System Design Made Easy: A Step-by-Step Guide for 2024
In the past two decades, the world has made significant advancements in app or software development. Many companies that rely on digital products or services need a system design to sell their products and flourish their business. Even B2B or B2C companies need a system to survive in the digital era. Unfortunately, many of them don't have a system design. Due to this, their software or app has inconsistent UI elements.
So, they are always looking for any software developer who can design their system according to their requirements. In this case, having a guide to system design comes in handy.
For this reason, every fresh graduate or tech-savvy expert needs to know about system design. They can be asked different questions related to this field in every software development interview. Failing to answer them properly can lead to losing opportunities. So, they need to learn about this design aspect in detail.
That's why we are going to discuss some basic and advanced aspects of system design in this blog.

What is System Design?

System design is designing the software or hardware of a company by taking care of all of its guidelines and needs. You need to map out a system's datasets, architecture, modules, components, and interfaces. You need to consider every aspect of software and hardware, the type of data you need to store and the different ways to store it. You keep your system organized and well-defined to make sure the implementation process is smooth. Along with that, you should know the technologies and tools to design and implement the system.

How to Design a System?

It is a detailed tutorial on how you can design and implement a system. We have only discussed the basic steps in this tutorial that everyone should know. However, you may have to add more steps if your company and design require it.
Whether you are a software engineer or an architect, you must know the importance of system design in your life. System design involves deciding the interfaces, modules, or architecture of any product or system. The process involves planning the data design and then implementing it.
In short, system design is the road map, and then one has to implement it on any system. Codemia.io is one such platform where one can learn anything related to system design

1. Researching

The first thing you need to do is research. For this, you should have a long meeting with the company's members to learn about their requirements and guidelines and why they want the system design. After that, you should check the government guidelines about the system design of your specific country.
These requirements will tell you about the settings of different UI elements. It will tell you which colors you should add to your UI elements, what the font of your system should be so that it can be readable, and many more things. These guidelines will help you in making decisions regarding UI. Moreover, it will ensure that your system design is legal and accessible to your audience.

2. Planning

After researching, you need to make a blueprint of your system design. This means you need to plan the scalability, modules, and architecture of your system. You can do it by looking into the budget, resources and goals of your system design.
For example, if you are developing a customer relationship management system, you must outline its functionalities and team responsibilities.

3. Design System's Architectural Aspect

After researching and planning, you must design your system's architectural aspect. In it, you need to decide how to store your data and what module you should use. How many and which interface should you add to your system design? For this, you need to develop the blueprint and outline the dataset structure. Moreover, you need to think about consistency, scalability and other aspects of your system design.
For example, a social media platform needs high availability and partition tolerance more than consistency. But, a financial trading system may need more consistency than other factors. So, you need to keep these differences in mind while making the architecture of your system.

4. Choose the technology tools.

There are different programming languages, tools, dataset frameworks, and libraries that can be used to implement your architectural design. Among these, you need to choose those technology aspects that will match your system design. You should ensure you implement your system design easily through your chosen technology tools.

5. Design the Modules

You need to design the modules of your system design now. It means you need to add all the required modules that will make up the system. So, you need to identify the role of each module and determine the type of data each module will contain.

6. Implementation

After designing your whole system, you need to implement it now. For this, you need to look at different ways of how to turn this design into an operational one. An example of this is that developers can write code for your system's design. This step will also tell you about different bugs, gaps and issues in your system design.

7. Test and Validate

You need to test your system designs to ensure that they meet all the company's requirements. For this, you should expose your system to different world scenarios. You can ask a specific company team to use this tool to determine whether it meets their requirements and keeps up with their expectations.

In it, you should also make sure about the security and privacy of your software. You need to make sure that the company's data is secure and safe in your system design or not.

8. Maintenance

Designing software is not a one-time task. In fact, a software developer has to maintain the system design from time to time. To do this, you should fix bugs, regularly update the system, and address any emerging issues.

This is all about designing a system. You should have noticed a lot of unfamiliar terminology and concepts in this guide. In the next part, we will discuss all the basic concepts of system design in detail.
Key Concepts of System Designs:

• Latency

Latency refers to the ability of a system to respond to the queries. When a user sends a query to the system, it needs to evaluate, code it and respond. If the system takes time to respond, users may get frustrated. That's why it is measured in milliseconds and sometimes microseconds to check the efficiency of the server.
If your system has low latency, it will work smoothly. High latency can lead to lags and errors in the system. It is especially crucial in real-data systems such as financial trading systems, so you need to focus on it.

• Scalability

It refers to the ability of a system to handle large amounts of load and traffic without compromising on latency. Social media platforms get a large audience daily. So, they need high scalability to handle this large audience.
For this, you need to give strong computing power and servers to your system to handle increased traffic. You need to focus on your servers a lot. To make them powerful, there are two types of scalability:

1. Horizontal scaling- adding more machines to a system.
2. Vertical scaling- adding more power or resources to a single machine. Horizontal scaling is also known as scaling out. It means adding more hardware to your existing system. It will increase the power of your system as a whole. The pros of it are that you can scale your system as much as you can. You can divide the workload among different servers, and this system will not fail easily because there are various servers in it. But, the downfall is that it is difficult and complex to handle.

On the other hand, vertical scaling is known as scaling up. It means increasing the power of your hardware to increase its power. Then, that hardware will drive your whole system. It is beneficial because it is simple to implement and requires a lower initial cost. You just need to add any RAM or CPU to your existing system in it. However, the downfall is that there is a limit to its scalability. Moreover, if your hardware fails, your whole system will be gone.
This means that both types of scaling have limitations and strengths. Therefore, you need to choose one of them carefully according to your application requirements.

• Caching

Caching is small and cost-effective hardware or software for temporarily storing data. It stores data that is frequently used or requested by the client. So, storing it in a high-speed storage layer can reduce the load on the main system, and you can access it more easily and quickly than from the main memory.
If your client wants any data, they may search the cache. If they find the data, it will be a cache hit. But it will be a cache miss if they don't find it. In this case, they should take the data from the main memory and store it in the cache.
There are two main concepts in organizing and maintaining a cache. These are:

1. Cache Invalidation: It is removing the outdated data from your cache. It can happen when you frequently update data in your main memory. So, you need to update it in your cache, too. Otherwise, your users can get frustrated when they see old information even after updating their profile. For this, you can use a time-based, manual invalidation or dependency-based approach.
2. Cache Eviction: It removes excessive data from your cache to make space for the new one. The cache doesn't have a lot of space, so you need to delete the outdated or old data from time to time. Otherwise, new and updated data will not be stored. In this, there are different types of algorithms to do the task. These are "less recently used," "less frequently used," "most recently used," "random replacement," "last in first out," and "first in first out." They delete data according to their algorithms approach.

• Fault Tolerance

It involves your system keeping working even if one part of its server fails. You must ensure that your system keeps working properly in case of any errors or faults.
This doesn't mean that you need to make a system to avoid errors. In fact, it means making a system that can deal with errors. Scalability can play a great role in this regard.
Moreover, you should implement proper error-handling mechanisms in your system. Duplicating critical data in different servers and replicating data across different computers can also be a good approach for increasing the fault tolerance of your system.

• CAP Theorem

This theorem states that any system can't have all the properties simultaneously. The three main properties it discussed is

1. Consistency means that all data in your system is consistent throughout the time for every user. Every computer on which your data is present could see the same data and interface of your software at the same time. Consistency refers to having a consistent UI design so that every user can navigate the software without any difficulty. For this, the developer should have a consistent coding style, color scheme, documentation style and system design.
2. Availability is very similar to the fault tolerance concept. It means that your system should be available for every user to respond to without wasting any time. Your users should get a response from your server promptly. Availability is typically measured as the percentage of time your system takes to operate.
3. Partition Tolerance means that your system keeps functioning even in case of partition tolerance or communication failure among different computers (nodes). If your system is distributed among different nodes, partition tolerance will ensure that the failure in one data system or computer doesn't impact the other one. For this, there can be less or no communication between two computers operating the system. Partition tolerance is the exact opposite of consistency. That's why the CAP theorem states that you can't put both in one system. You have to choose one thing from them while making your system.

• Redundancy and Replication

These two concepts are crucial to enhancing the fault tolerance of a system. So, you need to understand them in detail.
Redundancy means duplicating servers' data so that they can work as a backup file. It enhances the system's reliability and overall performance. If one part of the system gets any error, you can use the backup file to keep the system running.
Replication refers to sharing information among redundant resources. There are different software and hardware components, and you can replicate the data to enhance its reliability. It is used in many database management systems. In it, the primary resource gets the original information and delivers the copies to different servers. These replica servers send a message when they get the data.

• Data Storage

We all know that data is crucial in each system. You need to store data so that your system keeps working at a good pace. For this, you need to determine how you can store data. There are four different methods of doing it.

1. Block Storage: In it, you can store data in equal sizes of blocks. It means you need to break down your data into blocks and then store them in physical storage. Each block will be given a unique identifier so you can easily identify it and access your data. You can store them anywhere you want in the system, as there is no fixed place.
2. Files Storage: The second method is storing your data in the form of files. In it, you need to store data in files, then save those files in the folder and put those folders in a directory. This is a hierarchical system of storing data, and you can't store large amounts of data in it. So, when data size starts increasing, this data storage method can become a headache.
3. Object Storage: If your system has large unstructured data and log files, then you need object storage. It can store large amounts of unstructured data and backup files, which helps in scalability. Moreover, it provides flexibility to your system if it is large and contains a bunch of data. However, you can't access it directly from operating systems.
4. Redundant Disk Array (RAID): We all know the importance of discs in storing data. However, the issue with some discs is that your data has no backup. So, if your disk gets any issues, your data will be gone. But, this is not the case with RAID. It is a redundant array of different inexpensive disks combined to work. So they are faster and provide more space for organizing data. It is a disk system that contains memory, multiple disks and one or more processors. The hardware of this system looks like a computer system but with a specialization in handling different disks. It is the best storage method if you are making any complex and large system. There are various levels of RAID, so you need to research them and choose the one that will suit your application. These are four main types of data storage systems. You may have seen that all of them are different and suitable for different systems. So, you need to choose the one that is suitable for your application.

• File Systems

These systems ensure how and where you can store data in your disk so that it can be accessible to the user and software. It manages the whole operation of internal disks, making sure that retrieving data and storing it is easy for every person.
This system performs different functions, such as:
● Storage management
● File naming
● Making directories
● Making folders
● Access rules

This system allows you to identify, retrieve, and manage the authorization of your files. There are two types of file systems you should know.

Google File System (GFS)

This file system is ideal for large data-intensive applications such as YouTube and Gmail. It is a scalable and fault-tolerant file-distributed system that can handle batch processing on large data sets. Its architecture consists of GFS clusters in a single master file with multiple servers. So multiple clients can access it. This file system is used for system-to-system interaction rather than user-to-user interaction.

Hadoop Distributed File System (HDFS)

This file system can handle large unstructured data sets and runs on commodity hardware. Its architectural system is very similar to the Google file system, but it is a simplified version. It means you can make this system easier than the GFS system. Moreover, you can store unstructured data in this file system.
So, these are some basic concepts you should know about software development. Now, we will discuss some design concepts.

Common Design Patterns

Every beginner should know some of the most famous system design patterns.

• Microservices

It includes breaking down your large application into small and manageable services. These microservices are independent, have their own code and can be maintained without any difficulty. Each service is given a specific function, and they are all made and deployed independently.
As they all are independent, they have a specific team working on them. When the limit of that microservice is completed, the team can scale it with ease. Moreover, these services can communicate with each other through Application Programming Interfaces (APIs).
This design provides various benefits. Some of these are:
● The system is easily scalable. Because every service is independent and has different teams.
● It provides improved fault tolerance to your system.
● It has faster deployment cycles, so that it can save you time.
But, they are complex and need extra care to keep working. This complexity includes the need for service discovery and inter-service communication. So, if you are working in a large and growing organization, only go with this design.

• Event Sourcing

Your application will be available in the form of a stream of events. You can find this system in your gaming platforms and financial systems where there is a need for a large number of updates. You can easily replay different events that can be useful for debugging. But you need extra storage and computational resources to maintain it.

• Proxy Servers

Proxy servers are channels between users and the internet. It sits in front of one or two web browsers and forwards clients' requests to a suitable server.
So, how does it work?
Well, let's suppose you send a request for an address. The traffic or information will flow from the proxy server that will direct your query toward the suitable address. The information from that address will also flow from the server before reaching you.
This server has a lot of benefits. Some of them are:
● It can be used to provide additional functionality such as caching, SSL termination and compression.
● Can control the internet usage of teenagers and children.
● It can provide enhanced security.
● Provide better privacy.
● It can give access to blocked resources.
● Improve performance and scalability of a system.
This means that it is an integral part of system design.

• Sharding

Sharding is the system design in which data is partitioned horizontally and can distribute the load on a system. The data can be available on multiple machines or computers. Each machine has its own specific dataset and responsibilities. When a query comes, it is directed to the machine that contains that specific data. It is done using the data partition key.
As data is distributed across different machines, the system is scalable and reliable. It has an enhanced capacity to deal with any query. There are three types of database sharding systems:
● Range based sharding
● Hash-based sharding
● Directory based sharding
However, this system design has some drawbacks, too. This includes the complex nature of the system. It is complex to understand and difficult to handle. You need consistent hashing, data replication, and partition-aware clients.
• Command Query Responsibility Segregation (CQRS)
You need this system design when you are designing any e-commerce system or application. Because it segregates the read and write systems from each other, they are two separate models for these two jobs that increase the scalability and performance of your system. It allows different strategies for storing data and caching it for read and write operations. So, it makes sure that both systems keep working smoothly without any worries. So, you can use this pattern on every system that receives a lot of queries in a day.
But, this design is complex as you need to make two different systems for reading and writing. Moreover, you need to maintain both of them, which can be a hassle.

• Circuit Breaker

You need this system design aspect in the distributed system. This is crucial to maintain the health of your complex system. The circuit breaker, as the name indicates, can detect any bug or error in your system and can trip. It will send you a message telling you that your system has some problems and that you need to fix them immediately. In this way, it can prevent the system from crashing down entirely.
These are some famous design patterns you should know because they can help you solve common problems in your system and make it more reliable for your users. Now, we are going to discuss some design patterns.
System Design Patterns
They are crucial in understanding and solving problems in your distributed system. Moreover, a lot of system design interviews ask questions related to these patterns. So, you should know of them to excel in your design interview.

• Bloom Fillers

They are probabilistic data structures used for membership testing in a system design. They can quickly determine whether an element is present in a set.
Quite confusing? Well, I will explain it with some examples.
If a user ID is already present on a system and someone else tries to create an ID with the same URL or username, Bloom Fillers will immediately detect and stop it. If you search for a malicious website, Chrome can use its Bloom Fillers to check whether the website is on the malicious list. The Bloom Fillers will give Chrome a complete overview of malicious website lists without going into detailed research.

So, how does it work? It is in a bit size with all the vectors set to zero. When a piece of information goes into a bit, its value becomes one. For example, when you read one article on Medium, its bloom fillers add that article in one of their bits. This ensures that Medium will not recommend the same article to you next time.
They are beneficial because they take up very little space. However, they can store data to a limit, and you can't delete data from them, so that they can be a bit of a hassle in some situations.

• Consistent Hashing

It is another crucial question in system design interviews. In this, the system distributes data across various computers or servers. These nodes are in a ring shape so that the data remains in a structured form. Each node is assigned a specific set of data, and it performs specific tasks.
When data arrives, its key is hashed, and it is stored in its node. This doesn't disturb other servers or the ring, ensuring that the whole system remains in structure.

• Merkle Trees

In Merkle trees, you store data in the form of a tree. It is also known as a hash tree. In it, every node is responsible for having two children. There is a parent node that has the hash of their children's hashes. In this way, data moves from downward to upward.
It has leaf nodes that contain the portion of the original data. The root node is the upper one that contains the hash of all the datasets in the tree under it.
In a distributed system, the Merkle tree makes sure that the data is consistent among all the nodes. These nodes can compare their data by checking each other's root nodes. In this way, they don't need to check all the data.

• Leader Election

Leader election is an interesting algorithm system in the distributed system. You all may have the idea that there are independent computers or nodes in this system that are handling specific data. These nodes select any computer as their leader. In this way, they simplified their management and increased their fault tolerance. If the leader fails, they can elect another one in its place to keep the system running.
To elect the leader, nodes communicate with each other and select the one with the highest computing power and availability. Now, the leader is responsible for handling all the tasks.
Some Common Types of Databases

• Relational Databases

This type of database uses Structured Query Language (SQL) to manage and manipulate that data. The data is stored in the form of tables. You can find various tables in it as this system organizes the data. Each table contains different rows and columns in it. The row contains information on a single entity, while the column contains information on a different data set. It is just like a phone number directory.
Popular SQL databases include:

1. MySQL: MySQL is an open-source relational database management system.
2. PostgreSQL: It has a version of SQL named pg/SQL. It performs more complex queries than SQL and follows the ACID properties for transactions. It uses foreign keys so we can keep our data normalized.
3. SQL Joins: You can access information from multiple tables simultaneously. It keeps the data normalized so there is low data redundancy.

• Non-Relational Databases

They are also known as "no SQL databases" because they do not contain SQL. This database is used to find and organize unstructured data. It does not have a fixed way to handle and store data.
For example, it can store data in a file folder containing information about a person's Instagram likes and online shopping preferences. So, it is used to scale mobile applications and the modern web.
There are different types of Non-Relational Databases:

1. Distributed Key-value stores: It stores data as a key-value pair and is often used as a caching layer. It is used for horizontal scalability. An example of this is Redis and Riak.
2. Document databases: They store data in the form of a semi-structured document. You can optimize and store large amounts of data in it. An example is Couchbase and MongoDB.
3. Graph Databases store data in the form of nodes and edges and handle data with complex relationships. They are used in applications that involve fraud detection, recommendation systems and social networking. Examples are JanusGraph and Neo4j.
4. Time-series Databases store time-stamped data. They are used for applications that monitor financial details and IoT. Prometheus and InfluxDB are examples. These are the types of databases. You have noticed the mention of "ACID properties" in PostgreSQL. This is another important phenomenon that you should know about databases. So, let's discuss it. What are ACID Properties? ACID properties maintain the integrity of a database system. They ensure that you can make changes in a database without any worries. The changes you make can remain consistent and isolated from other data. Moreover, these changes are saved in your database without errors or bugs. This makes your database reliable even in the face of any unexpected situation. So, you can access your database and make changes to it with the help of ACID properties. It is the acronym of four words that explain its whole purpose. These are: ● Atomicity: All the transactions in the database are atomic units. It includes all the instructions for the transaction. Atomicity makes sure that all those instructions are fulfilled when doing the transaction. If it is not, then none of them will be fulfilled. So, it prevents partially completed transactions from leaving the inconsistent database behind. ● Consistency: It makes sure that your data remains consistent or valid even when a transaction leaves the system. There should be no compromise on the integrity of the database system. ● Isolation: It keeps each transaction isolated from another one, making sure none of them impact each other. It is crucial when you are running multiple transactions in a system at the same time. ● Durability: It makes sure that the changes in the transaction remain in the system even when there is any system failure or bugs. It saves data from unexpected situations. So, this is about ACID properties.

Frequently Asked Questions

• What are distributed systems?

It is the collection of many computers that work together to make a single computer for the end user. All these computers have specific data in them and work independently. They also fail independently without affecting the system.

• What is HTTP?

HTTP is a type of scalable web application. It stands for HyperText Transfer Protocol. It dictates how messages should be sent, appropriate responses and how messages should be interpreted. These messages can be requests or responses.

It sends messages from source to destination or from sender to receiver. It follows the FIFO policy, so the message sent first will be delivered first. It also allows the computers of a system to communicate with each other without disturbing their primary tasks.

Conclusion

So, this is a full guide on how to design a system in the software development niche. This guide contains all the basic concepts that every fresher and tech person should know who wants to excel in software development or system designing. This blog contains all the information that is crucial to passing the interview for system design. You should remember all these terms before appearing in the system design interview. You should also remember that all these concepts will not fit into one single system. Each system has specific requirements, and you need to find which concepts will be applicable to your system. So, as a newer system designer, you should keep this fact in mind, too.