20 System Design Concepts Explained in 10 Minutes
Summary
TLDRThis video script offers an insightful guide for developers aiming to scale applications and enhance their system design skills. It covers essential concepts like vertical and horizontal scaling, load balancing, CDNs, caching, IP addressing, TCP/IP protocols, HTTP, REST, GraphQL, gRPC, WebSockets, and databases including SQL and NoSQL. It also delves into replication, sharding, and the CAP theorem, providing a comprehensive overview of building scalable and robust systems.
Takeaways
- 🚀 Vertical scaling involves adding more resources like RAM or upgrading the CPU to scale a server, but it has limitations.
- 🔄 Horizontal scaling adds server replicas to handle more requests, allowing for almost infinite scaling and redundancy but introduces complexity.
- 🔄 Load balancers distribute incoming requests to multiple servers, preventing overload and providing fault tolerance.
- 🌐 Content Delivery Networks (CDNs) serve static files from a network of servers worldwide to reduce latency and improve performance.
- 💾 Caching is a technique to store copies of data for faster retrieval, used at various levels including browser, disk, and CPU cache.
- 🌐 IP addresses uniquely identify network devices, and the Internet Protocol Suite (TCP/IP) defines the rules for data transmission over the internet.
- 🔄 TCP is a reliable protocol that ensures data packets are sent and received in order, and is the foundation for many other protocols like HTTP and WebSockets.
- 🌐 DNS translates domain names to IP addresses, with DNS records like A records mapping domains to server IP addresses for quick access.
- 📚 HTTP is an application-level protocol that simplifies data transmission over TCP, following a client-server model with request and response headers and bodies.
- 🔄 REST is a popular API pattern that standardizes HTTP APIs, making them stateless and following consistent guidelines for responses.
- 📈 GraphQL allows clients to make a single request to fetch exactly the resources they need, reducing over-fetching and the number of requests.
- 🔄 gRPC is an RPC framework that uses Protocol Buffers for efficient binary data serialization, improving performance over REST APIs that use JSON.
- 🔄 WebSockets enable bi-directional communication, allowing for real-time data transfer without the need for polling, as in chat applications.
- 💾 SQL databases organize data into tables and rows, providing efficient storage and retrieval with ACID compliance for reliability.
- 🔄 NoSQL databases drop the consistency requirement of ACID and the relational model, allowing for horizontal scaling and different data models like key-value, document, and graph stores.
- 🔄 Sharding and replication are techniques used in databases to scale horizontally and improve read performance, respectively.
- 🔄 The CAP theorem highlights the trade-offs in distributed systems between consistency, availability, and partition tolerance.
- 🔄 Message queues provide durable storage and can be used for decoupling parts of an application, allowing for asynchronous processing of data.
Q & A
What is the difference between vertical scaling and horizontal scaling?
-Vertical scaling involves adding more resources like RAM or upgrading the CPU of a single server, which is easy but limited. Horizontal scaling, on the other hand, involves adding replicas of the server to handle subsets of requests, allowing for almost infinite scaling and redundancy without requiring high-end machines.
Why is a load balancer necessary in a horizontally scaled system?
-A load balancer is needed to distribute incoming requests evenly across multiple servers, preventing any single server from being overloaded while others are underutilized. It also provides fault tolerance by ensuring that if one server fails, others can continue to handle requests.
What is a Content Delivery Network (CDN) and how does it work?
-A CDN is a network of servers distributed worldwide that serves static files like images, videos, and sometimes HTML, CSS, and JavaScript files. It works by caching copies of files from the origin server onto CDN servers, which can be done on a push or pull basis, reducing latency and improving load times for users.
What is the purpose of caching in computer networks?
-Caching is used to create copies of data so that it can be retrieved faster in the future. It reduces the need for repeated network requests, which can be expensive in terms of time and resources, by storing data at various levels, from browser cache to CPU cache.
How does the Domain Name System (DNS) translate domain names to IP addresses?
-The DNS is a decentralized service that maps domain names to IP addresses using DNS records, such as the A record for address mapping. When a DNS query is made, the system uses these records to retrieve the corresponding IP address, which is then cached by the operating system to avoid repeated queries.
What is the main advantage of using HTTP over TCP for web browsing?
-HTTP is an application-level protocol built on top of TCP that provides a higher level of abstraction, making it easier for developers to work with. It follows the client-server model and includes methods like GET and POST, which simplify the process of sending and receiving data over the internet without worrying about individual data packets.
What are the main differences between REST and GraphQL API patterns?
-REST is a standardization for HTTP APIs that makes them stateless and follows consistent guidelines, using different HTTP status codes to indicate success or error. GraphQL, introduced by Facebook, allows clients to make a single request and specify exactly which resources they need, reducing over-fetching and the number of requests made.
How does gRPC differ from REST in terms of performance?
-gRPC uses protocol buffers, which serialize data into a binary format that is more storage-efficient and faster to send over a network compared to JSON used in REST APIs. This results in a performance boost, especially for server-to-server communication.
What is the purpose of Websockets and how do they differ from HTTP?
-Websockets provide bi-directional communication, allowing for real-time data transfer between a client and server. Unlike HTTP, which requires polling to check for new data, Websockets push updates immediately when new data is available, making them ideal for applications like chat apps.
Why are databases like MySQL and PostgreSQL preferred over storing data in text files?
-Databases offer more efficient data storage using data structures like B-trees and allow for fast retrieval of data through SQL queries. They are also ACID-compliant, ensuring durability, isolation, atomicity, and consistency, which are crucial for maintaining data integrity.
What is the CAP theorem and how does it relate to database design?
-The CAP theorem states that in the presence of a network partition, a database can only guarantee two out of three properties: consistency, availability, and partition tolerance. It helps database designers make trade-offs in replicated systems, often choosing between consistency and availability based on the system's requirements.
What is message queuing and how does it benefit a system with high data intake?
-Message queuing involves using a system like a message queue to persist data before it can be processed, especially when the system receives more data than it can handle. This not only helps in managing data flow but also decouples different parts of an application, improving system architecture and reliability.
Outlines
🚀 Scaling Applications: Vertical vs. Horizontal Scaling
This paragraph introduces key concepts in system design, particularly focusing on scaling strategies for handling increased user load. It explains vertical scaling, which involves upgrading a single server’s resources, and contrasts it with horizontal scaling, where additional servers are added to distribute the load. The paragraph also highlights the importance of load balancers in horizontal scaling to ensure even distribution of requests and discusses the benefits of using content delivery networks (CDNs) for serving static files. Additionally, it briefly touches on caching mechanisms and the fundamentals of networking, such as IP addresses and TCP/IP protocols.
🌐 Understanding HTTP and API Patterns
This paragraph delves into the HTTP protocol and various API design patterns. It explains the client-server model and breaks down the components of an HTTP request into the header and body. The paragraph then introduces REST, a popular API pattern that emphasizes statelessness and consistent guidelines, and discusses how different HTTP status codes represent the outcome of requests. Other API patterns such as GraphQL, which allows more efficient data retrieval, and gRPC, which offers performance improvements through protocol buffers, are also covered. Additionally, WebSockets are mentioned as a solution for bi-directional communication, particularly useful in real-time applications like chat.
💾 Database Management: SQL, NoSQL, and Replication Strategies
This paragraph focuses on different database management approaches, starting with relational databases like SQL, which offer ACID compliance for data integrity. It then contrasts this with NoSQL databases, which are designed for horizontal scalability by dropping certain constraints like consistency. The paragraph also explores database scaling techniques such as sharding, which distributes data across multiple machines, and replication, where data is copied across different servers for redundancy and availability. It concludes by discussing the complexities of maintaining data consistency and availability in distributed systems, referencing the CAP theorem and PACELC theorem, and introduces message queues as a solution for handling large data streams.
Mindmap
Keywords
💡Vertical Scaling
💡Horizontal Scaling
💡Load Balancer
💡Content Delivery Network (CDN)
💡Caching
💡IP Address
💡TCP/IP
💡Domain Name System (DNS)
💡HTTP
💡REST
💡GraphQL
💡gRPC
💡WebSockets
💡SQL Database
💡NoSQL Database
💡Sharding
💡Replication
💡CAP Theorem
💡Message Queue
Highlights
Scaling apps from a single server to handling more users involves vertical and horizontal scaling.
Vertical scaling is limited, while horizontal scaling allows for almost infinite scalability with load balancing.
Load balancers distribute traffic evenly among servers to prevent overload and add fault tolerance.
Content Delivery Networks (CDNs) serve static files globally to reduce latency.
Caching techniques like CDNs improve data retrieval speed and reduce network requests.
IP addresses uniquely identify devices on a network, essential for computer communication.
TCP/IP protocols, including TCP and UDP, govern data transmission over the Internet.
Domain Name System (DNS) translates domain names to IP addresses for website access.
HTTP is an application-level protocol built on top of TCP for client-server communication.
REST API pattern standardizes stateless HTTP APIs with consistent response codes.
GraphQL allows for fetching specific resources in a single request, reducing over-fetching.
gRPC is an RPC framework using Protocol Buffers for efficient binary data serialization.
WebSockets enable bi-directional communication for real-time applications like chat apps.
SQL databases provide efficient data storage and retrieval with ACID compliance.
NoSQL databases sacrifice consistency for horizontal scaling and flexibility.
Sharding is a technique for horizontal scaling of databases using a Shard key.
Replication creates read-only copies of databases to scale reads, with leader-follower and leader-leader models.
The CAP theorem highlights the trade-offs between consistency, availability, and partition tolerance in distributed systems.
Message queues provide durable storage and enable system decoupling for data processing.
System design involves complex methods for efficient data storage and movement.
neetcode.io offers courses for beginners and interview preparation in system design.
Transcripts
do you want to level up from Junior Dev
so that you can build scalable apps or
maybe get a 100K pay Bump by passing
your system design interview round well
you're gonna need a box of neat codes 20
essential system Design Concepts which
include networking API patterns
databases and more all of which are
covered more extensively on neetcode.io
to start let's say you have a single
server which is accepting and fulfilling
requests for your application but now
we're getting more users so we need to
scale it the easiest thing to do would
be to add more resources like Ram or
maybe upgrade your CPU this is known as
vertical scaling it's pretty easy but
it's very limited a better approach
would be to add replicas so that each
server can handle a subset of requests
this is known as horizontal scaling it's
more powerful because we can almost
scale infinitely and we don't even need
good machines it also adds redundancy
and fault tolerance because if one of
our servers goes down all of the other
servers can continue to fulfill requests
this eliminates our previous single
point of failure but the downside is
that this approach is much more
complicated first of all how do we
ensure that one server won't get
overloaded while the others sit idle
well for that we'll need a load balancer
which is just a server known as a
reverse proxy it directs incoming
requests to the appropriate server so we
can use an algorithm like round robin
which will balance traffic by cycling
through our pool of servers or we could
go with another approach like hashing
the incoming request ID in our case the
goal is to even the amount of traffic
each server is getting but if our
servers are located all around the world
we could even use a load balancer to
route a request to the nearest location
which brings us to content delivery
networks if you're just serving static
files like images videos and sometimes
even HTML CSS and JavaScript files you
can just use a CDN it's a network of
servers located all around the world
cdns don't really run any application
logic they work by taking files hosted
on your server aka the origin server and
copying them onto the CDN servers this
can be done either on a push or pull
basis but cdns are just one technique
for caching which is all about creating
copies of data so that it can be
refetched faster in the future making
Network requests can be expensive so our
browsers will sometimes cache data onto
our disk but reading disk can be
expensive so our computers will copy it
into memory but reading memory can be
expensive so our operating systems will
copy a subset of it into our L1 L2 or L3
CPU cache but how do computers
communicate with each other well well
every computer is assigned an IP address
which uniquely identifies a device on a
network and to round it all out we have
the poorly named TCP slash IP or the
Internet Protocol Suite since it
actually includes UDP as well what but
focusing on TCP for a second there has
to be some set of rules AKA protocols
that decide how we send data over the
Internet just like how in real life we
have a system that decides how we send
mail to each other usually when we send
data like files they're broken down into
individual packets and they're sent over
the internet and when they arrive at the
destination the packets are numbered so
that they can be reassembled in the same
order if some packets are missing TCP
ensures that they'll be resent this is
what makes it a reliable protocol and
why many other protocols like HTTP and
websockets are built on top of TCP but
when you type neetcode.io into your
search bar how does your computer know
which IP address it belongs to well for
that we have the domain name system
which is a largely decentralized service
that works to translate a domain to its
IP address when you buy a domain from a
DNS registrar you can create a dnsa
record which stands for address and then
you can enter the IP address of your
server so then when you search and your
computer makes a DNS query to get the IP
address it'll use the a record mapping
to get the address and then your
operating system will cache it so that
it doesn't need to make a DNS query
every single time but wait a minute why
do we usually use HTTP to view websites
well TCP is too low level we don't want
to have to worry about individual data
packets so we have an application Level
protocol like HTTP which is what
developers like like you and I actually
use on a day-to-day basis it follows the
client server model where a client will
initiate a request which includes two
parts one the request header think of
that as the shipping label you put on a
package it tells you where the package
is going who it's from and maybe some
other metadata about the package itself
the second part is the request body
which is basically the package contents
to test it out just open your Dev tools
Network Tab and click subscribe go on
always taking a closer look at the
request we can see that the response
also includes a header as well as a body
but even with HTTP there are multiple
API patterns we could follow the most
popular one being rest which is a
standardization around HTTP apis making
them stateless and following consistent
guidelines like a successful request
should include a 200 code in its
response header whereas a bad request
from the client would return a 400 code
and an issue with the server would
result in a 500 level code graphql is
another API pattern introduced by
Facebook in 2015. the idea is that
instead of making another request for
every single resource on your server
like you would do with rest with graphql
you can just make a single request AKA a
query and you can choose exactly which
resources you want to fetch this means
you can fetch multiple resources with a
single request and you also don't end up
over fetching any data that's not
actually needed another API pattern is
grpc though it's really considered a
framework released by Google in 2016 it
was also meant to be an improvement over
rest apis it's an RPC framework mainly
used for server-to-server communication
but there's also grpc web which allows
using grpc from a browser which has also
been growing quickly over the last few
years the performance boost comes from
protocol buffers comparing them to Json
which is what rest apis use protocol
buffers are an improvement in that data
is serialized into a binary format which
is usually more storage efficient and of
course sending less data over a network
will usually be faster the downside is
that Json is a lot more human readable
since it's just plain text another app
layer protocol is websockets to
understand the main problem that it
solves let's take chat apps for example
usually when someone sends you a message
you receive it immediately if we were to
implement this with HTTP we would have
to use polling where we would
periodically make a request to check if
there was a new message available for us
but unlike HTTP 1 websockets support
bi-directional communication so when you
get a new message it's immediately
pushed to your device and whenever you
send a message it's immediately pushed
to the receiver's device and for
actually storing data we have SQL or
relational database Management Systems
like MySQL and postgres but why should
we use a database when we can just store
everything in text files stored on disk
well with databases we can more
efficiently store data using data
structures like B trees and we have fast
retrieval of data using SQL queries
since data is organized into rows and
tables relational database Management
systems are usually acid compliant which
means that they offer durability because
data is stored on disk so even if a
machine restarts the data will still be
there isolation means that different
concurrent transactions won't interfere
with each other atomicity means that
every transaction is All or Nothing
lastly we have consistency which means
that foreign key and other constraints
will always be enforced this one is
really important because it led to the
creation of nosql or non-relational
databases consistency makes databases
harder to scale so no SQL databases drop
this constraint and the whole idea of
relations all together there are many
types of nosql databases but popular
ones include key value stores document
stores and graph databases but going
back to consistency for a second if we
don't have to enforce any foreign key
constraints that means we can break up
our database and scale it horizontally
with different machines this technique
is called sharding but how do we decide
which portion of the data to put on
which machine well for that we usually
have a Shard key so given a table of
people our Shard key could be the ID of
the person but sharding can get
complicated a simpler approach is
replication if we want to scale our
database reads we can make read-only
copies of our database this is called
leader follower replication wherever
every right will get sent to the leader
who sends those to the followers but
every read could go to a leader or a
follower there's also leader leader
replication where every replica can be
used to read or write but this can
result in inconsistent data so it would
be best to use it where you can have a
replica for every region in the world
for example it can be complex to keep
replicas in sync so the cap theorem was
created to weigh trade-offs with
replicated design it states that given a
network partition in a database as
database designers we can only choose to
favor either data consistency or data
availability what makes it confusing is
that consistency here means something
different than with acid it's a somewhat
controversial theorem which is why the
more complete pack else theorem was
created lastly we have message cues
they're kind of like databases because
they have durable storage and they can
be replicated for redundancy see or
sharded for scalability but they have
many use cases if our system was
receiving more data than it can process
it would be good to introduce a message
queue so that our data can be persisted
before we're able to process it in doing
so we also get the added benefit that
different parts of our app can become
decoupled and if you've learned anything
by now it's that software engineering is
all about finding new and complicated
ways to store and move data around if
you want to learn more you can check out
my system design for beginners course on
neetcode.io as well as my system design
interview course thank you for
supporting my work and I'll see you soon
Weitere ähnliche Videos ansehen
Types Of Network Protocol | TCP | IP | UDP | POP | SMTP | FTP | HTTPS |Computer Networks|Simplilearn
Redes de computadores - Protocolo TCP IP - Informática para concursos - Professor Danilo Vilanova
SQL Basics for Beginners | Learn SQL | SQL Tutorial for Beginners | Edureka
WHATSAPP System Design: Chat Messaging Systems for Interviews
Introduction to NoSQL databases
What are WebSockets? How is it different from HTTP?
5.0 / 5 (0 votes)