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Event-Driven and Streaming Architectures

Evolving to an event streaming architecture: The patterns and strategies to liberate your data

Price : 1850€ H.T. - per attendee

For more information about this training course, please free to contact :


During this instructor-led three-day hands-on you will learn the different patterns and strategies needed to implement a modern streaming event-driven architecture.

Course Objectives

This course enables participants to acquire the following skills:

  • Understand the different event-driven architectures.
  • Understanding the characteristics and benefits of event-driven architectures.
  • Implementing different data integration and inter-application communication patterns.
  • Modeling events and an event system.
  • Understand and use the different data streaming solutions.


60% theory, 40% practice

Who Should Attend ?

This workshop is designed for Application Developers, Architects and Data Engineers.

Course Duration

3 Days

Course Prerequisites

Participants should be familiar with Java development. No previous knowledge of Apache Kafka or Apache Pulsar is required.

Course Content

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