Cloud Native Patterns: Designing change-tolerant software

by Cornelia Davis

Overview

Summary

Cloud Native Patternsis your guide to developing strong applications that thrive in the dynamic, distributed, virtual world of the cloud. This book presents a mental model for cloud-native applications, along with the patterns, practices, and tooling that set them apart.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

Cloud platforms promise the holy grail: near-zero downtime, infinite scalability, short feedback cycles, fault-tolerance, and cost control. But how do you get there? By applying cloudnative designs, developers can build resilient, easily adaptable, web-scale distributed applications that handle massive user traffic and data loads. Learn these fundamental patterns and practices, and you'll be ready to thrive in the dynamic, distributed, virtual world of the cloud.

About the Book

With 25 years of experience under her belt, Cornelia Davis teaches you the practices and patterns that set cloud-native applications apart. With realistic examples and expert advice for working with apps, data, services, routing, and more, she shows you how to design and build software that functions beautifully on modern cloud platforms. As you read, you will start to appreciate that cloud-native computing is more about the how and why rather than the where.

What's inside

• The lifecycle of cloud-native apps
• Cloud-scale configuration management
• Zero downtime upgrades, versioned services, and parallel deploys
• Service discovery and dynamic routing
• Managing interactions between services, including retries and circuit breakers

About the Reader

Requires basic software design skills and an ability to read Java or a similar language.

About the Author

Cornelia Davis is Vice President of Technology at Pivotal Software. A teacher at heart, she's spent the last 25 years making good software and great software developers.

Table of Contents

PART 1 - THE CLOUD-NATIVE CONTEXT
1. You keep using that word: Defining "cloud-native"
2. Running cloud-native applications in production
3. The platform for cloud-native software
PART 2 - CLOUD-NATIVE PATTERNS
4. Event-driven microservices: It's not just request/response
5. App redundancy: Scale-out and statelessness
6. Application configuration: Not just environment variables
7. The application lifecycle: Accounting for constant change
8. Accessing apps: Services, routing, and service discovery
9. Interaction redundancy: Retries and other control loops
10. Fronting services: Circuit breakers and API gateways
11. Troubleshooting: Finding the needle in the haystack
12. Cloud-native data: Breaking the data monolith

Product Details

ISBN-13:	9781617294297
Publisher:	Manning
Publication date:	05/31/2019
Edition description:	1st Edition
Pages:	400
Product dimensions:	7.30(w) x 9.10(h) x 0.80(d)

About the Author

Cornelia Davis is Vice President of Technology at Pivotal Software. A teacher at heart, she's spent the last 25 years making good software and great software developers.

Table of Contents

Foreword xv

Preface xvii

Acknowledgments xix

About this book xxi

About the author xxv

About the cover illustration xxvi

Part 1 The Cloud-Native Context 1

1 You keep using that word: Defining "cloud-native" 3

1.1 Today's application requirements 7

Zero downtime 7

Shortened feedback cycles 7

Mobile and multidevice support 8

Connected devices-also known as the Internet of Things 8

Data-driven 9

1.2 Introducing cloud-native software 10

Defining "cloud-native" 10

A mental model for cloud-native software 12

Cloud-native software in action 17

1.3 Cloud-native and world peace 21

Cloud and cloud-native 21

What isn't cloud-native 22

Cloud-native plays nice 23

2 Running cloud-native applications in production 26

2.1 The obstacles 27

Snowflakes 29

Risky defrayments 30

Change is the exception 34

Production instability 34

2.2 The enablers 35

Continuous delivery 36

Repeatability 40

Safe deployments 44

Change is the rule 48

3 The platform for cloud-native software 51

3.1 The cloud (-native) platform evolution 52

It started with the cloud 53

Cloud-native dial tone 54

3.2 Core tenets of the cloud-native platform 57

First, let's talk about containers 58

Support for "constantly changing" 59

Support for "highly distributed" 62

3.3 Who does what? 65

3.4 More cloud-native platform capabilities 68

The platform supports the entire SDLC 68

Security, change-control, compliance (the control functions) 71

Controlling what goes into the container 73

Upgrading and patching vulnerabilities 75

Change control 77

Part 2 Cloud-Native Patterns 81

4 Event-driven microservices: It's not just request/response 83

4.1 We're (usually) taught imperative programming 84

4.2 Reintroducing event-driven computing 86

4.3 My global cookbook 87

Request/response 88

Event-driven 94

4.4 Introducing Command Query Responsibility Segregation 103

4.5 Different styles, similar challenges 105

5 App redundancy: Scale-out and statelessness 108

5.1 Cloud-native apps have many instances deployed 110

5.2 Stateful apps in the cloud 112

Decomposing the monolith and binding to the database 112

Poorly handling session state 115

5.3 HTTP sessions and sticky sessions 129

5.4 Stateful services and stateless apps 131

Stateful services are special services 131

Making apps stateless 133

6 Application configuration: Not just environment variables 139

6.1 Why are we even talking about config? 140

Dynamic scaling-increasing and decreasing the number of app instances 141

Infrastructure changes causing configuration changes 141

Updating application configuration with zero downtime 142

6.2 The app's configuration layer 144

6.3 Injecting system/environment values 148

Let's see this in action: Using ENV variables for configuration 148

6.4 Injecting application configuration 157

Introducing the configuration server 158

Security adds more requirements 165

Let's see this in action: Application configuration using a config server 166

7 The application lifecycle: Accounting for constant change 170

7.1 Having empathy for operations 172

7.2 Single-app lifecycle, multiple-instance lifecycles 173

Blue/green upgrades 176

Rolling upgrades 178

Parallel deployments 179

7.3 Coordinating across different app lifecycles 181

7.4 Let's see this in action: Credential rotation and app lifecycle 185

7.5 Dealing with ephemeral runtime environments 194

7.6 Visibility of app lifecycle state 196

Let's see this in action: Health endpoints and probes 201

7.7 Serverless 204

8 Accessing apps: Services, routing, and service discovery 207

8.1 The service abstraction 210

Service example: Googling 211

Service example: Our blog aggregator 213

8.2 Dynamic routing 214

Sewer-side load balancing 214

Client-side load balancing 215

Route freshness 216

8.3 Service discovery 219

Service discovery on the web 222

Service discovery with client-side load balancing 223

Service discovery in Kubernetes 224

Let's see this in action: Using service discovery 226

9 Interaction redundancy: Retries and other control loops 231

9.1 Request retries 233

The basic request retry 233

Let's see this in action: Simple retries 234

Retries: what could go wrong? 238

Creating a retry storm 240

Let's see this in action: Creating a retry storm 240

Avoiding retry storms: Kind clients 250

Let's see this in action: being a kinder client 251

When not to retry 256

9.2 Fallback logic 257

Let's see this in action: Implementing fallback logic 257

9.3 Control loops 263

Understanding types of control loops 263

Controlling the control loop 264

10 Fronting services: Circuit breakers and API gateways 267

10.1 Circuit breakers 269

The software circuit breaker 269

Implementing a circuit breaker 272

10.2 API gateways 284

The case for API gateways in cloud-native software 286

API gateway topology 286

10.3 The service mesh 289

The sidecar 289

The control plane 292

11 Troubleshooting: Finding the needle in the haystack 295

11.1 Application logging 296

11.2 Application metrics 300

Pulling metrics from cloud-native applications 302

Pushing metrics from cloud-native applications 304

11.3 Distributed tracing 306

Tracer output 310

Assembling traces via Zipkin 313

Implementation details 317

12 Cloud-native data: Breaking the data monolith 320

12.1 Every microservice needs a cache 323

12.2 Moving from request/response to event driven 326

12.3 The event log 328

Let's see this in action: Implementing event-driven microservices 330

What's new with topics and queues? 343

The event payload 347

Idempotency 348

12.4 Event sourcing 349

The journey, so far 349

The source of truth 351

Let's see this in action: Implementing event sourcing 353

12.5 We're just scratching the surface 356

Index 359