Referred Link - https://www.linkedin.com/posts/dileeppandiya_dissecting-the-architecture-of-netflix-a-activity-7263040985083924480-wZYU/

Dissecting the Architecture of Netflix: A Look at the Tech Stack Behind Scalable Streaming

This diagram outlines the architecture behind Netflix’s seamless streaming experience, breaking down the tech stack that powers everything from frontend interfaces to backend services, streaming infrastructure, and big data management. It’s a solid example of how a well-designed architecture supports millions of concurrent users and delivers high-quality video on demand.

Key Layers:
Frontend 💻 – The frontend stack includes APIs, mobile and web technologies like GraphQL, Swift, Kotlin, JavaScript, and React. These tools deliver a consistent experience across devices, handling requests with efficiency and speed.

Backend 🔗 – Backend services are built using Spring Boot, with Netflix’s own Zuul and Eureka handling service discovery and communication in a microservices architecture. Databases like EVCache, CockroachDB, MySQL, and Cassandra manage vast amounts of user data and support high-availability.

Streaming Infrastructure 🎥 – Netflix relies on Open Connect and integrates with Amazon Cloudfront and S3 for content delivery, ensuring fast and reliable video streaming worldwide.

Big Data 📊 – To deliver personalized recommendations and insights, Netflix uses a powerful data stack with Amazon Redshift, Apache Iceberg, Apache Spark, and Druid, optimizing both storage and real-time processing.

CI/CD 🔄 – A streamlined CI/CD pipeline with Jenkins, Spinnaker, PagerDuty, and Confluence supports rapid development cycles, testing, and deployment, enabling continuous improvement and scalability.

Why This Matters:
This architecture demonstrates the importance of modularity, scalability, and resilience in high-demand applications. Netflix’s use of in-house and open-source solutions, combined with cloud integrations, exemplifies a robust setup for handling massive concurrent traffic while maintaining performance.

For those building similar architectures – what tools or strategies have worked best for you? Drop your insights below—let’s exchange ideas on scalable, resilient systems.

Tags:

#Architecture, #NetflixArchitecture

 Referred Link - https://www.linkedin.com/posts/dileeppandiya_having-spent-years-working-on-distributed-activity-7267741954724048896-vG5X

Core Architecture Components:

1. Frontend Layer:
- Client interface connects to multiple services through DNS
- Load balancers distribute traffic across API gateways
- CDN optimization for static content delivery

2. Data Processing Pipeline:
- Sophisticated write/read server separation for optimal performance
- Multiple API gateways handle request routing and load distribution
- Dedicated video/image processing service with worker pools
- Feed generation tasks run asynchronously through dedicated queues

3. Storage Architecture:
- Multi-tiered caching system reducing database load
- Directory-based partitioning for efficient data distribution
- Master-slave database configuration enabling:
• High availability
• Read scalability
• Disaster recovery
- Shard manager handling data partitioning and replication

4. Real-Time Features:
- Dedicated notification service with queue management
- Search functionality with results aggregators
- Elastic search implementation with caching layer
- Like service integration with feed generation

5. Performance Optimizations:
- Strategic cache placement at multiple levels
- Asynchronous processing for compute-heavy tasks
- Horizontal scaling capabilities at every tier
- Specialized workers for media processing

🔍 Technical Deep-Dive:
The architecture demonstrates several critical patterns:
- Microservices decomposition for independent scaling
- Event-driven design for real-time updates
- Polyglot persistence with different storage solutions
- Circuit breakers and fault isolation
- Eventually consistent data model

⚡ Performance Considerations:
- Read/write splitting reduces contention
- Caching at multiple layers minimizes latency
- Async processing prevents blocking operations
- Partitioning enables infinite horizontal scaling
- CDN integration optimizes content delivery globally

🛡️ Reliability Features:
- Multiple API gateways prevent single points of failure
- Slave DB replicas ensure data redundancy
- Sharding enables better fault isolation
- Queue-based design handles traffic spikes
- Worker pools manage resource utilization

📈 Scaling Strategies:
- Horizontal scaling across all services
- Partition tolerance through sharding
- Load balancing at multiple levels
- Stateless services for easy replication
- Cache hierarchies for performance

🎯 Key Engineering Decisions:
1. Separating read/write paths
2. Implementing content-aware routing
3. Using specialized processing queues
4. Maintaining data consistency through careful service design
5. Employing multiple layers of caching

💡 Learning Points:
- How to handle web-scale data processing
- Balancing consistency vs availability
- Managing real-time features at scale
- Implementing efficient content delivery
- Designing for fault tolerance

Tags:

#Architecture, #FaceBookArchitecture