Visão Geral
O curso RabbitMQ com Streams apresenta aos alunos o novo modelo de streaming introduzido pelas versões modernas do RabbitMQ, permitindo o processamento de eventos em alta velocidade, retenção prolongada de mensagens e consumo incremental. Os participantes aprenderão a construir pipelines de dados, integrar aplicações usando o protocolo de streams e aplicar casos de uso como análise em tempo real, ETL orientado a eventos e comunicação assíncrona de microserviços.
Conteúdo Programatico
Module 1 – Introduction to RabbitMQ Streams
- Overview of RabbitMQ streaming architecture
- Why Streams? Differences between Streams and AMQP queues
- Stream queue characteristics: retention, offsets, partitions
- Use cases for event streaming with RabbitMQ
Module 2 – Installing and Configuring RabbitMQ with Streams
- Enabling the RabbitMQ Streams plugin
- Configuration for performance and durability
- Stream storage engine: files, segments, retention policies
- Understanding stream partitions and scalability
Module 3 – Stream Producers
- Producer API overview
- Creating high-throughput producers
- Message batching and compression
- Idempotency and delivery guarantees
- Lab: Writing a producer application
Module 4 – Stream Consumers
- Types of consumers: single, superstream, offset-based
- Tracking offsets and replaying messages
- Consumer groups and load balancing
- High-performance consumption patterns
- Lab: Building a consumer application
Module 5 – Super Streams
- What is a Super Stream
- Creating partitioned streams
- Routing strategies and partition keys
- Scaling producers and consumers across partitions
- Lab: Implementing a Super Stream
Module 6 – Integrating RabbitMQ Streams
- Integrating with microservices
- Using Streams with Python, Java, Node.js, and Go
- Connecting RabbitMQ Streams with Kafka/ETL pipelines
- Bridges, connectors, and streaming pipelines
Module 7 – Monitoring and Observability
- Monitoring streams with RabbitMQ Management
- Using Prometheus + Grafana
- Detecting bottlenecks and tuning throughput
- Troubleshooting stream queue issues
Module 8 – Advanced Operations
- Stream retention policies
- Backup and disaster recovery
- Scaling storage and consumers
- Performance tuning best practices
Module 9 – Real-World Architecture
- Event-driven architectures with RabbitMQ Streams
- Stream processing patterns
- Using RabbitMQ for logs, metrics, clickstream, IoT, and analytics
- Case studies and architecture examples
Module 10 – Final Hands-On Project
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Building a complete streaming pipeline using producers, consumers, partitions, and monitoring tools