I just bought this book and I'm completely blown away. I teach some of the patterns found inside to regional technology leaders and graduate students, but this book provides a new level of clarity.
Author Cornelia Davis likes to say that "the cloud" is more about how you design your applications than where you deploy them. Cloud Native: Designing Change-tolerant Software is 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 sets them apart. In it, you'll find realistic examples and expert advice for working with apps, data, services, routing, and more.
Table of Contents takes you straight to the bookdetailed table of contents
Part 1: The Cloud-native Context: What are we Designing to? Defined
1. You Keep Using that Word: Defining Cloud
1.1. It’s Not Amazon’s Fault
1.2. Today’s Application Requirements
1.2.1. Zero Downtime
1.2.2. Shortened Feedback Cycles
1.2.3. Mobile and Multi-Device Support
1.2.4. Connected Devices — Also Known as the Internet of Things
1.2.5. Data-Driven
1.3. Cloud-Native Software
1.3.1. Defining Cloud-Native
1.3.2. Cloud-Native Software — The Pieces and Parts
1.3.3. A Model for Cloud-Native Software
1.3.4. Cloud-Native Software in Action
1.4. Cloud, Cloud-Native, None of the Above and Somewhere In-Between
1.5. Summary
2. Running Cloud-Native Applications in Production
2.1. The Obstacles
2.1.1. Snowflakes
2.1.2. Risky Deployments
2.1.3. Change Is the Exception
2.1.4. Production Instability
2.2. The Enablers
2.2.1. Continuous Delivery
2.2.2. Repeatability
2.2.3. Safe Deployments
2.2.4. Change Is the Rule
2.3. Summary
3. The Platform for Cloud-Native Software
3.1. The Cloud(-/native) Platform Evolution
3.2. Cloud-Native Dial Tone
3.3. The Platform Supports the Entire SDLC
3.4. Enable Operational Excellence
3.4.1. Repeatability
3.4.2. Security, Change-Control, Compliance (the Control Functions)
3.4.3. Autonomy
3.4.4. Reliability
3.5. Support Microservice-Based Software Architectures
3.5.1. Multi-Tenancy
3.5.2. That Which Is Distributed Once Was Not
3.6. Summary
Part 2: Cloud-Native Foundations
4. It’s not Just Request/Response
4.1. We are (Usually) Taught Imperative Programming
4.2. (Re)Introducing Event-driven Computing
4.3. My Global Cookbook
4.3.1. Request/Response
4.3.2. Event-driven
4.4. Different Styles, Similar Challenges
4.5. Summary
5. Scale Out and Statelessness
5.1. Cloud-native Apps Have Many Instances Deployed
5.2. Stateful Apps in the Cloud
5.2.1. Decomposing the Monolith and Binding to the Database
5.2.2. Poorly Handling Session State
5.3. HTTP Sessions and Sticky Sessions
5.4. Stateful Services and Stateless Apps
5.4.1. Stateful Services are Special Services
5.4.2. Making Apps Stateless
5.5. Summary
6. Application Configuration: Not Just Environment Variables
6.1. Why are we even talking about config?
6.1.1. Contextual Variability Through the SDLC
6.1.2. Contextual Variability From Horizontal Scaling
6.1.3. Contextual Variability From Infrastructure Changes
6.1.4. Contextual Variability Through, Well, the Need to Change Something
6.2. Configuration in the Application Source
6.3. Bringing in System Values
6.4. Bringing in Application Configuration
6.5. Summary
7. The Application Lifecycle
7.1. App Lifecycle Impacts
7.2. Single App, Multiple Instances
7.2.1. Blue/Green Deployments
7.2.2. Rolling Upgrades
7.3. Coordinating Across Different Apps
7.4. Example: Credential Rotation and App Lifecycle
7.5. Dealing with Ephemeral Runtime Environments
7.6. Visibility of App Lifecycle State
7.6.1. Example: Health Endpoints and Probes
7.7. Serverless
7.8. Summary
8. Accessing Apps: Services, Routing and Service Discovery
8.1. The Service Abstraction
8.1.1. Service Example: Googling
8.1.2. Service Example: Our Blog Aggregator
8.2. Dynamic Routing
8.2.1. Server-side Load Balancing
8.2.2. Client-side Load Balancing
8.2.3. Route Freshness
8.3. Service Discovery
8.3.1. Service Discovery on the Web
8.3.2. Service Discovery with Client-side Load-balancing
8.3.3. Service Discovery in Kubernetes
8.4. Example: Using Service Discovery
8.5. Summary
9. Resilient Interactions: Retries and Other Control Loops
9.1. Request Retries
9.1.1. The Basic Request Retry
9.1.2. Retries: What Could Go Wrong?
9.1.3. Creating a Retry Storm
9.1.4. Avoiding Retry Storms: Kind Clients
9.1.5. When Not to Retry
9.2. Fallback Logic
9.3. Control Loops in General
9.3.1. Controlling the Control Loop
9.4. Summary
10. Fronting Services: Circuit Breakers and API Gateways
10.1. Circuit Breakers
10.1.1. The Software Circuit Breaker
10.1.2. Implementing a Circuit Breaker
10.2. API Gateways
10.2.1. The Case for API Gateways in Cloud Native Software
10.2.2. API Gateway Topology
10.3. The Service Mesh
10.3.1. The Sidecar
10.3.2. The Control Plane
10.4. Summary
11. Troubleshooting: Needle in the Haystack
12. Cloud-native Data: Breaking the Data Monolith
About the Technology
We are amid a radical change in how we design and build applications. With cloud platforms like AWS, Azure, and Google Cloud, even small teams can take full advantage of web-scale distributed application patterns and practice. Users and customers have higher expectations for reliability, availability, and performance. Cloud-native software promises near-zero downtime, shortened feedback cycles, multi-device support, and improved cost control. All this means developers need to learn new skills and techniques, along with a new way of thinking about application design.What's inside
- The application lifecycle of Cloud Native apps
- Automated configuration management
- Multi-tenant services, versioned services, and parallel deploys
- Understanding Cloud Native Routing
- Managing dependencies between apps and services
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Great introduction material that provides answers to all questions that come up when getting involved into cloud native development.