Microsoft - Cloud Application Architecture Guide

Index

• Overview vii
• Introduction viii
• Chapter 1: Choose an architecture style 1
• A quick tour of the styles 2
• Architecture styles as constraints 4
• Consider challenges and benefits 5
• Chapter 1a: N-tier architecture style 6
• When to use this architecture 7
• Benefits 7
• Challenges 7
• Best practices 8
• N-tier architecture on virtual machines 8
• Additional considerations 9
• Chapter 1b: Web-Queue-Worker architecture style 10
• When to use this architecture 11
• Benefits 11
• Challenges 11
• Best practices 11
• Web-Queue-Worker on Azure App Service 12
• Additional considerations 12
• Chapter 1c: Microservices architecture style 14
• When to use this architecture 15
• Benefits 15
• Challenges 16
• Best practices 17
• Microservices using Azure Container Service 19
• Chapter 1d: CQRS architecture style 20
• When to use this architecture 21
• Benefits 21
• Challenges 22
• Best practices 22
• CQRS in microservices 22
• Contents
• iii
• Chapter 1e: Event-driven architecture style 24
• When to use this architecture 25
• Benefits 25
• Challenges 25
• IoT architectures 26
• Chapter 1f: Big data architecture style 27
• Benefits 29
• Challenges 29
• Best practices 30
• Chapter 1g: Big compute architecture style 31
• When to use this architecture 32
• Benefits 32
• Challenges 32
• Big compute using Azure Batch 33
• Big compute running on Virtual Machines 33
• Chapter 2: Choose compute and data store technologies 35
• Chapter 2a: Overview of compute options 37
• Chapter 2b: Compute comparison 39
• Hosting model 39
• DevOps 40
• Scalability 41
• Availability 41
• Security 42
• Other 42
• Chapter 2c: Data store overview 43
• Relational database management systems 44
• Key/value stores 44
• Document databases 45
• Graph databases 46
• Column-family databases 47
• Data analytics 48
• Search Engine Databases 48
• Time Series Databases 48
• Object storage 49
• Shared files 49
• Chapter 2d: Data store comparison 50
• Criteria for choosing a data store 50
• General Considerations 50
• Relational database management systems (RDBMS) 52
• Document databases 53
• Key/value stores 54
• Contents
• iv
• Graph databases 55
• Column-family databases 56
• Search engine databases 57
• Data warehouse 57
• Time series databases 58
• Object storage 58
• Shared files 59
• Chapter 3: Design your Azure application: design principles 60
• Chapter 3a: Design for self healing 62
• Recommendations 62
• Chapter 3b: Make all things redundant 64
• Recommendations 64
• Chapter 3c: Minimize coordination 66
• Recommendations 67
• Chapter 3d: Design to scale out 69
• Recommendations 69
• Chapter 3e: Partition around limits 71
• Recommendations 72
• Chapter 3f: Design for operations 73
• Recommendations 73
• Chapter 3g: Use managed services 75
• Chapter 3h: Use the best data store for the job 76
• Recommendations 77
• Chapter 3i: Design for evolution 78
• Recommendations 78
• Chapter 3j: Build for the needs of business 80
• Recommendations 80
• Chapter 3k: Designing resilient applications for Azure 82
• What is resiliency? 82
• Process to achieve resiliency 83
• Defining your resiliency requirements 83
• Designing for resiliency 87
• Resiliency strategies 87
• Resilient deployment 91
• Monitoring and diagnostics 92
• Manual failure responses 93
• Summary 94
• Chapter 4: Design your Azure application: Use these pillars of quality 95
• Scalability 96
• Availability 98
• Resiliency 99
• Contents
• v
• Management and DevOps 100
• Security 101
• Chapter 5: Design your Azure application: Design patterns 103
• Challenges in cloud development 103
• Data Management 104
• Design and Implementation 104
• Messaging 105
• Management and Monitoring 106
• Performance and Scalability 107
• Resiliency 108
• Security 109
• Chapter 6: Catalog of patterns 110
• Ambassador pattern 110
• Anti-Corruption Layer pattern 112
• Backends for Frontends pattern 114
• Bulkhead pattern 116
• Cache-Aside pattern 119
• Circuit Breaker pattern 124
• CQRS pattern 132
• Compensating Transaction pattern 139
• Competing Consumers pattern 143
• Compute Resource Consolidation pattern 148
• Event Sourcing pattern 156
• External Configuration Store pattern 162
• Federated Identity pattern 170
• Gatekeeper pattern 174
• Gateway Aggregation pattern 176
• Gateway Offloading pattern 180
• Gateway Routing pattern 182
• Health Endpoint Monitoring pattern 185
• Index Table pattern 191
• Leader Election pattern 197
• Materialized View pattern 204
• Pipes and Filters pattern 208
• Priority Queue pattern 215
• Queue-Based Load Leveling pattern 221
• Retry pattern 224
• Scheduler Agent Supervisor pattern 227
• Sharding pattern 234
• Sidecar pattern 243
• Contents
• vi
• Static Content Hosting pattern 246
• Strangler pattern 250
• Throttling pattern 252
• Valet Key pattern 256
• Chapter 7: Design review checklists 263
• DevOps checklist 264
• Availability checklist 270
• Scalability checklist 276
• Resiliency checklist 276
• Azure services 286
• Chapter 8: Summary 291
• Chapter 9: Azure reference architectures 292
• Identity management 293
• Hybrid network 298
• Network DMZ 303
• Managed web application 306
• Running Linux VM workloads 310
• Running Windows VM workloads 315

Total Pages: 333

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