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Spis treści

Designing Distributed Systems. 2nd Edition eBook -- spis treści

• Preface
  • Who Should Read This Book
  • Why I Wrote This Book
  • The World of Distributed Systems Today
  • Navigating This Book
  • Conventions Used in This Book
  • Online Resources
  • Using Code Examples
  • OReilly Online Learning
  • How to Contact Us
  • Acknowledgments
• I. Foundational Concepts
• 1. Introduction
  • A Brief History of Systems Development
  • A Brief History of Patterns in Software Development
    • Formalization of Algorithmic Programming
    • Patterns for Object-Oriented Programming
    • The Rise of Open Source Software
  • The Value of Patterns, Practices, and Components
    • Standing on the Shoulders of Giants
    • A Shared Language for Discussing Our Practice
    • Shared Components for Easy Reuse
  • Summary
• 2. Important Distributed System Concepts
  • APIs and RPCs
  • Latency
  • Reliability
  • Percentiles
  • Idempotency
  • Delivery Semantics
  • Relational Integrity
  • Data Consistency
  • Orchestration and Kubernetes
  • Health Checks
  • Summary
• II. Single-Node Patterns
• 3. The Sidecar Pattern
  • An Example Sidecar: Adding HTTPS to a Legacy Service
  • Dynamic Configuration with Sidecars
  • Modular Application Containers
    • Hands On: Deploying the topz Container
  • Building a Simple PaaS with Sidecars
  • Designing Sidecars for Modularity and Reusability
    • Parameterized Containers
    • Define Each Containers API
    • Documenting Your Containers
  • Summary
• 4. Ambassadors
  • Using an Ambassador to Shard a Service
    • Hands On: Implementing a Sharded Redis
  • Using an Ambassador for Service Brokering
  • Using an Ambassador to Do Experimentation or Request Splitting
    • Hands On: Implementing 10% Experiments
  • Summary
• 5. Adapters
  • Monitoring
    • Hands On: Using Prometheus for Monitoring
  • Logging
    • Hands On: Normalizing Different Logging Formats with fluentd
  • Adding a Health Monitor
    • Hands On: Adding Rich Health Monitoring for MySQL
  • Summary
• III. Serving Patterns
• 6. Replicated Load-Balanced Services
  • Stateless Services
    • Readiness Probes for Load Balancing
    • Hands On: Creating a Replicated Service in Kubernetes
  • Session Tracked Services
  • Application-Layer Replicated Services
  • Introducing a Caching Layer
    • Deploying Your Cache
    • Hands On: Deploying the Caching Layer
  • Expanding the Caching Layer
    • Rate Limiting and Denial-of-Service Defense
    • SSL Termination
    • Hands On: Deploying nginx and SSL Termination
  • Summary
• 7. Sharded Services
  • Sharded Caching
    • Why You Might Need a Sharded Cache
    • The Role of the Cache in System Performance
    • Replicated Sharded Caches
    • Hands On: Deploying an Ambassador and Memcache for a Sharded Cache
  • An Examination of Sharding Functions
    • Selecting a Key
    • Consistent Hashing Functions
    • Hands On: Building a Consistent HTTP Sharding Proxy
  • Sharded Replicated Serving
  • Hot Sharding Systems
  • Summary
• 8. Scatter/Gather
  • Scatter/Gather with Root Distribution
    • Hands On: Distributed Document Search
  • Scatter/Gather with Leaf Sharding
    • Hands On: Sharded Document Search
    • Choosing the Right Number of Leaves
  • Scaling Scatter/Gather for Reliability and Scale
  • Summary
• 9. Functions and Event-Driven Processing
  • Determining When FaaS Makes Sense
    • The Benefits of FaaS
    • The Challenges of FaaS
    • The Need for Background Processing
    • The Need to Hold Data in Memory
    • The Costs of Sustained Request-Based Processing
  • Patterns for FaaS
    • The Decorator Pattern: Request or Response Transformation
    • Hands On: Adding Request Defaulting Prior to Request Processing
    • Handling Events
    • Hands On: Implementing Two-Factor Authentication
    • Event-Based Pipelines
    • Hands On: Implementing a Pipeline for New User Signup
  • Summary
• 10. Ownership Election
  • Determining If You Even Need Leader Election
  • The Basics of Leader Election
    • Hands On: Deploying etcd
    • Implementing Locks
    • Hands On: Implementing Locks in etcd
    • Implementing Ownership
    • Hands On: Implementing Leases in etcd
  • Handling Concurrent Data Manipulation
  • Summary
• IV. Batch Computational Patterns
• 11. Work Queue Systems
  • A Generic Work Queue System
    • The Source Container Interface
    • Work Queue API
    • The Worker Container Interface
    • The Shared Work Queue Infrastructure
  • Hands On: Implementing a Video Thumbnailer
  • Dynamic Scaling of the Workers
  • The Multiworker Pattern
  • Summary
• 12. Event-Driven Batch Processing
  • Patterns of Event-Driven Processing
    • Copier
    • Filter
    • Splitter
    • Sharder
    • Merger
  • Hands On: Building an Event-Driven Flow for New User Signup
  • Publisher/Subscriber Infrastructure
  • Hands On: Deploying Kafka
  • Resiliency and Performance in Work Queues
    • Work Stealing
    • Errors, Priority, and Retry
  • Summary
• 13. Coordinated Batch Processing
  • Join (or Barrier Synchronization)
  • Reduce
    • Hands On: Count
    • Sum
    • Histogram
    • Hands On: An Image Tagging and Processing Pipeline
  • Summary
• V. Universal Concepts
• 14. Monitoring and Observability Patterns
  • Monitoring and Observability Basics
    • Logging
    • Metrics
    • Basic Request Monitoring
    • Advanced Request Monitoring
    • Alerting
      • Basic alerting
      • Alerting on anomolies
    • Tracing
  • Aggregating Information
  • Summary
• 15. AI Inference and Serving
  • The Basics of AI Systems
  • Hosting a Model
  • Distributing a Model
  • Development with Models
  • Retrieval-Augmented Generation
  • Testing and Deployment
  • Summary
• 16. Common Failure Patterns
  • The Thundering Herd
  • The Absence of Errors Is an Error
  • Client and Expected Errors
  • Versioning Errors
  • The Myth of Optional Components
  • Oops, We Cleaned Up Everything
  • Challenges with the Breadth of Inputs
  • Processing Obsolete Work
  • The Second System Problem
  • Summary
• Conclusion: A New Beginning?
• Index