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Minaz Inamdar
Minaz Inamdar

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Distributed Systems Patterns

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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