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* Fatih: Add Cloud Design Patterns instructions for distributed systems architecture * Convert Cloud Design Patterns from instruction to skill * Update skills/cloud-design-patterns/SKILL.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update skills/cloud-design-patterns/references/reliability-resilience.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
128 lines
4.5 KiB
Markdown
128 lines
4.5 KiB
Markdown
# Messaging & Integration Patterns
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## Choreography Pattern
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**Problem**: Central orchestrators create coupling and single points of failure.
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**Solution**: Let individual services decide when and how a business operation is processed through event-driven collaboration.
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**When to Use**:
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- Loosely coupled microservices architectures
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- Event-driven systems
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- Avoiding central orchestration bottlenecks
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**Implementation Considerations**:
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- Use publish-subscribe messaging for event distribution
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- Each service publishes domain events and subscribes to relevant events
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- Implement saga pattern for complex workflows
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- Ensure idempotency as events may be delivered multiple times
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- Provide comprehensive logging and distributed tracing
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## Claim Check Pattern
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**Problem**: Large messages can overwhelm message infrastructure.
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**Solution**: Split a large message into a claim check (reference) and a payload stored separately.
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**When to Use**:
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- Messages exceed messaging system size limits
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- Reducing message bus load
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- Handling large file transfers asynchronously
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**Implementation Considerations**:
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- Store payload in blob storage or database
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- Send only reference/URI through message bus
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- Implement expiration policies for stored payloads
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- Handle access control for payload storage
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- Consider costs of storage vs message transmission
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## Competing Consumers Pattern
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**Problem**: Single consumer may not keep up with message volume.
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**Solution**: Enable multiple concurrent consumers to process messages from the same messaging channel.
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**When to Use**:
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- High message throughput requirements
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- Scaling message processing horizontally
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- Load balancing across multiple instances
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**Implementation Considerations**:
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- Ensure messages can be processed in any order
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- Use competing consumer queues (Service Bus, RabbitMQ)
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- Implement idempotency for message handlers
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- Handle poison messages with retry and dead-letter policies
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- Scale consumer count based on queue depth
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## Messaging Bridge Pattern
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**Problem**: Different systems use incompatible messaging technologies.
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**Solution**: Build an intermediary to enable communication between messaging systems that are otherwise incompatible.
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**When to Use**:
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- Migrating between messaging systems
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- Integrating with legacy systems
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- Connecting cloud and on-premises messaging
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**Implementation Considerations**:
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- Transform message formats between systems
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- Handle protocol differences
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- Maintain message ordering if required
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- Implement error handling and retry logic
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- Monitor bridge performance and health
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## Pipes and Filters Pattern
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**Problem**: Complex processing tasks are difficult to maintain and reuse.
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**Solution**: Break down a task that performs complex processing into a series of separate, reusable elements (filters) connected by channels (pipes).
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**When to Use**:
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- Processing data streams with multiple transformations
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- Building reusable processing components
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- Enabling parallel processing of independent operations
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**Implementation Considerations**:
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- Each filter performs a single transformation
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- Connect filters using message queues or streams
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- Enable parallel execution where possible
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- Handle errors within filters or at pipeline level
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- Support filter composition and reordering
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## Publisher-Subscriber Pattern
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**Problem**: Applications need to broadcast information to multiple interested consumers.
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**Solution**: Enable an application to announce events to multiple consumers asynchronously, without coupling senders to receivers.
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**When to Use**:
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- Broadcasting events to multiple interested parties
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- Decoupling event producers from consumers
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- Implementing event-driven architectures
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**Implementation Considerations**:
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- Use topic-based or content-based subscriptions
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- Ensure message delivery guarantees match requirements
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- Implement subscription filters for selective consumption
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- Handle consumer failures without affecting publishers
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- Consider message ordering requirements per subscriber
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## Scheduler Agent Supervisor Pattern
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**Problem**: Distributed actions need coordination and monitoring.
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**Solution**: Coordinate a set of actions across distributed services and resources with a supervisor that monitors and manages the workflow.
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**When to Use**:
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- Orchestrating multi-step workflows
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- Coordinating distributed transactions
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- Implementing resilient long-running processes
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**Implementation Considerations**:
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- Scheduler dispatches tasks to agents
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- Agents perform work and report status
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- Supervisor monitors progress and handles failures
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- Implement compensation logic for failed steps
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- Maintain state for workflow recovery
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