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
CAP & PACELC Theorems
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
Databases (SQL vs. NoSQL)
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
Indexes
What are Indexes?
Types of Indexes
Bloom Filters
Introduction to Bloom Filters
Benefits & Limitations of Bloom Filters
Variants and Extensions of Bloom Filters
Applications of Bloom Filters
Long-Polling vs. WebSockets vs. Server-Sent Events
Difference Between Long-Polling, WebSockets, and Server-Sent Events
Quorum
What is Quorum?
Heartbeat
What is Heartbeat?
Checksum
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 Checksum

Here are the top uses of checksum:

  1. Data Integrity Checks: Imagine sending a super-secret spy message - you wanna make sure it doesn’t get altered during transmission, right? Checksums ensure data hasn’t been tampered with during transmission by checking - you guessed it - the Checksum! If it doesn’t match, something’s fishy.

  2. Error Detection: Ever download a file and it just won’t open? Checksums can help detect if a bit of data got scrambled during a download, helping systems know when they need to try downloading it again.

  3. Data Retrieval and Verification: When you download software or a file from a website, they often provide a Checksum value. You can use this to verify the integrity of the data, ensuring that what you downloaded is exactly what the creators intended, no nasty surprises hiding inside!

  4. Networking: In networking, Checksums help detect errors in packets of data sent over a network. If the arriving packet's Checksum doesn’t match the one it was sent with, the packet can be rejected, ensuring no corrupted data gets through!

  5. Secure Storage: In some databases, Checksums help maintain the integrity of the stored data. Periodically, the stored data is checked against the Checksum - if it doesn’t match, the system knows something’s amiss in the storage system!

  6. Password Verification: Some systems store the Checksum of a password instead of the password itself. When you log in, the system runs the Checksum algorithm on the password you enter and checks that Checksum against the stored Checksum. If they match, you’re in! No need to store actual passwords, adding a layer of security!

  7. Preventing Accidental Duplicates: Systems can use Checksums to prevent accidentally storing duplicate data. If two pieces of data have the same Checksum, they might be duplicates, saving storage space and preventing redundancy!

What is Checksum?
What is Leader and Follower Pattern?
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