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
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
Types of Caching

Caching can be implemented in various ways, depending on the specific use case and the type of data being cached. Here are some of the most common types of caching:

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1. In-memory caching

In-memory caching stores data in the main memory of the computer, which is faster to access than disk storage. In-memory caching is useful for frequently accessed data that can fit into the available memory. This type of caching is commonly used for caching API responses, session data, and web page fragments. To implement in-memory caching, software engineers can use various techniques, including using a cache library like Memcached or Redis, or implementing custom caching logic within the application code.

2. Disk caching

Disk caching stores data on the hard disk, which is slower than main memory but faster than retrieving data from a remote source. Disk caching is useful for data that is too large to fit in memory or for data that needs to persist between application restarts. This type of caching is commonly used for caching database queries and file system data.

3. Database caching

Database caching stores frequently accessed data in the database itself, reducing the need to access external storage. This type of caching is useful for data that is stored in a database and frequently accessed by multiple users. Database caching can be implemented using a variety of techniques, including database query caching and result set caching.

4. Client-side caching

This type of caching occurs on the client device, such as a web browser or mobile app. Client-side caching stores frequently accessed data, such as images, CSS, or JavaScript files, to reduce the need for repeated requests to the server. Examples of client-side caching include browser caching and local storage.

5. Server-side caching

This type of caching occurs on the server, typically in web applications or other backend systems. Server-side caching can be used to store frequently accessed data, precomputed results, or intermediate processing results to improve the performance of the server. Examples of server-side caching include full-page caching, fragment caching, and object caching.

6. CDN caching

CDN caching stores data on a distributed network of servers, reducing the latency of accessing data from remote locations. This type of caching is useful for data that is accessed from multiple locations around the world, such as images, videos, and other static assets. CDN caching is commonly used for content delivery networks and large-scale web applications.

7. DNS caching

DNS cache is a type of cache used in the Domain Name System (DNS) to store the results of DNS queries for a period of time. When a user requests to access a website, their computer sends a DNS query to a DNS server to resolve the website’s domain name to an IP address. The DNS server responds with the IP address, and the user’s computer can then access the website using the IP address. DNS caching improves the performance of the DNS system by reducing the number of requests made to DNS servers. When a DNS server receives a request for a domain name, it checks its local cache to see if it has the IP address for that domain name. If the IP address is in the cache, the DNS server can immediately respond with the IP address without having to query other servers. This can significantly reduce the response time for DNS queries and improve the overall performance of the system.

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Why is Caching Important?
Cache Replacement Policies
Mark as Completed

On this page

  1. In-memory caching
  1. Disk caching
  1. Database caching
  1. Client-side caching
  1. Server-side caching
  1. CDN caching
  1. DNS caching