The All-in-One System Design Master Template

The System Design interview (SDI) evaluates a candidate’s ability to build robust and scalable systems. In SDIs, multiple solutions to a problem exist that are open for discussion and iteration, unlike coding interviews with usually a single best or optimal solution. 

System Design interviews are not just about solving a problem—they also test your ability to think beyond the now, envisioning how a system can scale, adapt, and remain resilient under growing pressure. It’s about anticipating the future, planning for growth, and designing a system that can evolve as demand changes across time. This is where a System Design master template becomes essential.

Rather than tackling each new project from scratch or learning by trial and error, a structured template helps you create a blueprint that incorporates best practices, proven strategies, and scalable architecture. Think of it as a cheatsheet for designing complex systems efficiently. In an interview, having this boilerplate design in mind can demonstrate that you understand how to build systems and how to build them to last. 

The following is a System Design master template by Educative, meticulously crafted by ex-FAANG engineers:

Case study of Twitter (now known as X)#

Disclaimer: For this tech blog, we’ll refer to X (the social networking site) as Twitter.

Let’s see how a real-world system like Twitter struggled to keep up with scaling challenges because of its architecture.

In its early years, Twitter started with a simple idea and as a side project: letting users share short, 140-character messages with the world. Like many startups, the initial focus was on shipping the product quickly rather than building a robust infrastructure. The system was simple, with a single server, a basic database, and minimal redundancy, and that was fine at first.

A System Design template isn’t just about building a system that works––it’s about building one that thrives, even when success exceeds your wildest expectations. 

Key takeaways#

In this blog, I’ll cover the following:

• Take a step-wise approach to developing a master template for System Design.

• Start with a basic system at 50,000 feet and gradually evolve the application’s design, assuming growth in user demand and features/services.

• Design a real-world application with the master template.

Let’s start with the crucial components and services.

System Design template#

I understand that it’s not easy to familiarize yourself with all the elements in a typical System Design. So, in this template, I’ve divided all these elements into three categories and listed them below:

Supporting services#

• Media/file upload service

• Recommendation system

• ML/AI engine

• Data processing system

• Payment system

• Compliance service

• WebRTC service

Let’s use these components to gradually build the System Design template, guided by the different challenges an application faces during its evolution at various stages.

Stage 1: The basic setup#

Scenario: Let’s create a simple social media platform. At this early stage, the focus is quickly getting the core functionality up and running. Initially, users can sign up, write posts, and read posts from others.

The architecture is minimal—a single application server handles all the operations from user authentication to serving web pages, while a relational database stores all the user data and posts. This straightforward setup is perfect for a small-scale project with limited users or a startup just getting off the ground.

However, this basic system has significant limitations. With everything running on a single server, it can only handle a limited number of users before performance starts to degrade. Also, if this single server fails, the service becomes unavailable.

Now, imagine the platform goes viral, and thousands of users sign up and post content simultaneously. The server becomes overwhelmed, requests start to time out, and users experience slow response times or crashes like Twitter’s fail whale. It becomes apparent to make the system scalable for growth.

Stage 2: Scaling for traffic#

To handle increased traffic, improve reliability, and prepare for future growth, we’ll need to introduce new components and break down the system into more manageable parts, such as:

• Multiple application servers

• Load balancers

• Replication of databases

We can start by deploying multiple application servers to distribute the load, ensuring no single server becomes a bottleneck. The next thing to add is a load balancer to evenly distribute incoming user requests across these servers, improving response times and reducing the risk of downtime. Additionally, we can replicate a database where data is copied across multiple database instances. This setup improves performance by spreading read operations across replicas while the primary database handles write operations.

These improvements ensure the system can now handle the increased load; however, this setup is not without its challenges. As the platform grows, we might still face issues such as uneven load distribution, bottlenecks in database writes, and difficulties in managing the increased complexity of multiple servers.

For example, during a major viral event, even a well-balanced system might struggle with sudden traffic spikes or fail to efficiently handle complex queries. We must introduce advanced features and redundancy measures to enhance resilience and ensure the service’s high availability.

Stage 3: Ensuring high availability#

To meet users’ expectation of the platform to be available 24/7, even during peak traffic or unexpected server failures, let’s introduce advanced components and techniques like:

• Database sharding

• Shard manager

• Backup and recovery service

Database sharding involves splitting the database into smaller, more manageable pieces called shards. Each shard is responsible for a subset of data. This reduces the load on any database instance and allows for more efficient query processing.

On the other hand, horizontal scaling involves adding more servers to the system as needed rather than upgrading existing ones. This approach not only improves performance but also enhances fault tolerance. Additionally, we can implement a failover mechanismIn this mechanism, standby servers automatically take over if a primary server goes down, ensuring minimal disruption. by having a backup of servers and data.

After ensuring availability and resilience through backups, replicas, and sharding, the next focus is to enhance the application’s control. As the platform scales, managing traffic efficiently, offloading heavy tasks, and safeguarding against unwanted requests become especially challenging. Let’s discuss how we can achieve this control.

Stage 4: Streamlining traffic and task management#

In this stage, we introduce crucial components that centralize request management, improve task handling, and enable the system to handle spikes in requests within a timeframe, such as:

• API gateway

• Rate limiter

• Worker servers

• Task scheduler

• Distributed ID generator

The API gateway is added as a centralized request manager that manages routing, authentication, API versioning, and overall traffic. We also add a rate limiter to help control traffic spikes by capping the number of requests a user can make within a given timeframe. This protects the system from being overwhelmed by bots or users making numerous requests simultaneously.

To further optimize the application, we can deploy worker servers. These servers handle time-consuming tasks that don’t require immediate user feedback, such as processing images or running data analysis jobs. We can ensure that the core functions of the platform remain fast and efficient. To coordinate these tasks efficiently, we deploy a task scheduler on top of workers that balances the workload and acts as a bridge between application servers and workers.

We also add a distributed ID generator that ensures that every piece of event and data, including user interactions and background tasks, has a unique ID. This prevents conflicts and ensures data consistency across the platform, even as it scales.

While these enhancements significantly improve and streamline traffic and tasks, they also introduce more complexity. The platform will now face new performance and user experience challenges. Users want more flexibility and ease in using the platform. They now expect faster load times, real-time updates, and seamless interaction with the application. That’s where we’ll need to focus on optimizing performance and introducing real-time processing capabilities in the system.

This brings us to shift our focus to optimizing system performance, implementing real-time processing, and integrating advanced services like caching and queuing to further enhance scalability and user experience.

Stage 5: Optimizing performance#

To optimize performance and add real-time processing to enhance user experience and scalability, we’ll introduce the following advanced components:

• Cache

• Content delivery network

• Pub/Sub system

A cache layer is added to store frequently accessed data, reducing the need to query the database repeatedly, hence reducing latency. For example, popular posts, user profiles, and other frequently accessed content can be stored in a cache, allowing the application to retrieve them almost instantly. Moreover, we can also deploy a content delivery network (CDN), from which we can quickly send static content to the users, effectively bringing the content closer to the user instead of the other way around.

We can also use a Pub/Sub system that handles queuing and real-time processing, enabling instant notifications for live comments, likes, and share updates. This also offloads tasks that can run in the background from application servers to the task scheduler, ensuring they remain responsive to user requests while supporting real-time interactions.

As the platform grows and becomes accessible in new regions, user expectations change, requiring us to add more interesting features. To facilitate growth, the next step is to make the platform feature-rich; you know—it’s time to beat the competition.

Stage 6: Feature expansion#

For our social media application, we will start by allowing users to upload and interact with rich media content like photos and videos and leave comments, likes, dislikes, etc. To support these features, we’ll need to integrate key components such as:

• Media/file upload system

• Blog store

• Search service

• Sharded counters

• WebRTC service

A media/file service processes larger media files such as videos and processes them through transcoders to convert them to multiple formats later to be served according to users’ network conditions. The processed files can be stored in a blob storage that is purposefully used to store large files and accommodate media file storage as the requirements grow.

We can also deploy a powerful search engine or service to let the users search content. This service indexes data and supports advanced querying, enabling users to locate videos, comments, or profiles based on user names, keywords, or tags.

Moreover, to provide a real-time experience to users, we have already introduced a Pub/Sub service that sends real-time notifications as soon as an interaction happens.

Now that the platform has almost all the features, let’s add a new feature enabling another way of interaction for users to have direct real-time communication. To facilitate that, WebSockets can be implemented to establish a persistent connection between users, allowing continuous data exchange for instant and low-latency communication. A webRTC service can be integrated to manage peer-to-peer connections, enabling users to securely engage in real-time voice, video, or text chats.

With the inclusion of components like a file system, elastic search service, and sharded counters, we have successfully introduced new features to our users. However, managing, optimizing, and scaling these components will require advanced strategies.

This triggers our focus on implementing advanced analytics to provide accurate search results and recommendation systems to make the user experience personalized. Let’s do that.

Stage 7: Personalization and intelligence#

To give a personalized experience to users with optimized search results and premium services, we can introduce the following components:

• Recommendation system

• Data processing service

• ML/AI engine

• Payment system

A recommendation system ensures that each user receives personalized content, posts, or newsfeeds. It employs smart algorithms to recommend content through machine learning. It also employs a data processing service that processes data in real-time and batch mode. The processed data is passed through an ML/AI engine, combining collaborative filteringA filtering technique to recommend content based on the behavior of similar users or items., content-based filteringA filtering technique to recommend content based on similarities between items or content based on metadata and content features., and a hybrid approach to recommend personalized content.

We can also add a payment system that allows users to unlock premium features or monetize content. This service securely handles transactions, enabling a new revenue stream.

Everything looks amazing now; we’ve updated the system to provide personalized content, enabled users to interact more, and enabled monetization and premium features. With so many features, users, and global coverage, we now need to ensure our service can scale up or down based on demand, follow the regulations of different regions, and ensure configurations are up to date.

Let’s focus on components that help us achieve all this.

Stage 8: Compliance and system management #

We can introduce some key components to ensure our service is scalable, manageable, and follows the regulations of different regions:

• Auto-scaling

• Web servers

• Authentication and authorization service

• Compliance and configuration services

• Cluster manager

Auto-scaling is integrated to dynamically adjust resources based on traffic patterns, ensuring the platform remains responsive during peak usage while optimizing costs during off-peak times. We can lower the load on application servers by serving static content, such as web pages, CSS files, images, etc., through web servers. It improves load distribution, decouples application logic from web request handling, and enhances user experience. We can introduce a separate authentication and authorization (Authn and Authz) service to allow application servers to handle core functionalities-related requests. Initially, this was managed within the application service, but as the platform scales, a separate service ensures more secure and efficient handling of user identities, access control, and permission across the system.

A compliance service can manage and enforce data protection and regulations as the platform expands its service to different regions. It ensures users’ data is handled securely and in accordance with local laws. Moreover, a configuration service can manage settings across the platform from a centralized location. This allows for consistent and efficient deployment of changes, ensuring smooth operations as the platform grows and gets complex.

Lastly, when we talk about system management, we must introduce cluster managers to streamline the orchestration and management of components. Cluster managers automate deployment, scaling, and workload distribution across a cluster of machines, ensuring optimal resource use and high availability.

With these enhancements, the platform is better equipped to scale according to need, remain highly available, manage complexity, and stay compliant as it grows in newer regions.

In the last stage, we’ll dive into security, exploring how to protect the platform from emerging threats while maintaining the high performance and user experience established in previous stages.

Stage 9: Security and monitoring#

As the platform reaches its ultimate potential, ensuring it remains secure against emerging threats is critical. In this final stage, we focus on integrating key security components such as:

• Firewalls

• Monitoring and logging service

The components that are already integrated into our system, such as the Authn and Authz service, rate limiter, and API gateway, play a crucial role in maintaining the system’s security. These components with integrated security features ensure defense against DDoS attacks and unauthorized access. 

To further enhance security, firewalls can be employed to act as a barrier between the internal network and untrusted external networks, filtering incoming and outgoing traffic based on predetermined security rules. This helps prevent unauthorized access and protects the platform from malicious attacks.

A monitoring and logging system can be crucial for system management and security. The monitoring system can help us detect unusual patterns or potential breaches early by providing real-time insights into system activity. Logging maintains detailed records of system events, user activities, and security incidents. This data is crucial for identifying vulnerabilities in the system, responding to incidents, and maintaining a secure environment.

This is a comprehensive System Design master template that caters to all the needs of modern systems.

Note: If you are interested in exploring the nitty-gritty details of each component used in the System Design master template and taking your System Design skills to the next level, I highly recommend Educative’s popular Grokking Modern System Design Interview course.

In the next stage, let’s use this master template to design a real-world system that effectively balances performance, security, and user experience.

Stage 10: Designing YouTube with the master template#

YouTube design will leverage the essential components from our template to handle massive volumes of video content, users, and real-time streaming while ensuring scalability, performance, and security.

To start with, an API gateway will route user requests to appropriate services, with rate limiters preventing system overload during traffic spikes. Web servers will handle incoming traffic, serving static content such as video thumbnails and homepage data. Meanwhile, application servers will process dynamic requests like video upload, user authentication, and content search or recommendation. To manage video files, a media/file upload service will be in place, processing and storing videos in blob storage that is optimized for handling large datasets. Worker servers will manage background tasks such as video encoding and thumbnail generation coordinated with the task scheduler.

A Pub/Sub system will facilitate real-time communication between users and other microservices for real-time features such as live streaming and instant notifications. Sharded counters will track user interactions such as views, likes, comments, etc. Finally, a recommendation system powered by an ML/AI engine will enhance the user experience by suggesting videos based on viewing history, supported by a data processing system that analyzes user behavior.

Conclusion#

With the completion of our System Design master template and its application to a video streaming system, we’ve demonstrated how a thoughtfully structured approach can cater to the complexities of modern, large-scale systems. Each stage of the template adds critical components and optimizations, ensuring that the social media platform remains scalable, available, efficient, and secure as it grows. From handling basic user interactions to managing vast amounts of data and supporting real-time communication, this template provides a versatile foundation that can be adapted to various systems.

As you embark on your System Design journey, consider how this template can be customized to meet the unique needs of your application. Whether you’re building a social media platform, an e-commerce application, or any other complex system, the principles and components outlined here offer a strong starting point.

Now it’s your turn. Take the template, adapt it to your specific system, and start designing a real-world system that can scale to success.

Good luck and happy learning!