Distributed Systems Patterns

• Notes via ByteByteGo

1. Ambassador Pattern

Pros:

• Simplifies communication between services.
• Handles load balancing, traffic routing, and retries transparently.
• Promotes decoupling of services.

Cons:

• Adds an additional layer, which can introduce latency.
• Requires configuration and management overhead.

Applications:

• Kubernetes uses Envoy as an Ambassador.

2. Circuit Breaker Pattern

Pros:

• Prevents cascading failures and improves system resilience.
• Enhances fault tolerance by isolating failing components.
• Provides fallback mechanisms to maintain system stability.

Cons:

• Introduces complexity to manage circuit states.
• May impact performance during high load or transient failures.

Applications:

• Netflix's Hytrix library.

3. CQRS (Command Query Responsibility Segregation) Pattern

Pros:

• Optimizes read and write operations independently.
• Improves scalability and performance for read-heavy workloads.
• Facilitates complex business logic on the write side.

Cons:

• Increases architectural complexity.
• Requires careful synchronization between command and query models.

4. Event Sourcing Pattern

Pros:

• Provides a complete audit trail of system state changes.
• Enables temporal queries and historical analysis.
• Supports scalability and resilience through immutable event logs.

Cons:

• Increased storage requirements due to storing all events.
• Requires efficient replay mechanisms for state rebuilds.

5. Leader Election Pattern

Pros:

• Establishes a single point of coordination in distributed systems.
• Ensures high availability by quickly electing a new leader.
• Facilitates scalability and fault tolerance.

Cons:

• Adds overhead due to election algorithms and heartbeat mechanisms.
• May introduce latency during leader changes.

Applications:

• Apache zookeeper.

6. Publisher-Subscriber Pattern

Pros:

• Supports asynchronous and real-time messaging.
• Decouples publishers from subscribers, improving scalability.
• Facilitates event-driven architectures.

Cons:

• Requires robust message delivery mechanisms to ensure reliability.
• May introduce complexity in managing message ordering and processing.

7. Sharding Pattern

Pros:

• Improves scalability by distributing data across multiple nodes.
• Enhances performance for read and write operations by reducing contention.
• Allows horizontal scaling by adding more shards.

Cons:

• Requires careful shard key selection and management.
• Increases complexity in data distribution and query routing.
• Introduces additional overhead for data rebalancing and maintenance.

Applications:

• Cassandra and MongoDB