Visão Geral

O curso RabbitMQ com Streams de Eventos ensina como projetar, implementar e operar pipelines orientados a eventos de alta performance usando RabbitMQ Streams. Os alunos aprenderão desde os fundamentos até práticas avançadas, incluindo escalabilidade, particionamento, monitoramento, retenção, offsets, replay e integração com microserviços e ferramentas de processamento de dados em tempo real.

Objetivo

Após realizar este curso RabbitMQ com Streams de Eventos, você será capaz de:

• Entender profundamente o modelo de Streams do RabbitMQ
• Criar pipelines completos orientados a eventos
• Configurar, operar e monitorar stream queues
• Construir produtores e consumidores de alto throughput
• Trabalhar com offsets, retenção e replay de eventos
• Implementar Super Streams para alta escalabilidade
• Projetar integrações event-driven entre microserviços
• Criar arquiteturas robustas de streaming de dados

Publico Alvo

• Desenvolvedores backend
• Engenheiros de software
• Arquitetos de soluções
• Engenheiros DevOps e SRE
• Especialistas em integração e mensageria
• Profissionais que trabalham com dados em tempo real

Pre-Requisitos

•  
• Noções de mensageria e AMQP
• Noções de containers (Docker)
• Experiência em alguma linguagem (Python, Java, Node.js ou Go)
• Noções de microserviços
•  

Materiais

Conteúdo Programatico

Module 1 – Event Streaming Fundamentals (3 hours)

1. What are events and event streams
2. Event-driven architecture principles
3. Comparing Message Queues vs Event Streams
4. RabbitMQ architecture refresher
5. When to use RabbitMQ Streams

Module 2 – RabbitMQ Streams Deep Dive (3 hours)

1. How Streams work internally
2. Segments, indexes, retention policies
3. Sequential write architecture
4. Advantages over traditional AMQP queues
5. Hands-on: Exploring stream structure

Module 3 – Installing & Configuring RabbitMQ Streams (2 hours)

1. Installing RabbitMQ with streams enabled
2. Configuring plugins and tuning parameters
3. Storage, durability, disk usage
4. Hands-on: Setting up a full stream environment

Module 4 – Stream Producers (3 hours)

1. Producer API architecture
2. Batching, compression, flow control
3. Exactly-once publishing and idempotence
4. Error handling and retries
5. Hands-on: Building a high-throughput producer

Module 5 – Stream Consumers (3 hours)

1. Offset-based consumption
2. Replay strategies
3. Consumer groups and horizontal scaling
4. Backpressure and flow management
5. Hands-on: Implementing high-speed consumers

Module 6 – Super Streams & Partitioning (3 hours)

1. What are Super Streams
2. Partitioning strategies and event keys
3. Scaling consumers and producers
4. Ensuring ordering guarantees
5. Hands-on: Creating a partitioned Super Stream

Module 7 – Event Processing & Data Pipelines (2 hours)

1. Filtering, aggregation, enrichment
2. Using RabbitMQ with ETL and analytics tools
3. Building real-time pipelines
4. Hands-on: Event transformation exercises

Module 8 – Microservices Integration (2 hours)

1. Event-driven microservices patterns
2. Designing asynchronous workflows
3. Using streams as event logs
4. Saga and outbox patterns with RabbitMQ Streams
5. Hands-on: Microservice integration lab

Module 9 – Monitoring & Observability (2 hours)

1. Stream metrics and monitoring
2. Prometheus + Grafana dashboards
3. Detecting consumer lag
4. Troubleshooting performance issues
5. Hands-on: Observability lab

Module 10 – Scaling & Advanced Operations (2 hours)

1. Auto-scaling consumers
2. Stream storage scaling and disk optimization
3. Changing retention without downtime
4. Backup/restore and disaster recovery
5. Hands-on: Performance tuning scenarios

Module 11 – Real-World Case Studies (1 hour)

1. IoT streaming
2. Log ingestion
3. E-commerce event pipelines
4. Financial transaction streaming
5. Clickstream analytics

Module 12 – Final Project (2 hours)

1. Build a complete end-to-end event streaming solution:
2. Producer
3. Consumer
4. Partitioned Super Stream
5. Retention & offsets
6. Monitoring dashboards
7. Event processing flow