- 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
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