Event-Driven and Streaming Architectures

Module 1: Introduction to Event-driven Architectures

• Event-first Application, The motivations
• Event-driven Architectures
• Event-driven, Microservices
• Event-driven, Streaming applications
• The main characteristics
• Benefits and disadvantages
• The concepts of Microservices

Module 2: The fundamentals of an Event-driven Architecture

• The concept of Event Streams
• Event-driven microservices
• Event types and Event structures
• The principle of “Single Writer”

Module 3: Event Brokers

• The different models: queuing and Publish/Subscribe
• Introduction to Apache Kafka
• Introduction to Apache Pulsar
• Comparison of the two solutions

Module 4: Data schema management

• The notion of “Event-driven Contract”
• The event formats (Avro, Protobuf)
• Strategies to evolve schemas
• Modeling an Event, The best practices

Module 5: Integration patterns

• Building a migration strategy: Unidirectional Event-driven Architecture
• Data sourcing or Change Data Capture
• The “Query-based” pattern
• The “Log-based” pattern
• Limitations: Data consistency and schema dependencies
• Implementation of the Anti-Corruption Layer pattern
• Implementation of the Outbox Tables pattern
• The data consumption
• Introduction to Debezium
• The Frameworks Connect (Kafka and Pulsar)
• Impact on the organization: Dependencies and team responsibilities

Module 6: Event-driven, Streaming services

• Partitioned Event Streams
• Consumer Groups
• Assignment strategies and collocation of data
• Co-location of processing: Shuffling vs Re-partitioning
• Frameworks: Flink & Kafka Streams

Module 7: Event-driven, Microservices

• Communication patterns
• Interaction mechanisms
• Event Notification
• Event Carried State Transfer
• Event Chain
• Synchronous commands
• The Event-sourcing model
• What is Event-Sourcing?
• Event Store: Concepts and characteristics
• Command Query Responsibility Segregation (CQRS)
• The challenges

Module 8: Implementing Event-driven workflows

• Patterns to build processing lines
• Choreography
• Orchestration
• Distributed transactions
• Compensation mechanisms

Module 9: Event reprocessing and deterministic behavior

• The motivations for data reprocessing
• Idempotence and Processing Semantics
• The notion of time in an event stream
• How to manage retroactive event ?
• The challenges
• How to manage interactions with external systems ?
• Understanding the impacts of Query and Command
• Temporal Properties
• The Gateways
• Evolution of the source code
• Understanding the impacts
• Implement the pattern: Agreement Dispatcher

Module 10: Materializing event streams

• Motivations
• The different patterns (External, Internal, Global, Shared)
• Consistency

Module 11: Streaming SQL Databases

• What is a Streaming database ?
• The different solutions
• Confluent ksqlDB
• Materialize

Module 12: Modeling an Event System

• The different approaches
• The Event Modeling approach

Module 13: Standards and Specifications

• Traceability Open-tracing
• CloudEvents (CNCF)
• ASyncAPI