System Design Table of Content

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Url Shortener

Here we are going to design a url shortener system.

Questions for clear scope

Can you give an example of how a URL shortener work? –

What is the traffic volume? – 100 million URLs are generated per day.

How long is the shortened URL? – as short as possible

What characters are allowed in the shortened URL? – Shortened URL can be a combination of numbers (0-9) and characters (a-z, A- Z).

Can shortened URLs be deleted or updated? – For simplicity, let us assume shortened URLs cannot be deleted or updated.

Here are the basic use cases:

  1. URL shortening: given a long URL => return a much shorter URL
  2. URL redirecting: given a shorter URL => redirect to the original URL
  3. High availability, scalability, and fault tolerance considerations

Solution with Base 62 conversion

Base conversion is an approach commonly used for URL shorteners. Base conversion helps to convert the same number between its different number representation systems. Base 62 conversion is used as there are 62 possible characters for hashValue.

Conversion of 11157 to base 62

The short url is

  1. longURL is the input.
  2. The system checks if the longURL is in the database.
  3. If it is, it means the longURL was converted to shortURL before. In this case, fetch the shortURL from the database and return it to the client.
  4. If not, the longURL is new. A new unique ID (primary key) Is generated by the unique ID generator.
  5. Convert the ID to shortURL with base 62 conversion.
  6. Create a new database row with the ID, shortURL, and longURL.

To make the flow easier to understand, let us look at a concrete example.

  • Assuming the input longURL is: • Unique ID generator returns ID: 2009215674938.
  • Convert the ID to shortURL using the base 62 conversion. ID (2009215674938) is converted to “zn9edcu”.
  • Save ID, shortURL, and longURL to the database

Comparison of Hash solution vs Base 62 conversion

As you can see Base 62 conversion is the clear winner.


March 14, 2019

Chat System

A chat app performs different functions for different people. It is extremely important to nail down the exact requirements. For example, you do not want to design a system that focuses on group chat when the interviewer has one-on-one chat in mind. It is important to explore the feature requirements.

It is vital to agree on the type of chat app to design. In the marketplace, there are one-on-one chat apps like Facebook Messenger, WeChat, and WhatsApp, office chat apps that focus on group chat like Slack, or game chat apps, like Discord, that focus on large group interaction and low voice chat latency.

The first set of clarification questions should nail down what the interviewer has in mind exactly when she asks you to design a chat system. At the very least, figure out if you should focus on a one-on-one chat or group chat app.

Questions to ask for exact scope

What kind of chat app shall we design? 1 on 1 or group based? – It should support both 1 on 1 and group chat.

Is this a mobile app? Or a web app? Or both? – both

What is the scale of this app? A startup app or massive scale? – It should support 50 million daily active users (DAU).

For group chat, what is the group member limit? – A maximum of 100 people

What features are important for the chat app? Can it support attachment? – 1 on 1 chat, group chat, online indicator. The system only supports text messages.

Is there a message size limit? – Yes, text length should be less than 100,000 characters long.

Is end-to-end encryption required? – Not required for now but we will discuss that if time allows.

How long shall we store the chat history? – forever

These are the requirements based on the questions above:

  • A one-on-one chat with low delivery latency
  • Small group chat (max of 100 people)
  • Online presence
  • Multiple device support. The same account can be logged in to multiple accounts at the same time.
  • Push notifications

Clients do not communicate directly with each other. Instead, each client connects to a chat service, which supports all the features mentioned above. Let us focus on fundamental operations. The chat service must support the following functions:

  • Receive messages from other clients.
  • Find the right recipients for each message and relay the message to the recipients.
  • If a recipient is not online, hold the messages for that recipient on the server until she is online.

When a client intends to start a chat, it connects the chats service using one or more network protocols. For a chat service, the choice of network protocols is important.

Requests are initiated by the client for most client/server applications. This is also true for the sender side of a chat application. When the sender sends a message to the receiver via the chat service, it uses the time-tested HTTP protocol, which is the most common web protocol. In this scenario, the client opens a HTTP connection with the chat service and sends the message, informing the service to send the message to the receiver. However, the receiver side is a bit more complicated. Since HTTP is client-initiated, it is not trivial to send messages from the server. Over the years, many techniques are used to simulate a server-initiated connection: polling, long polling, and WebSocket.

Polling – polling is a technique that the client periodically asks the server if there are messages available. Depending on polling frequency, polling could be costly. It could consume precious server resources to answer a question that offers no as an answer most of the time.

Long Polling – in long polling, a client holds the connection open until there are actually new messages available or a timeout threshold has been reached. Once the client receives new messages, it immediately sends another request to the server, restarting the process. Long polling has a few drawbacks:

  • Sender and receiver may not connect to the same chat server. HTTP based servers are usually stateless. If you use round robin for load balancing, the server that receives the message might not have a long-polling connection with the client who receives the message.
  • A server has no good way to tell if a client is disconnected.
  • It is inefficient. If a user does not chat much, long polling still makes periodic connections after timeouts.

Websocket – webSocket is the most common solution for sending asynchronous updates from server to client. WebSocket connection is initiated by the client. It is bi-directional and persistent. It starts its life as a HTTP connection and could be “upgraded” via some well-defined handshake to a WebSocket connection. Through this persistent connection, a server could send updates to a client.

  • WebSocket connections generally work even if a firewall is in place. This is because they use port 80 or 443 which are also used by HTTP/HTTPS connections.
  • Earlier we said that on the sender side HTTP is a fine protocol to use, but since WebSocket is bidirectional, there is no strong technical reason not to use it also for sending.


No technologist would design such a scale in a single server. Single server design is a deal breaker due to many factors. The single point of failure is the biggest among them. We suggest having a presence server.

Here the client maintains a persistent WebSocket connection to a chat server for real-time messaging.

  • Chat servers facilitate message sending/receiving.
  • Presence servers manage online/offline status.
  • API servers handle everything including user login, signup, change profile, etc.
  • Notification servers send push notifications.
  • Finally, the key-value store is used to store chat history. When an offline user comes online, she will see all her previous chat history.


Selecting the correct storage system that supports all of our use cases is crucial. We recommend key-value stores for the following reasons:

  • Key-value stores allow easy horizontal scaling.
  • Key-value stores provide very low latency to access data.
  • Relational databases do not handle long tail of data well. When the indexes grow large, random access is expensive.
  • Key-value stores are adopted by other proven reliable chat applications. For example, both Facebook messenger and Discord use key-value stores. Facebook messenger uses HBase, and Discord uses Cassandra.


One on One chat flow

  1. User A sends a chat message to Chat server 1.
  2. Chat server 1 obtains a message ID from the ID generator.
  3. Chat server 1 sends the message to the message sync queue.
  4. The message is stored in a key-value store.
  5. If User B is online, the message is forwarded to Chat server 2 where User B is connected
  6. If User B is offline, a push notification is sent from push notification (PN) servers.
  7. Chat server 2 forwards the message to User B. There is a persistent WebSocket connection between User B and Chat server 2.

Message synchronization across multiple devices

Each device maintains a variable called cur_max_message_id, which keeps track of the latest message ID on the device. Messages that satisfy the following two conditions are considered as news messages:

  • The recipient ID is equal to the currently logged-in user ID.
  • Message ID in the key-value store is larger than cur_max_message_id .

With distinct cur_max_message_id on each device, message synchronization is easy as each device can get new messages from the KV store.

Group chat

March 10, 2019

Unique ID Generator

In this chapter, you are asked to design a unique ID generator for a distributed system. Your first thought might be to use a primary key with the auto_increment attribute in a traditional database. However, auto_increment does not work in a distributed environment because a single database server is not large enough and generating unique IDs across multiple databases with minimal delay is challenging.

Here is an example.

Questions to ask for clear scope

What are the characteristics of unique IDs? – IDs must be unique and sortable.

For each new record, does ID increment by 1? – The ID increments by time but not necessarily only increments by 1. IDs created in the evening are larger than those created in the morning on the same day.

Do IDs only contain numerical values? – Yes, that is correct.

What is the ID length requirement? – IDs should fit into 64-bit.

What is the scale of the system? – The system should be able to generate 10,000 IDs per second.

Now here are the requirements gathered from questions above:

  • IDs must be unique.
  • IDs are numerical values only.
  • IDs fit into 64-bit.
  • IDs are ordered by date.
  • Ability to generate over 10,000 unique IDs per second.


Datacenter IDs and machine IDs are chosen at the startup time, generally fixed once the system is up running. Any changes in datacenter IDs and machine IDs require careful review since an accidental change in those values can lead to ID conflicts. Timestamp and sequence numbers are generated when the ID generator is running.


The most important 41 bits make up the timestamp section. As timestamps grow with time, IDs are sortable by time. Figure below shows an example of how binary representation is converted to UTC. You can also convert UTC back to binary representation using a similar method.

Sequence number

12 bits. For every ID generated on that machine/process, the sequence number is incremented by 1. The number is reset to 0 every millisecond.

There are other alternatives but they don’t work as well as the soluton above according to our requirements.

UUID is worth mentioning here as an alternative. If our requirements include that IDs are 128 bits long instead of 64 bits long or can be non-numeric then UUID will work.

March 9, 2019

Notification System

A notification system has already become a very popular feature for many applications in recent years. A notification alerts a user with important information like breaking news, product updates, events, offerings, etc. It has become an indispensable part of our daily life. In this chapter, you are asked to design a notification system.

A notification is more than just mobile push notification. Three types of notification formats are: mobile push notification, SMS message, and Email. Figure 10-1 shows an example of each of these notifications.




Service 1 to N: They represent different services that send notifications via APIs provided by notification servers.

Notification servers: They provide the following functionalities:

  • Provide APIs for services to send notifications. Those APIs are only accessible internally or by verified clients to prevent spams.
  • Carry out basic validations to verify emails, phone numbers, etc.
  • Query the database or cache to fetch data needed to render a notification. • Put notification data to message queues for parallel processing.

Cache: User info, device info, notification templates are cached.

DB: It stores data about user, notification, settings, etc.

Message queues: They remove dependencies between components. Message queues serve as buffers when high volumes of notifications are to be sent out. Each notification type is assigned with a distinct message queue so an outage in one third-party service will not affect other notification types.

Workers: Workers are a list of servers that pull notification events from message queues and send them to the corresponding third-party services.

Third-party services: Already explained in the initial design.

iOS, Android, SMS, Email: Already explained in the initial design.

Now, let us examine how every component works together to send a notification:

  1. A service calls APIs provided by notification servers to send notifications.
  2. Notification servers fetch metadata such as user info, device token, and notification setting from the cache or database.
  3. A notification event is sent to the corresponding queue for processing. For instance, an iOS push notification event is sent to the iOS PN queue.
  4. Workers pull notification events from message queues. 5. Workers send notifications to third party services.
  5. Third-party services send notifications to user devices.

How to prevent data loss?

One of the most important requirements in a notification system is that it cannot lose data. Notifications can usually be delayed or re-ordered, but never lost. To satisfy this requirement, the notification system persists notification data in a database and implements a retry mechanism.

Will recipients receive a notification exactly once?

The short answer is no. Although notification is delivered exactly once most of the time, the distributed nature could result in duplicate notifications. To reduce the duplication occurrence, we introduce a dedupe mechanism and handle each failure case carefully. Here is a simple dedupe logic:

When a notification event first arrives, we check if it is seen before by checking the event ID. If it is seen before, it is discarded. Otherwise, we will send out the notification.

Notification template

A large notification system sends out millions of notifications per day, and many of these notifications follow a similar format. Notification templates are introduced to avoid building every notification from scratch. A notification template is a preformatted notification to create your unique notification by customizing parameters, styling, tracking links, etc. Here is an example template of push notifications.

You dreamed of it. We dared it. [ITEM NAME] is back — only until [DATE]. CTA:
Order Now. Or, Save My [ITEM NAME]
The benefits of using notification templates include maintaining a consistent format, reducing the margin error, and saving time.

Notification setting

Users generally receive way too many notifications daily and they can easily feel overwhelmed. Thus, many websites and apps give users fine-grained control over notification settings. This information is stored in the notification setting table, with the following fields:

user_id bigInt
channel varchar # push notification, email or SMS 
opt_in boolean # opt-in to receive notification

Before any notification is sent to a user, we first check if a user is opted-in to receive this type of notification.

Rate limiting

To avoid overwhelming users with too many notifications, we can limit the number of notifications a user can receive. This is important because receivers could turn off notifications completely if we send too often.

Retry mechanism

When a third-party service fails to send a notification, the notification will be added to the message queue for retrying. If the problem persists, an alert will be sent out to developers.

Here is the final design, many new components are added in comparison with the previous design.

  • The notification servers are equipped with two more critical features: authentication and rate-limiting.
  • We also add a retry mechanism to handle notification failures. If the system fails to send notifications, they are put back in the messaging queue and the workers will retry for a predefined number of times.
  • Furthermore, notification templates provide a consistent and efficient notification creation process.
  • Finally, monitoring and tracking systems are added for system health checks and future improvements.

March 5, 2019


What is system design?

System design is the process of designing the elements of a system such as the architecture, modules and components, the different interfaces of those components and the data that goes through that system. It is meant to satisfy specific needs and requirements of a business or organization through the engineering of a coherent and well-running system.

What is the purpose of system design

The purpose of the System Design process is to provide sufficient detailed data and information about the system and its system elements to enable the implementation consistent with architectural entities as defined in models and views of the system architecture.

How do you design a system?
(we are using a chat app as an example)

    • Step #1 understand the requirements or the problem. In most cases, when you given a new feature or a new system to develop, you are not given all the little details that you need to know. It is always a good idea to ask questions about the requirements. You might not have the domain knowledge to even understand the requirements. For example, you have to design tinder but you have never used a dating app before. If that is the case, ask for more information. The better you understand the requirements the more likely you will design a system that meets the expected outcome. One of the many important things you need to know(from the beginning) is the scope of the problem. You have to figure out what you are working to solve and what can be pushed until later. You also need to know how you will need to scale the system.
      – What kind of chat app shall we design? 1 on 1 or group based?
      – Is this a mobile app? Or a web app? Or both?
      – What is the scale of this app? A startup app or massive scale?
      – For group chat, what is the group member limit?
      – Is there a message size limit?
      – How long shall we store the chat history?
      – What network bandwidth usage are we expecting? This will be crucial in deciding how we will manage traffic and balance load between servers.
    •  Step #2 propose high-level design. In this step, draw up a high-level design using wireframe or flow chart that represents the players/entities of the system. You should draw this flow chart from the requirements. Make sure you confirm with product owner that this is what he has in mind. For our example, here are the main entities we are dealing with: sender, receiver, and chat service which is what connects them. Don’t forget to focus on the main functionalities of the system and not the little details.

      You also can walk through how the system will function from a very high level(1000 ft view). 


  • Step #3 deep dive. In this step, you dive into APIs and endpoints. You also dive into the data model of each entity in the system.

    For endpoints
    Users: create, update
    Messages: message, timeCreated, destination, etc

    For data model
    User: firstName, lastName, displayName, email, password, etc
    Group: id, list of users

    Also talk about which programming language, framework, cloud infrastructure, etc to use.

    You also walk through a happy path of how a user uses the system.

  • Step #4  identify and resolve problems. Try to discuss as many bottlenecks as possible and different approaches to mitigate them. 


March 4, 2019