کتاب ساخت میکروسرویس‌های رویدادمحور

چرا میکروسرویس‌های رویدادمحور

What Are Event-Driven Microservices? • Introduction to Domain-Driven Design and Bounded Contexts • Leveraging Domain Models and Bounded Contexts • Aligning Bounded Contexts with Business Requirements • Communication Structures • Business Communication Structures • Implementation Communication Structures • Data Communication Structures • Conway’s Law and Communication Structures • Communication Structures in Traditional Computing • Option 1: Make a New Service • Option 2: Add It to the Existing Service • Pros and Cons of Each Option • The Team Scenario, Continued • Conflicting Pressures • Event-Driven Communication Structures • Events Are the Basis of Communication • Event Streams Provide the Single Source of Truth • Consumers Perform Their Own Modeling and Querying • Data Communication Is Improved Across the Organization • Accessible Data Supports Business Communication Changes • Asynchronous Event-Driven Microservices • Example Team Using Event-Driven Microservices • Synchronous Microservices • Drawbacks of Synchronous Microservices • Benefits of Synchronous Microservices • Summary

مبانی میکروسرویس رویدادمحور

Building Topologies • Microservice Topology • Business Topology • The Contents of an Event • The Structure of an Event • Unkeyed Event • Entity Event • Keyed Event • Materializing State from Entity Events • Event Data Definitions and Schemas • Microservice Single Writer Principle • Powering Microservices with the Event Broker • Event Storage and Serving • Additional Factors to Consider • Event Brokers Versus Message Brokers • Consuming from the Immutable Log • Providing a Single Source of Truth • Managing Microservices at Scale • Putting Microservices into Containers • Putting Microservices into Virtual Machines • Managing Containers and Virtual Machines • Paying the Microservice Tax • Summary

قراردادهای ارتباطی و داده‌ای

Event-Driven Data Contracts • Using Explicit Schemas as Contracts • Schema Definition Comments • Full-Featured Schema Evolution • Code Generator Support • Breaking Schema Changes • Selecting an Event Format • Designing Events • Tell the Truth, the Whole Truth, and Nothing but the Truth • Use a Singular Event Definition per Stream • Use the Narrowest Data Types • Keep Events Single-Purpose • Minimize the Size of Events • Involve Prospective Consumers in the Event Design • Avoid Events as Semaphores or Signals • Summary

ادغام معماری‌های رویدادمحور با سیستم‌های موجود

What Is Data Liberation? • Compromises for Data Liberation • Converting Liberated Data to Events • Data Liberation Patterns • Data Liberation Frameworks • Liberating Data by Query • Bulk Loading • Incremental Timestamp Loading • Autoincrementing ID Loading • Custom Querying • Incremental Updating • Benefits of Query-Based Updating • Drawbacks of Query-Based Updating • Liberating Data Using Change-Data Capture Logs • Benefits of Using Data Store Logs • Drawbacks of Using Data Base Logs • Liberating Data Using Outbox Tables • Performance Considerations • Isolating Internal Data Models • Ensuring Schema Compatibility • Capturing Change-Data Using Triggers • Making Data Definition Changes to Data Sets Under Capture • Handling After-the-Fact Data Definition Changes for the Query and CDC Log Patterns • Handling Data Definition Changes for Change-Data Table Capture Patterns • Sinking Event Data to Data Stores • The Impacts of Sinking and Sourcing on a Business • Summary

مبانی پردازش رویدادمحور

Composing Stateless Topologies • Transformations • Branching and Merging Streams • Repartitioning Event Streams • Example: Repartitioning an Event Stream • Copartitioning Event Streams • Example: Copartitioning an Event Stream • Assigning Partitions to a Consumer Instance • Assigning Partitions with the Partition Assignor • Assigning Copartitioned Partitions • Partition Assignment Strategies • Recovering from Stateless Processing Instance Failures • Summary

پردازش قطعی جریان

Determinism with Event-Driven Workflows • Timestamps • Synchronizing Distributed Timestamps • Processing with Timestamped Events • Event Scheduling and Deterministic Processing • Custom Event Schedulers • Processing Based on Event Time, Processing Time, and Ingestion Time • Timestamp Extraction by the Consumer • Request-Response Calls to External Systems • Watermarks • Watermarks in Parallel Processing • Stream Time • Stream Time in Parallel Processing • Out-of-Order and Late-Arriving Events • Late Events with Watermarks and Stream Time • Causes and Impacts of Out-of-Order Events • Time-Sensitive Functions and Windowing • Handling Late Events • Reprocessing Versus Processing in Near-Real Time • Intermittent Failures and Late Events • Producer/Event Broker Connectivity Issues • Summary and Further Reading

جریان‌سازی با وضعیت

State Stores and Materializing State from an Event Stream • Recording State to a Changelog Event Stream • Materializing State to an Internal State Store • Materializing Global State • Advantages of Using Internal State • Disadvantages of Using Internal State • Scaling and Recovery of Internal State • Materializing State to an External State Store • Advantages of External State • Drawbacks of External State • Scaling and Recovery with External State Stores • Rebuilding Versus Migrating State Stores • Rebuilding • Migrating • Transactions and Effectively Once Processing • Example: Stock Accounting Service • Effectively Once Processing with Client-Broker Transactions • Effectively Once Processing Without Client-Broker Transactions • Summary

ساخت گردش کار با میکروسرویس‌ها

The Choreography Pattern • A Simple Event-Driven Choreography Example • Creating and Modifying a Choreographed Workflow • Monitoring a Choreographed Workflow • The Orchestration Pattern • A Simple Event-Driven Orchestration Example • A Simple Direct-Call Orchestration Example • Comparing Direct-Call and Event-Driven Orchestration • Creating and Modifying an Orchestration Workflow • Monitoring the Orchestration Workflow • Distributed Transactions • Choreographed Transactions: The Saga Pattern • Orchestrated Transactions • Compensation Workflows • Summary

میکروسرویس‌ها با استفاده از تابع به عنوان سرویس

Designing Function-Based Solutions as Microservices • Ensure Strict Membership to a Bounded Context • Commit Offsets Only After Processing Has Completed • Less Is More • Choosing a FaaS Provider • Building Microservices Out of Functions • Cold Start and Warm Starts • Starting Functions with Triggers • Triggering Based on New Events: The Event-Stream Listener • Triggering Based on Consumer Group Lag • Triggering on a Schedule • Triggering Using Webhooks • Triggering on Resource Events • Performing Business Work with Functions • Maintaining State • Functions Calling Other Functions • Event-Driven Communication Pattern • Direct-Call Pattern • Termination and Shutdown • Tuning Your Functions • Allocating Sufficient Resources • Batch Event-Processing Parameters • Scaling Your FaaS Solutions • Summary

میکروسرویس‌های پایه تولیدکننده و مصرف‌کننده

Where Do BPCs Work Well? • Integration with Existing and Legacy Systems • Stateful Business Logic That Isn’t Reliant Upon Event Order • When the Data Layer Does Much of the Work • Independent Scaling of the Processing and Data Layer • Hybrid BPC Applications with External Stream Processing • Example: Using an External Stream-Processing Framework to Join Event Streams • Summary

میکروسرویس‌های فریم‌ورک‌های سنگین

A Brief History of Heavyweight Frameworks • The Inner Workings of Heavyweight Frameworks • Benefits and Limitations • Cluster Setup Options and Execution Modes • Use a Hosted Service • Build Your Own Full Cluster • Create Clusters with CMS Integration • Application Submission Modes • Driver Mode • Cluster Mode • Handling State and Using Checkpoints • Scaling Applications and Handling Event Stream Partitions • Scaling an Application While It Is Running • Scaling an Application by Restarting It • Autoscaling Applications • Recovering from Failures • Multitenancy Considerations • Languages and Syntax • Choosing a Framework • Example: Session Windowing of Clicks and Views • Summary

میکروسرویس‌های فریم‌ورک‌های سبک‌وزن

Benefits and Limitations • Lightweight Processing • Handling State and Using Changelogs • Scaling Applications and Recovering from Failures • Event Shuffling • State Assignment • State Replication and Hot Replicas • Choosing a Lightweight Framework • Apache Kafka Streams • Apache Samza: Embedded Mode • Languages and Syntax • Stream-Table-Table Join: Enrichment Pattern • Summary

ادغام میکروسرویس‌های رویدادمحور و درخواست-پاسخ

Handling External Events • Autonomously Generated Events • Reactively Generated Events • Handling Autonomously Generated Analytical Events • Integrating with Third-Party Request-Response APIs • Processing and Serving Stateful Data • Serving Real-Time Requests with Internal State Stores • Serving Real-Time Requests with External State Stores • Handling Requests Within an Event-Driven Workflow • Processing Events for User Interfaces • Micro-Frontends in Request-Response Applications • The Benefits of Microfrontends • Composition-Based Microservices • Easy Alignment to Business Requirements • Drawbacks of Microfrontends • Potentially Inconsistent UI Elements and Styling • Varying Microfrontend Performance • Example: Experience Search and Review Application • Summary

ابزارهای پشتیبان

Microservice-to-Team Assignment System • Event Stream Creation and Modification • Event Stream Metadata Tagging • Quotas • Schema Registry • Schema Creation and Modification Notifications • Offset Management • Permissions and Access Control Lists for Event Streams • State Management and Application Reset • Consumer Offset Lag Monitoring • Streamlined Microservice Creation Process • Container Management Controls • Cluster Creation and Management • Programmatic Bringup of Event Brokers • Programmatic Bringup of Compute Resources • Cross-Cluster Event Data Replication • Programmatic Bringup of Tooling • Dependency Tracking and Topology Visualization • Topology Example • Summary

آزمایش میکروسرویس‌های رویدادمحور

General Testing Principles • Unit-Testing Topology Functions • Stateless Functions • Stateful Functions • Testing the Topology • Testing Schema Evolution and Compatibility • Integration Testing of Event-Driven Microservices • Local Integration Testing • Create a Temporary Environment Within the Runtime of Your Test Code • Create a Temporary Environment External to Your Test Code • Integrate Hosted Services Using Mocking and Simulator Options • Integrate Remote Services That Have No Local Options • Full Remote Integration Testing • Programmatically Create a Temporary Integration Testing Environment • Testing Using a Shared Environment • Testing Using the Production Environment • Choosing Your Full-Remote Integration Testing Strategy • Summary

استقرار میکروسرویس‌های رویدادمحور

Principles of Microservice Deployment • Architectural Components of Microservice Deployment • Continuous Integration, Delivery, and Deployment Systems • Container Management Systems and Commodity Hardware • The Basic Full-Stop Deployment Pattern • The Rolling Update Pattern • The Breaking Schema Change Pattern • Eventual Migration via Two Event Streams • Synchronized Migration to the New Event Stream • The Blue-Green Deployment Pattern • Summary

نتیجه‌گیری

Communication Layers • Business Domains and Bounded Contexts • Shareable Tools and Infrastructure • Schematized Events • Data Liberation and the Single Source of Truth • Microservices • Microservice Implementation Options • Testing • Deploying • Final Words