Top 7 Most-Used Distributed System Patterns

Summary

In this video, we explore the top 7 distributed system patterns that can help design more scalable and efficient systems. We cover patterns such as Ambassador, Circuit Breaker, CQRS, Event Sourcing, Leader Election, Pub/Sub, and Sharding, with real-world examples from companies like Netflix and Kubernetes. These patterns help prevent system failures, improve performance, and ensure better scalability. Additionally, the Strangler Fig pattern is introduced as a bonus, showing how to incrementally replace legacy systems. Understanding and applying these patterns can lead to more robust distributed applications.

Takeaways

• 😀 Ambassador pattern acts as an intermediary between services, improving communication and reducing latency, security, and architecture complexity.
• 😀 Circuit Breaker pattern prevents cascading failures by halting requests to an unavailable service, ensuring system resilience.
• 😀 CQRS (Command Query Responsibility Segregation) separates read and write operations to optimize each independently for better scalability.
• 😀 Event Sourcing stores events representing changes instead of directly updating records, providing a complete history and advanced features like time-travel debugging.
• 😀 Leader Election ensures consistency by designating a leader node responsible for specific tasks, preventing conflicts in distributed systems.
• 😀 Pub/Sub pattern allows publishers to emit events without knowing who receives them, promoting scalability and modularity in event-driven systems.
• 😀 Sharding distributes data across multiple nodes, improving performance and reducing the load on any single node, making systems more scalable.
• 😀 The Strangler Fig pattern allows for gradual system migration, replacing legacy systems incrementally to manage risks in the transition.
• 😀 Distributed system patterns like Ambassador, Circuit Breaker, and CQRS help design more efficient, reliable, and scalable applications.
• 😀 Understanding the specific needs of a system and applying the right patterns is crucial for building better distributed systems.

Q & A

What is the Ambassador pattern, and how does it work in distributed systems?

The Ambassador pattern acts as a 'go-between' for your application and the services it communicates with. It offloads tasks like logging, monitoring, and retry handling, improving communication between services. An example is Kubernetes using Envoy as an ambassador to simplify service communication.

How does the Circuit Breaker pattern help in preventing system failures?

The Circuit Breaker pattern prevents cascading failures in distributed systems. When a service becomes unavailable, the Circuit Breaker stops requests to the service, allowing it time to recover. This pattern is used in libraries like Netflix's Hystrix to ensure system resilience.

What is CQRS, and why is it useful in handling read and write operations?

CQRS (Command Query Responsibility Segregation) separates the handling of write (command) and read (query) operations. This allows each operation to be scaled and optimized independently. It’s particularly useful in scenarios where read and write operations have different performance requirements.

Can you explain how Event Sourcing works in distributed systems?

Event Sourcing involves storing events that represent changes in the system instead of directly updating records. This provides a complete history of changes, allowing for features like time-travel debugging and event replay for analytics. A common example is Git, where each commit represents a change in the system.

What role does the Leader Election pattern play in distributed systems?

The Leader Election pattern ensures that only one node is responsible for a task or resource at a time. When the leader node fails, the remaining nodes elect a new leader. This pattern is used in systems like ZooKeeper and etcd to manage configurations and ensure consistent decision-making.

What is the Publisher/Subscriber (Pub/Sub) pattern, and how does it work?

In the Pub/Sub pattern, publishers emit events without knowing who will receive them, while subscribers listen for events they are interested in. This pattern facilitates scalable and modular communication between components. Google Cloud Pub/Sub is a real-world example of this pattern enabling asynchronous messaging.

How does Sharding improve the performance and scalability of a system?

Sharding involves distributing data across multiple nodes to improve performance and scalability. Each shard contains a subset of the data, which reduces the load on any single node. This technique is commonly used in databases like MongoDB and Cassandra to handle large volumes of data efficiently.

What is the Strangler Fig pattern, and how is it used in system migrations?

The Strangler Fig pattern is inspired by the way a strangler fig tree gradually replaces its host tree. In software, it allows for the incremental replacement of legacy systems with new components. This approach reduces the risk of a 'big bang' migration and simplifies system migrations by gradually phasing out older parts.

Why are distributed system patterns important for scalable application design?

Distributed system patterns are essential for building scalable, efficient, and resilient applications. They help manage complexity, improve fault tolerance, and ensure optimal performance by providing tried-and-true solutions for common challenges in distributed architectures.

Can you give examples of systems that implement distributed system patterns like Leader Election and Pub/Sub?

ZooKeeper and etcd implement the Leader Election pattern to manage distributed configurations. Google Cloud Pub/Sub is an example of the Pub/Sub pattern, which enables asynchronous messaging between services in cloud-based applications, ensuring scalability and modularity.