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
Challenges of Load Balancers

Load balancers play a crucial role in distributing traffic and optimizing resource utilization in modern applications. However, they are not without potential challenges or problems. Some common issues associated with load balancers include:

1. Single Point of Failure

If not designed with redundancy and fault tolerance in mind, a load balancer can become a single point of failure in the system. If the load balancer experiences an outage, it could impact the entire application.

  • Remedy: Implement high availability and failover mechanisms, such as redundant load balancer instances, to ensure continuity even if one instance fails.

2. Configuration Complexity

Load balancers often come with a wide range of configuration options, including algorithms, timeouts, and health checks. Misconfigurations can lead to poor performance, uneven traffic distribution, or even service outages.

  • Remedy: Regularly review and update configurations, and consider using automated configuration tools or expert consultation to ensure optimal settings.

3. Scalability Limitations

As traffic increases, the load balancer itself might become a performance bottleneck, especially if it is not configured to scale horizontally or vertically.

  • Remedy: Plan for horizontal or vertical scaling of the load balancer to match traffic demands, and use scalable cloud-based load balancing solutions.

4. Latency

Introducing a load balancer into the request-response path adds an additional network hop, which could lead to increased latency. While the impact is typically minimal, it is essential to consider the potential latency introduced by the load balancer and optimize its performance accordingly.

  • Remedy: Optimize load balancer performance through efficient routing algorithms and by placing the load balancer geographically close to the majority of users.

5. Sticky Sessions

Some applications rely on maintaining session state or user context between requests. In such cases, load balancers must be configured to use session persistence or "sticky sessions" to ensure subsequent requests from the same user are directed to the same backend server. However, this can lead to uneven load distribution and negate some of the benefits of load balancing.

  • Remedy: Employ advanced load balancing techniques that balance the need for session persistence with even traffic distribution, or redesign the application to reduce dependence on session state.

6. Cost

Deploying and managing load balancers, especially in high-traffic scenarios, can add to the overall cost of your infrastructure. This may include hardware or software licensing costs, as well as fees associated with managed load balancing services provided by cloud providers.

  • Remedy: Opt for cost-effective load balancing solutions, such as open-source software or cloud-based services that offer pay-as-you-go pricing models.

7. Health Checks and Monitoring

Implementing effective health checks for backend servers is essential to ensure that the load balancer accurately directs traffic to healthy instances. Misconfigured or insufficient health checks can lead to the load balancer sending traffic to failed or underperforming servers, resulting in a poor user experience.

  • Remedy: Implement comprehensive and regular health checks for backend servers, and use real-time monitoring tools to ensure traffic is always directed to healthy instances.

Despite these potential challenges, load balancers are an essential component of modern applications and can significantly improve performance, fault tolerance, and resource utilization when configured and managed correctly.

Scalability and Performance
Introduction to API Gateway
Mark as Completed

On this page

  1. Single Point of Failure
  1. Configuration Complexity
  1. Scalability Limitations
  1. Latency
  1. Sticky Sessions
  1. Cost
  1. Health Checks and Monitoring