Event-Driven Microservices and Data Streaming Training Course

 Event-Driven Microservices and Data Streaming Training Course 

Introduction 

Event-Driven Microservices and Data Streaming Training Course provides advanced knowledge and practical skills in designing, developing, deploying, and managing scalable distributed applications using event-driven architecture (EDA) and microservices technologies. The programme explores modern software engineering principles, asynchronous communication, distributed messaging, real-time data streaming, event processing, and cloud-native application development. Participants gain practical exposure to Apache Kafka, Apache Flink, RabbitMQ, Kafka Streams, Docker, and Kubernetes to develop resilient, loosely coupled, and high-performance enterprise systems. The course emphasizes event sourcing, Command Query Responsibility Segregation (CQRS), application programming interfaces, service discovery, distributed transactions, and real-time data integration to support enterprise digital transformation. 

The training further examines how organizations implement event-driven microservices to improve operational efficiency, system interoperability, data synchronization, and real-time business intelligence. Participants explore cloud-native deployment, streaming analytics, distributed system security, fault tolerance, performance optimization, and automated application monitoring. Through practical exercises and international industry case studies, the course demonstrates applications in banking, telecommunications, healthcare, e-commerce, logistics, and manufacturing. Participants develop the competencies required to build enterprise-grade microservices, optimize streaming pipelines, manage distributed data environments, and implement reliable real-time information systems. 

Course Objectives 

By the end of the training, participants will be able to: 

1. Understand event-driven architecture and distributed computing principles.
2. Design scalable microservices and cloud-native applications.
3. Develop real-time data streaming pipelines.
4. Configure Apache Kafka and distributed messaging platforms.
5. Implement event sourcing and CQRS design patterns.
6. Apply asynchronous communication between microservices.
7. Manage distributed transactions and data consistency.
8. Implement Apache Flink for real-time stream processing.
9. Deploy containerized applications using Docker and Kubernetes.
10. Configure API gateways and service discovery mechanisms.
11. Strengthen distributed application security and data governance.
12. Implement observability using modern monitoring technologies.
13. Optimize event-driven systems for enterprise scalability and performance.

Organizational Benefits
 

1. Improved enterprise application scalability and flexibility.
2. Faster real-time data processing and decision-making.
3. Reduced application downtime and operational disruptions.
4. Enhanced enterprise system integration and interoperability.
5. Improved customer experiences through responsive applications.
6. Reduced software development and maintenance complexity.
7. Stronger cybersecurity and distributed data management.
8. Increased operational efficiency through automation.
9. Improved business intelligence and predictive analytics.
10. Accelerated digital transformation and technology innovation.

Target Audiences
 

1. Software developers and microservices engineers.
2. Data engineers and streaming specialists.
3. Cloud architects and DevOps engineers.
4. Enterprise solutions architects.
5. Database administrators and data architects.
6. IT infrastructure and systems administrators.
7. Technical project managers and IT consultants.
8. Business intelligence and application integration professionals.

Course Duration: 5 days

Course Modules

Module 1: Foundations of Event-Driven Architecture
 

• Event-driven architecture principles and distributed systems.
• Event producers, consumers, brokers, and messaging channels.
• Synchronous and asynchronous communication patterns.
• Event schemas, serialization, and message formats.
• Event-driven application architecture and integration.
• Case study: Uber's event-driven systems for real-time transportation services.

Module 2: Microservices Architecture and Design Patterns
 

• Microservices principles, service decomposition, and bounded contexts.
• Domain-Driven Design and service autonomy.
• API gateways, service discovery, and inter-service communication.
• Circuit breakers, retries, and fault-tolerant application design.
• Microservices integration and distributed application management.
• Case study: Amazon's microservices architecture for scalable e-commerce.

Module 3: Apache Kafka and Distributed Messaging
 

• Apache Kafka architecture, brokers, topics, and partitions.
• Producers, consumers, and consumer groups.
• Message retention, replication, and fault tolerance.
• Kafka Connect, Schema Registry, and serialization.
• Distributed messaging and event delivery optimization.
• Case study: LinkedIn's use of Kafka for large-scale event streaming.

Module 4: Real-Time Data Streaming and Stream Processing
 

• Real-time data ingestion and continuous event processing.
• Apache Flink and Kafka Streams implementation.
• Event-time processing, windows, and state management.
• Streaming transformations, filtering, and aggregation.
• Real-time analytics and streaming pipeline optimization.
• Case study: Financial institutions applying streaming analytics for fraud detection.

Module 5: Event Sourcing and Distributed Data Management
 

• Event sourcing principles and event store architecture.
• Command Query Responsibility Segregation (CQRS).
• Distributed transactions and Saga design patterns.
• Event replay, snapshots, and data consistency.
• Distributed data synchronization and management.
• Case study: Banking transaction systems using event-driven data management.

Module 6: Cloud-Native Microservices and Deployment
 

• Containerization and application packaging using Docker.
• Kubernetes orchestration and microservices management.
• Cloud deployment and scalable streaming infrastructure.
• Continuous Integration and Continuous Deployment (CI/CD).
• Automated application deployment and infrastructure management.
• Case study: Spotify's microservices-based engineering practices.

Module 7: Security, Monitoring, and Observability
 

• Authentication, authorization, and secure service communication.
• Encryption, access control, and event data protection.
• Distributed tracing, logging, and performance monitoring.
• Prometheus, Grafana, and OpenTelemetry implementation.
• Fault detection, incident management, and system reliability.
• Case study: Financial technology platforms implementing secure distributed systems.

Module 8: Enterprise Integration and Performance Optimization
 

• Enterprise application integration and event-driven interoperability.
• Streaming pipeline optimization and latency management.
• Scalability, load balancing, and resource allocation.
• Data governance, schema evolution, and system reliability.
• Enterprise streaming architecture design and implementation.
• Case study: Walmart's real-time data systems for retail operations.

Training Methodology
 

• Instructor-led presentations and interactive technical discussions.
• Practical demonstrations using Apache Kafka and Apache Flink.
• Hands-on microservices development and configuration exercises.
• International industry case studies and group assignments.
• Simulation of distributed messaging and streaming environments.
• Practical projects, troubleshooting, and performance evaluation.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.
 
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
 
c. Course duration is flexible and the contents can be modified to fit any number of days.
 
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
 
e. One-year post-training support Consultation and Coaching provided after the course.
 f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.