Grokking System Design Fundamentals
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System Design Fundamentals
Introduction to System Design
Load Balancing
Introduction to Load Balancing
Load Balancing Algorithms
Uses of Load Balancing
Load Balancer Types
Stateless vs. Stateful Load Balancing
High Availability and Fault Tolerance
Scalability and Performance
Challenges of Load Balancers
API Gateway
Introduction to API Gateway
Usage of API gateway
Advantages and disadvantages of using API gateway
Key Characteristics of Distributed Systems
Scalability
Availability
Latency and Performance
Concurrency and Coordination
Monitoring and Observability
Resilience and Error Handling
Fault Tolerance vs. High Availability
Network Essentials
HTTP vs. HTTPS
TCP vs. UDP
HTTP: 1.0 vs. 1.1 vs 2.0 vs. 3.0
URL vs. URI vs. URN
Domain Name System (DNS)
Introduction to DNS
DNS Resolution Process
DNS Load Balancing and High Availability
Caching
Introduction to Caching
Why is Caching Important?
Types of Caching
Cache Replacement Policies
Cache Invalidation
Cache Read Strategies
Cache Coherence and Consistency Models
Caching Challenges
Cache Performance Metrics
CDN
What is CDN?
Origin Server vs. Edge Server
CDN Architecture
Push CDN vs. Pull CDN
Data Partitioning
Introduction to Data Partitioning
Partitioning Methods
Data Sharding Techniques
Benefits of Data Partitioning
Common Problems Associated with Data Partitioning
Proxies
What is a Proxy Server?
Uses of Proxies
VPN vs. Proxy Server
Redundancy and Replication
What is Redundancy?
What is Replication?
Replication Methods
Data Backup vs. Disaster Recovery
Introduction to CAP Theorem
Components of CAP Theorem
Trade-offs in CAP Theorem
Examples of CAP Theorem in Practice
Beyond CAP Theorem
System Design Trade-offs in Interviews
Introduction to Databases
SQL Databases
NoSQL Databases
SQL vs. NoSQL
ACID vs BASE Properties
Real-World Examples and Case Studies
SQL Normalization and Denormalization
In-Memory Database vs. On-Disk Database
Data Replication vs. Data Mirroring
Database Federation
What are Indexes?
Types of Indexes
Introduction to Bloom Filters
Benefits & Limitations of Bloom Filters
Variants and Extensions of Bloom Filters
Applications of Bloom Filters
Difference Between Long-Polling, WebSockets, and Server-Sent Events
What is Quorum?
What is Heartbeat?
What is Checksum?
Uses of Checksum
What is Leader and Follower Pattern?
What is Security and Privacy?
What is Authentication?
What is Authorization?
Authentication vs. Authorization
OAuth vs. JWT for Authentication
What is Encryption?
What are DDoS Attacks?
Introduction to Messaging System
Introduction to Kafka
Messaging patterns
Popular Messaging Queue Systems
RabbitMQ vs. Kafka vs. ActiveMQ
Scalability and Performance
What is a Distributed File System?
Architecture of a Distributed File System
Key Components of a DFS
Batch Processing vs. Stream Processing
XML vs. JSON
Synchronous vs. Asynchronous Communication
Push vs. Pull Notification Systems
Microservices vs. Serverless Architecture
Message Queues vs. Service Bus
Stateful vs. Stateless Architecture
Event-Driven vs. Polling Architecture
Quiz
What is Redundancy?

Redundancy refers to the duplication of critical components or functions to increase the reliability, availability, and fault tolerance of a system. The primary purpose of redundancy is to prevent system failures and ensure continuous operation, even in the event of hardware, software, or network issues. Redundant systems are designed to maintain functionality and performance despite component failures, providing increased resilience against downtime and data loss.

Redundancy plays a key role in removing the single points of failure in the system and provides backups if needed in a crisis. For example, if we have two instances of a service running in production and one fails, the system can failover to the other one.

Redundancy
Redundancy

Benefits of redundancy in system design

Implementing redundancy in system design offers numerous advantages:

1. Improved reliability

Redundant systems are more reliable, as they can continue to function despite individual component failures. This increased reliability reduces the likelihood of system outages, ensuring the availability of critical services and applications.

2. Enhanced fault tolerance

By incorporating redundant components, a system can better tolerate and recover from faults or failures. This fault tolerance is essential for maintaining high availability and minimizing downtime, particularly in mission-critical systems.

3. Increased availability

Redundant systems are designed to provide continuous operation, ensuring that services and applications remain available even during component failures or maintenance. This increased availability is crucial for organizations that rely on 24/7 access to their systems and data.

4. Simplified maintenance

Redundancy allows for maintenance and upgrades to be performed without disrupting system operation. By having backup components in place, administrators can perform maintenance on one part of the system while the redundant components continue to provide service.

5. Disaster recovery

Redundancy plays a crucial role in disaster recovery planning. By having multiple, geographically distributed copies of data and resources, organizations can recover more quickly from disasters or catastrophic events that may affect a single location.

Conclusion

Overall, implementing redundancy in system design is essential for ensuring the reliability, availability, and fault tolerance of modern computing systems. It helps prevent downtime, data loss, and other issues that can negatively impact user experience, productivity, and business operations.

VPN vs. Proxy Server
What is Replication?
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Benefits of redundancy in system design

  1. Improved reliability
  1. Enhanced fault tolerance
  1. Increased availability
  1. Simplified maintenance
  1. Disaster recovery

Conclusion