain analysis
          2.5.3. Identifying microservice boundaries
          2.5.4. Data considerations
          2.5.5. Interservice communication
          2.5.6. API design
          2.5.7. Ingestion and workflow
          2.5.8. API gateways
          2.5.9. Logging and monitoring
          2.5.10. CI/CD
     2.6. Manage multitenant identity
          2.6.1. Introduction
          2.6.2. The Tailspin scenario
          2.6.3. Authentication
          2.6.4. Claims-based identity
          2.6.5. Tenant sign-up
          2.6.6. Application roles
          2.6.7. Authorization
          2.6.8. Secure a web API
          2.6.9. Cache access tokens
          2.6.10. Client assertion
          2.6.11. Protect application secrets
          2.6.12. Federate with a customer's AD FS
          2.6.13. Run the Surveys application
     2.7. Migrate from Cloud Services to Service Fabric
          2.7.1. Migrate a Cloud Services application to Service Fabric
          2.7.2. Refactor a Service Fabric application
3. Example Scenarios
     3.1. Overview
     3.2. AI
          3.2.1. Image classification
     3.3. Apps
          3.3.1. Hotel reservation chatbot
          3.3.2. DevOps with Containers
          3.3.3. DevOps with VSTS
          3.3.4. SAP for Dev/Test
          3.3.5. E-commerce front-end
     3.4. Data & Analytics
          3.4.1. Real-time fraud detection
          3.4.2. Scalable order processing
     3.5. Infrastructure
          3.5.1. Multi-tier Windows
          3.5.2. HPC video rendering
4. Reference Architectures
     4.1. Overview
     4.2. App Service web application
          4.2.1. Basic web application
          4.2.2. Improved scalability
          4.2.3. Multi-region deployment
     4.3. Big data
          4.3.1. Enterprise BI with SQL Data Warehouse
          4.3.2. Automated enterprise BI with SQL Data Warehouse and Data Factory
     4.4. Hybrid networks
          4.4.1. Overview
          4.4.2. VPN
          4.4.3. ExpressRoute
          4.4.4. ExpressRoute with VPN failover
          4.4.5. Hub-spoke topology
          4.4.6. Hub-spoke topology with shared services
     4.5. Identity management
          4.5.1. Overview
          4.5.2. Integrate on-premises AD with Azure AD
          4.5.3. Extend AD DS to Azure
          4.5.4. Create an AD DS forest in Azure
          4.5.5. Extend AD FS to Azure
     4.6. N-tier application
          4.6.1. N-tier application with SQL Server
          4.6.2. Multi-region N-tier application
          4.6.3. N-tier application with Cassandra
          4.6.4. Deploy a Linux VM
          4.6.5. Deploy a Windows VM
     4.7. Network DMZ
          4.7.1. DMZ between Azure and on-premises
          4.7.2. DMZ between Azure and the Internet
          4.7.3. Highly available network virtual appliances
     4.8. SAP
          4.8.1. SAP NetWeaver for AnyDB
          4.8.2. SAP S/4HANA
          4.8.3. SAP HANA on Azure Large Instances
     4.9. Jenkins server
     4.10. SharePoint Server 2016
5. Design Review Framework
     5.1. Design for resiliency
     5.2. Failure mode analysis
     5.3. Availability checklist
     5.4. DevOps checklist
     5.5. Resiliency checklist (general)
     5.6. Resiliency checklist (Azure services)
     5.7. Scalability checklist
6. Cloud Adoption Guide
     6.1. Introduction
     6.2. Foundational Azure adoption
          6.2.1. Overview
          6.2.2. About Azure internals
      How does Azure work?
      What is cloud resource governance?
          6.2.3. About Azure resource access governance
      Understanding resource access management in Azure
      Azure governance design guide
          6.2.4. Deploying basic architectures to Azure
      Platform as a Service (PaaS) architecture
           Deploy a basic web application to Azure
           Best practices for web applications in Azure
      Infrastructure as a service (IaaS)
           What is an Azure virtual network?
           Deploy a virtual network to Azure
           Deploy a single Windows VM IaaS workload to Azure
           Best practices for deploying a Windows VM to Azure
           Deploy a single Linux VM IaaS workload to Azure
           Best practices for deploying a Linux VM to Azure
     6.3. Intermediate Azure adoption
          6.3.1. Overview
          6.3.2. Governance design guide
7. Azure Virtual Datacenter
8. Azure for AWS Professionals
     8.1. Overview
     8.2. Services comparison

Online Training Content

Date Title
8/28/2017 Architecting Distributed Cloud Applications
1/13/2015 Architecting Microsoft Azure Solutions


Tool Description


Date Title Length
How Microsoft AI defeated Ms Pacman
Inside Azure Datacenter Architecture with Mark Russinovich
Containers and Existing .NET Apps Part 2
Containers for Existing .NET Apps Part 1
Enable Edge Computing with Azure IoT Edge
Cloud Tech 10 - 11th December 2017 - Kubernetes, cloud-init, Cloud Foundry and more!
Cybersecurity Reference Architecture & Strategies: How to Plan for and Implement a Cybersecurity Strategy
Implement microservices patterns with .NET Core and Docker containers
Patterns, Architecture, & Best Practices: Scaling Machine Learning Algorithms with Azure
Deployment Techniques and Linux Containers with .NET Core 2.0

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