System Design

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How to Learn System Design?

Scalability

Availability

Latency and Performance

Concurrency and Coordination

Monitoring and Observability

Resilience and Error Handling

Fault Tolerance vs. High Availability

Flashcards Review

Chapter Assessment

HTTP vs. HTTPS

TCP vs. UDP

HTTP: 1.0 vs. 1.1 vs 2.0 vs. 3.0

URL vs. URI vs. URN

What Happens When You Type a URL into the Browser

Flashcards Review

Chapter Assessment

Introduction to Real-Time Communication

What is Long-Polling?

What is WebSocket?

What are Server-Sent Events?

Difference Between Long-Polling, WebSockets, and Server-Sent Events

Flashcards Review

Chapter Assessment

Domain Name System (DNS)

Introduction to DNS

DNS Resolution Process

DNS Load Balancing and High Availability

Flashcards Review

Chapter Assessment

What is a Proxy Server?

Uses of Proxies

VPN vs. Proxy Server

Flashcards Review

Chapter Assessment

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

Flashcards Review

Chapter Assessment

Introduction to API Gateway

Usage of API gateway

Advantages and disadvantages of using API gateway

Flashcards Review

Chapter Assessment

What Is an API?

What Are REST APIs?

Resources, Not Actions

HTTP Methods and Their Semantics

URL Design

Request and Response Shapes

Status Codes and Error Design

Pagination from the Consumer's View

Idempotency Keys

Versioning and Backward Compatibility

Concurrency and Conditional Requests

REST vs gRPC vs GraphQL

Flashcards Review

Chapter Assessment

What Is Rate Limiting

Rate Limiting Algorithms

Distributed Rate Limiting

Rate Limiting in Practice

Flashcards Review

Chapter Assessment

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

Flashcards Review

Chapter Assessment

What is CDN?

Origin Server vs. Edge Server

CDN Architecture

Push CDN vs. Pull CDN

Flashcards Review

Chapter Assessment

Introduction to Data Partitioning

Partitioning Methods

Data Sharding Techniques

Benefits of Data Partitioning

Common Problems Associated with Data Partitioning

Flashcards Review

Chapter Assessment

What is Redundancy?

What is Replication?

Replication Methods

Data Backup vs. Disaster Recovery

Flashcards Review

Chapter Assessment

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

Flashcards Review

Chapter Assessment

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

Flashcards Review

Chapter Assessment

What are Indexes?

How a B-Tree Index Works

Types of Indexes

B-Tree vs. LSM Tree

Indexes in Distributed Systems

Flashcards Review

Chapter Assessment

Introduction to Bloom Filters

Benefits & Limitations of Bloom Filters

Variants and Extensions of Bloom Filters

Applications of Bloom Filters

Flashcards Review

Chapter Assessment

Why Quorum?

What is Quorum?

Flashcards Review

Chapter Assessment

What is Leader and Follower Pattern?

Flashcards Review

Chapter Assessment

What is Heartbeat?

Flashcards Review

Chapter Assessment

What is Checksum?

Uses of Checksum

Flashcards Review

Chapter Assessment

Introduction to Messaging System

Introduction to Kafka

Messaging patterns

Popular Messaging Queue Systems

RabbitMQ vs. Kafka vs. ActiveMQ

Scalability and Performance

Flashcards Review

Chapter Assessment

What is a Distributed File System?

Architecture of a Distributed File System

Key Components of a DFS

Flashcards Review

Chapter Assessment

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?

Flashcards Review

Chapter Assessment

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

Flashcards Review

Chapter Assessment

Quiz

Importance of Discussing Trade-offs

Strong vs Eventual Consistency

Latency vs Throughput

ACID vs BASE Properties in Databases

Read-Through vs Write-Through Cache

Batch Processing vs Stream Processing

Load Balancer vs. API Gateway

API Gateway vs Direct Service Exposure

Proxy vs. Reverse Proxy

API Gateway vs. Reverse Proxy

SQL vs. NoSQL

Primary-Replica vs Peer-to-Peer Replication

Data Compression vs Data Deduplication

Server-Side Caching vs Client-Side Caching

REST vs RPC

Polling vs. Long-Polling vs. WebSockets vs. Webhooks

CDN Usage vs Direct Server Serving

Serverless Architecture vs Traditional Server-based

Stateful vs Stateless Architecture

Hybrid Cloud Storage vs All-Cloud Storage

Token Bucket vs Leaky Bucket

Read Heavy vs Write Heavy System

Quiz

System Design Interviews - A step by step guide

Functional vs. Non-functional Requirements

What are Back-of-the-Envelope Estimations?

Things to Avoid During System Design Interview

System Design Master Template

Quiz

Designing a URL Shortening Service like TinyURL

Quiz - Designing URL Shortner

Designing Pastebin

Quiz - Designing Pastebin

Designing Instagram

Quiz - Designing Instagram

Designing Dropbox

Quiz - Designing Dropbox

Designing Facebook Messenger

Quiz - Designing Facebook Messenger

Designing Twitter

Quiz - Designing Twitter

Designing Youtube or Netflix

Quiz - Designing Youtube

Designing Typeahead Suggestion

Quiz - Designing Typeahead Suggestion

Designing an API Rate Limiter

Quiz - Designing an API Rate Limiter

Designing Twitter Search

Quiz - Designing Twitter Search

Designing a Web Crawler

Quiz - Designing a Web Crawler

Designing Facebook’s Newsfeed

Quiz - Designing Facebook’s Newsfeed

Designing Yelp or Nearby Friends

Quiz - Designing Yelp or Nearby Friends

Designing Uber backend

Quiz - Designing Uber backend

Designing Ticketmaster

Quiz - Designing Ticketmaster

Dynamo: Introduction

High-Level Architecture

Data Partitioning

Replication

Vector Clocks and Conflicting Data

The Life of Dynamo’s put() & get() Operations

Anti-entropy Through Merkle Trees

Gossip Protocol

Dynamo Characteristics and Criticism

Summary: Dynamo

Quiz: Dynamo

Mock Interview: Dynamo

YouTube Likes Counter

Quiz

Cassandra: Introduction

High-level Architecture

Replication

Cassandra Consistency Levels

Gossiper

Anatomy of Cassandra's Write Operation

Anatomy of Cassandra's Read Operation

Compaction

Tombstones

Summary: Cassandra

Quiz: Cassandra

Mock Interview: Cassandra

Messaging Systems: Introduction

Kafka: Introduction

High-level Architecture

Kafka: Deep Dive

Consumer Groups

Kafka Workflow

Role of ZooKeeper

Controller Broker

Kafka Delivery Semantics

Kafka Characteristics

Summary: Kafka

Quiz: Kafka

Mock Interview: Kafka

Chubby: Introduction

High-level Architecture

Design Rationale

How Chubby Works

File, Directories, and Handles

Locks, Sequencers, and Lock-delays

Sessions and Events

Master Election and Chubby Events

Caching

Database

Scaling Chubby

Summary: Chubby

Quiz: Chubby

Mock Interview: Chubby

Hadoop Distributed File System: Introduction

High-level Architecture

Deep Dive

Anatomy of a Read Operation

Anatomy of a Write Operation

Data Integrity & Caching

Fault Tolerance

HDFS High Availability (HA)

HDFS Characteristics

Summary: HDFS

Quiz: HDFS

Mock Interview: HDFS

Google File System: Introduction

High-level Architecture

Single Master and Large Chunk Size

Metadata

Master Operations

Anatomy of a Read Operation

Anatomy of a Write Operation

Anatomy of an Append Operation

GFS Consistency Model and Snapshotting

Fault Tolerance, High Availability, and Data Integrity

Garbage Collection

Criticism on GFS

Summary: GFS

Quiz: GFS

Mock Interview: GFS

BigTable: Introduction

BigTable Data Model

System APIs

Partitioning and High-level Architecture

SSTable

GFS and Chubby

Bigtable Components

Working with Tablets

The Life of BigTable's Read & Write Operations

Fault Tolerance and Compaction

BigTable Refinements

BigTable Characteristics

Summary: BigTable

Quiz: BigTable

Mock Interview: BigTable

Design Reddit

Quiz

Designing a Notification System

Quiz

Design Google calendar (Medium)

Quiz

Design a Recommendation System for Netflix

Quiz

Design Gmail

Quiz

Design Google News, a Global News Aggregator System (Medium)

Quiz

Design Unique ID Generator (Easy)

Quiz

Design Code Judging System like LeetCode (Medium)

Quiz

Design Payment System

Quiz

Design a Flash Sale for an E-commerce Site (Hard)

Quiz

Design a Reminder Alert System

Quiz

Introduction: System Design Patterns

1. Bloom Filters

2. Consistent Hashing

3. Quorum

4. Leader and Follower

5. Write-ahead Log

6. Segmented Log

7. High-Water Mark

8. Lease

9. Heartbeat

10. Gossip Protocol

11. Phi Accrual Failure Detection

12. Split Brain

13. Fencing

14. Checksum

15. Vector Clocks

16. CAP Theorem

17. PACELC Theorem

18. Hinted Handoff

19. Read Repair

20. Merkle Trees

Quiz

DNS Load Balancing and High Availability

DNS Load Balancing and High Availability

dns

load balancing

availability

distributed systems

+2

hard
·
13 min
·Updated Sep 2026·Credit: System Design Fundamentals

A video site has servers in Europe, North America, and Asia. A user in Tokyo types the site's name. A user in Madrid types the same name at the same moment.

Both users should reach a server near them. And if the servers in Asia fail, the user in Tokyo should still reach the site.

The first decision happens before any request reaches a server. It happens when DNS chooses which IP address to return. This lesson explains how DNS uses that choice to spread load and to keep a service available.

Why DNS Can Balance Load

A DNS server does not have to give every user the same answer. For one name, it can return different IP addresses to different users, or change the answer over time.

That choice happens during name resolution, before any traffic reaches your servers. So DNS can do two useful jobs.

  • Spread load. Send different users to different servers.
  • Improve availability. Stop sending users to a server or a location that has failed.

There are four common techniques: round-robin DNS, geographically distributed DNS servers, anycast routing, and CDNs that use DNS.

Round-Robin DNS

Round-robin DNS is the simplest technique. Several IP addresses are associated with one domain name. When resolvers ask for that name, the DNS server rotates through the addresses, returning them in a different order each time.

For example, example.com has three A records: 203.0.113.10, 203.0.113.11, and 203.0.113.12. The first query gets .10 first, the next query gets .11 first, and the next gets .12 first. Most clients use the first address in the list, so requests are spread across the three servers.

Image
One domain name has three IP addresses, and each query receives the next address in the rotation

Round-robin DNS is easy to set up, and it improves both performance and availability.

The Limits of Round-Robin DNS

Round-robin DNS does not know how busy each server is, or where the user is. It only rotates through the list. This causes several problems.

  • Uneven load. A large resolver can serve thousands of users. It may cache one answer and give the same first address to all of them until the TTL expires. So one server can receive far more traffic than the others.
  • Distance. A user in Madrid may receive the address of a server in Asia, while a closer server has little traffic.
  • Failed servers still get traffic. DNS does not check whether a server is healthy. If one server crashes, its address is still returned in answers. Even after someone removes it, cached copies keep sending users there until their TTL expires. Some clients try the next address after a failure, but many users still see errors.

Smarter DNS Answers

Many DNS services go beyond simple rotation. They choose each answer with more information.

  • Health-checked DNS. The DNS service checks each server regularly, for example with an HTTP request every 30 seconds. When a server fails its checks, its address is removed from the answers.
  • Weighted DNS. Each address gets a share of the answers. For example, 90 percent of answers point to the current version of a service and 10 percent to a new version.
  • Location-based DNS. The DNS server returns the address of the region closest to the user. It usually judges this from the location of the user's resolver. Some resolvers also pass part of the user's IP address, so the answer matches the user's location more closely.
Image
Health-checked DNS removes failed servers, weighted DNS splits traffic by percentage, and location-based DNS returns the nearest region

All of these are still affected by caching. A change in the answer reaches users only after the cached answers expire. So services that use DNS for failover usually set short TTLs, like 30 to 60 seconds.

Geographically Distributed DNS Servers

DNS servers themselves can also be spread across many locations, instead of sitting in one data center.

This gives two benefits.

  • Faster resolution. Users get answers from a DNS server near them, so each lookup takes less time.
  • Redundancy. One location can become unreachable because of a server failure or a network outage. Users can then still be served by DNS servers in other locations.

Every large DNS provider works this way. So do the root servers, which the next section explains.

Anycast Routing

Anycast lets multiple servers in different places share the same IP address.

Here is how it works. Each location tells the internet's routers that it can reach that IP address. Routers share this information with a protocol called BGP (Border Gateway Protocol), which is how networks tell each other which addresses they can reach. When a query is sent to the shared address, the network delivers it to the nearest location. Routers judge this by factors like network distance and availability.

The user does not choose, and the DNS operator does not choose. The network's routing chooses.

Anycast gives three benefits at once.

  • Load balancing. Queries are spread across many servers, so no single server becomes a bottleneck.
  • Lower latency. Each user reaches a nearby server, which reduces resolution time.
  • High availability. If one location fails, it stops announcing the address. The network then automatically sends queries to the next closest location that shares the same IP address. No one has to change any configuration.
Image
Three sites share one IP address, each user reaches the nearest site, and if a site fails, users automatically reach the next nearest one

Anycast suits DNS very well because a DNS query is usually one short question and one short answer. The 13 root server clusters use anycast, which is how each one can be made of many servers around the world. Public resolvers like 1.1.1.1 and 8.8.8.8 also use it.

The difference from round-robin DNS is important. Round-robin gives out different addresses and does not consider where users are. Anycast gives out one address, and the network delivers each request to a nearby location.

CDNs and DNS

A Content Delivery Network (CDN) is a network of distributed servers that cache and deliver web content to users based on their location. It improves performance, reliability, and security by spreading load across many servers and serving each user from a nearby server.

DNS is how a CDN sends each user to a nearby server. Here are the steps.

  1. The website points its name to the CDN with a CNAME record. For example, www.example.com becomes an alias for example.cdnprovider.net.
  2. A user's resolver looks up www.example.com and follows the CNAME to the CDN's name.
  3. The CDN's own DNS server chooses the best edge server for this user, based on location, server load, and other factors.
  4. It returns that edge server's IP address, and the user's browser connects there.
Image
A site points its name to the CDN with a CNAME, the CDN's DNS server picks the best edge server for the user, and returns that server's address

So the routing decision happens during name resolution, before any content is sent. CDNs usually use short TTLs, so they can send users to a different edge server quickly when one is busy or has failed. The What is CDN? lesson covers CDNs in more detail.

Where DNS Load Balancing Stops

DNS is useful for spreading load, but it has limits.

  • Caching delays every change. Resolvers, operating systems, and browsers keep answers until the TTL expires, and sometimes longer.
  • No control over single requests. DNS picks an address for a lookup, not for each request. One cached answer can be used for thousands of requests.
  • Limited knowledge of servers. DNS does not see how busy each server is right now.

So large systems usually combine two layers. DNS, often with anycast or location-based answers, picks the region. Inside each region, a load balancer spreads requests across healthy servers, and it reacts to failures in seconds. The load balancing chapter explains load balancers.

TechniqueHow it choosesMain weakness
Round-robin DNSRotates through several addressesIgnores server load and user location
Health-checked, weighted, or location-based DNSUses health, weights, or locationChanges wait for caches to expire
Geographically distributed DNS serversUsers reach a DNS server nearbyYou must run and manage many locations
AnycastOne address, the network picks the nearest siteDepends on internet routing
CDN with DNSThe CDN's DNS returns the best edge serverHelps most for content that can be cached

Key Takeaways

  • DNS can choose which IP address to return, so it can spread load and avoid failed servers before traffic reaches them.
  • Round-robin DNS rotates through several addresses for one name. It ignores each server's real load and the user's location, so traffic can be uneven.
  • Health-checked, weighted, and location-based DNS choose answers with more information, but every change waits for cached answers to expire.
  • Geographically distributed DNS servers give nearby users faster answers and keep working if one location fails.
  • Anycast lets many servers share one IP address. The network routes each query to the nearest server, and it fails over to the next closest one automatically.
  • A CDN uses its own DNS server to return the address of the best edge server for each user.
  • Large systems use DNS to pick a region, and load balancers to spread requests inside it.

DNS gives every user an address, and the choice of that address is the first place a system can spread load and avoid failures. That completes the DNS chapter. Next is a Flashcards Review of the key terms, followed by the Chapter Assessment.

Practice Questions

Try each question first, then open the answer.

1. example.com uses round-robin DNS with three A records, and one of the three servers crashes. What happens to users, and why is round-robin DNS alone risky here?

<details> <summary>Show answer</summary>

Some users are still sent to the crashed server. Round-robin DNS does not check server health, so it keeps returning the failed address. Even after someone removes the address, cached copies keep sending users there until their TTL expires. Some clients retry another address, but many users see errors. Health-checked DNS or a load balancer avoids this.

</details>

2. A site uses round-robin DNS, and every query gets the addresses in a different order. Why can one server still receive much more traffic than the others?

<details> <summary>Show answer</summary>

Because answers are cached and shared. A large resolver can serve thousands of users. It may cache one answer and give the same first address to all of them until the TTL expires. Round-robin DNS also ignores how busy each server is, and some requests need much more work than others.

</details>

3. A DNS service uses anycast, with the same IP address announced from sites in Tokyo, Frankfurt, and Virginia. The Tokyo site goes offline. What happens to users in Tokyo?

<details> <summary>Show answer</summary>

Their queries automatically reach the next nearest site. When the Tokyo site goes offline, it stops announcing the shared address. The network then routes queries for that address to another site, like Virginia or Frankfurt. Users do not change any settings, and the DNS operator does not change any records. Answers may be slower because the site is farther away.

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4. A website uses a CDN. How does DNS send a user in Madrid to an edge server in Madrid, instead of a server on another continent?

<details> <summary>Show answer</summary>

The CDN's own DNS server chooses the edge server. The website's name is a CNAME alias for the CDN's host name. When the user's resolver looks it up, the CDN's DNS server sees where the query comes from. It returns the IP address of a nearby edge server in Madrid, and the browser connects there.

</details>

5. A team wants to send 10 percent of its users to a new version of a service. Which DNS technique fits, and what is its main drawback?

<details> <summary>Show answer</summary>

Weighted DNS. It returns the new version's address in about 10 percent of answers. The drawback is caching. One resolver's cached answer may serve many users, so the real split is only approximate. Changing the weights also takes effect only after the TTL expires. A load balancer can split traffic per request, much more precisely.

</details>
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