rabbitmq/rabbitmq-tutorials

Features

• Message Brokers - Demonstrates how to use a message broker to remove direct dependencies between distributed services.
• Message Broker Clusters - Includes detailed instructions for setting up and managing high availability RabbitMQ clusters on Kubernetes.
• Distributed Task Queues - Provides code examples for distributing background tasks across multiple worker nodes to balance processing loads.
• Distributed Task Workers - Teaches how to spread heavy workloads across multiple parallel workers to increase throughput.
• Broker High Availability - Provides documentation and examples for deploying high availability broker clusters on Kubernetes.
• High Availability Clustering - Coordinates multiple broker nodes to ensure continuous availability and distributed processing.
• High Availability Clusters - Provides guides for configuring multi-node clusters to ensure service continuity and fault tolerance.
• Messaging Patterns - Provides a comprehensive collection of educational resources for implementing asynchronous messaging patterns.
• Messaging Protocol Tutorials - Serves as a collection of runnable code examples and guides for implementing asynchronous messaging patterns.
• Consumer Group Coordinators - Implements patterns for distributing messages across multiple parallel workers to balance processing loads.
• Topic Routing Patterns - Demonstrates selective data distribution using routing keys and pattern-based message routing.
• Event-Driven Architectures - Guides the construction of reactive systems using broadcast messages and selective routing.
• Messaging Patterns - Implements practical communication strategies such as request-reply and pub-sub for coordinating data flow between services.
• Request Correlation Tokens - Implements request-reply patterns using unique correlation identifiers over asynchronous channels.
• Consumer Offset Trackers - Provides examples of tracking consumer positions within message streams to allow resuming processing.
• High-Throughput Data Streaming - Provides examples of using specialized stream protocol clients to handle large-scale data throughput.
• Message Routing - Implements routing keys to deliver messages to specific queues so consumers receive only relevant data.
• Multi-Language Client Libraries - Provides official client libraries for multiple programming languages to interact with the message broker.
• Kubernetes Cluster Orchestration - Provides automation for deploying and managing broker clusters using Kubernetes operators.
• Queue-Specific Metrics - Explains how to use the HTTP API to retrieve detailed statistics like message rates and memory usage for specific queues.
• Broadcast Messaging - Demonstrates how to send a single message to multiple subscribers simultaneously to notify various systems.
• Messaging Client Connections - Implements standard protocols and secure transport for establishing messaging client connections.
• Delivery Confirmations - Implements mechanisms to track whether a message successfully reached the broker to prevent data loss.
• Stream Offset Tracking - Demonstrates how to record a consumer's position within a stream to resume processing from a specific point.
• Language-Agnostic APIs - Enables communication between services written in different languages using standard protocols and official libraries.
• Request-Response Pattern Support - Provides a pattern for sending requests and waiting for specific responses to simulate synchronous communication.
• Message Broker Monitoring - Provides guides on tracking message throughput and latency using Prometheus and built-in visualization tools.
• Prometheus-Based Metric Exporters - Demonstrates how to expose RabbitMQ node, connection, and queue metrics in a Prometheus-compatible format.
• RabbitMQ Performance Monitoring - Provides guides for monitoring RabbitMQ broker resource utilization, including memory alarms and disk space statistics.

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