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
Introduction to API Gateway
Usage of API gateway
Advantages and disadvantages of using API gateway
Scalability
Availability
Latency and Performance
Concurrency and Coordination
Monitoring and Observability
Resilience and Error Handling
Fault Tolerance vs. High Availability
HTTP vs. HTTPS
TCP vs. UDP
HTTP: 1.0 vs. 1.1 vs 2.0 vs. 3.0
URL vs. URI vs. URN
Introduction to DNS
DNS Resolution Process
DNS Load Balancing and High Availability
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
What is CDN?
Origin Server vs. Edge Server
CDN Architecture
Push CDN vs. Pull CDN
Introduction to Data Partitioning
Partitioning Methods
Data Sharding Techniques
Benefits of Data Partitioning
Common Problems Associated with Data Partitioning
What is a Proxy Server?
Uses of Proxies
VPN vs. Proxy Server
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
Uses of Load Balancing

Load balancing is a technique used to distribute workloads evenly across multiple computing resources, such as servers, network links, or other devices, in order to optimize resource utilization, minimize response time, and maximize throughput. This technique helps ensure that no single resource is overwhelmed, thus maintaining a high level of performance and reliability. Here are some common uses of load balancing:

1. Improving website performance

Load balancing can distribute incoming web traffic among multiple servers, reducing the load on individual servers and ensuring faster response times for end users.

Example: An e-commerce website experiences a sudden surge in traffic during a holiday sale. A load balancer distributes incoming requests among multiple web servers, ensuring that each server handles a manageable number of requests, resulting in faster page load times for users

2. Ensuring high availability and reliability

By distributing the workload among multiple servers, load balancing helps prevent single points of failure. If one server fails or experiences an issue, the load balancer can redirect traffic to other available servers, maintaining uptime and minimizing service disruptions.

Example: A banking application relies on several servers to handle user transactions. The load balancer monitors the health of each server and, in the event of a server failure, redirects traffic to the remaining healthy servers, minimizing downtime and maintaining user access to the application.

3. Scalability

Load balancing allows organizations to easily scale their infrastructure as traffic and demand increase. Additional servers can be added to the load balancing pool to accommodate increased demand, without the need for significant infrastructure changes.

Example: A video streaming platform sees a steady increase in users as it gains popularity. To handle the growing demand, the platform adds new servers to the load balancing pool, allowing it to scale seamlessly without overloading existing infrastructure.

4. Redundancy

Load balancing can be used to maintain redundant copies of data and services across multiple servers, reducing the risk of data loss or service outages due to hardware failure or other issues.

Example: An online file storage service uses load balancing to maintain multiple copies of user data across different servers. If one server experiences a hardware failure, users can still access their data from the redundant copies stored on other servers.

5. Network optimization

Load balancing can help optimize network traffic by distributing it across multiple paths or links, reducing congestion and improving overall network performance.

Example: A large organization has multiple internet connections to handle its network traffic. A load balancer distributes the incoming and outgoing traffic across these connections, reducing congestion and improving overall network performance.

6. Geographic distribution

For global organizations, load balancing can be used to distribute traffic across data centers in different geographic locations. This ensures that users are directed to the nearest or best-performing data center, reducing latency and improving user experience.

Example: A multinational company has data centers in North America, Europe, and Asia. A load balancer directs users to the nearest data center based on their geographic location, reducing latency and improving the user experience.

7. Application performance

Load balancing can be used to distribute requests for specific applications or services among dedicated servers or resources, ensuring that each application or service receives the necessary resources to perform optimally.

Example: An enterprise uses a suite of applications, including email, file storage, and collaboration tools. A load balancer assigns dedicated resources to each application, ensuring that each service performs optimally without affecting the performance of other applications.

8. Security

Load balancers can help protect against distributed denial-of-service (DDoS) attacks by distributing incoming traffic across multiple servers, making it more difficult for attackers to overwhelm a single target.

Example: A news website faces a distributed denial-of-service (DDoS) attack, with a large number of malicious requests targeting its servers. The load balancer distributes the traffic among multiple servers, making it more difficult for the attackers to overwhelm a single target and mitigating the impact of the attack.

9. Cost savings

By distributing workloads across available resources more efficiently, load balancing can help organizations save money on hardware and infrastructure costs, as well as reduce energy consumption.

Example: A small business utilizes cloud-based infrastructure for its web applications. By using load balancing to optimize resource usage, the business can minimize the number of servers needed, resulting in lower infrastructure and energy costs.

10. Content caching

Some load balancers can cache static content, such as images and videos. This cached content is then served directly from the load balancer, reducing the demand on the servers and providing faster response times for users.

Example: In a streaming service like Netflix, users access a wide variety of content like TV shows, movies, etc. Now, consider a very popular TV show that millions of users might want to watch. If each request for this show was routed to the servers, it would result in a huge load on the servers, potentially slowing down response times or even leading to server failure. By caching such popular content on the load balancer, the streaming service can drastically reduce the load on its main servers.

Load Balancing Algorithms
Load Balancer Types
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On this page

  1. Improving website performance
  1. Ensuring high availability and reliability
  1. Scalability
  1. Redundancy
  1. Network optimization
  1. Geographic distribution
  1. Application performance
  1. Security
  1. Cost savings
  1. Content caching