Top Google system design interview questions

As a former software engineer and interviewer at Meta and Microsoft, I can say from my experience that system design interviews (SDIs) at top companies can be challenging for most candidates.

Most software engineers have never worked practically on such systems. Despite this lack of hands-on experience, candidates must be prepared to have in-depth theoretical discussions covering technologies they may have never interacted with.

Moreover, Google coding interviews are famously tricky. Google has extremely high standards for analyzing technical capabilities and a rigorous multi-phase interview loop designed to vet out suboptimal candidates.

Passing Google’s system design interview is the dream of many software engineers, but to do so, you need to be extremely well-prepared. Fortunately, Google is transparent about its expectations, which means you can succeed with proper practice and hard work.

Today, we’ll discuss the hiring process and the top system design interview questions commonly asked at Google.

The hiring process at Google

Google has an extremely rigorous hiring process that aims to filter the best technically capable candidates with a fair process, as illustrated below:

Interview tips by Google

Luckily, Google defines clear rubrics for analyzing candidates to ensure fairness and equality for everyone. Each interviewer rates candidates on six or seven parameters, ranging from strong no-hire to strong hire.

To keep fairness, Google also provides some tips to ace the interviews as follows:

• Show empathy to end users

• Good communication is essential to succeed in the interview:

  • Provide a roadmap by structuring your answer

  • Think out loud—provide a clear thought process and approach

  • Write or draw things down where needed

  • Actively engage the interviewer with genuine conversation

  • Be confident—take pauses or breaks to reflect and proceed

  • Listen actively—ensure you understand the problem and ask follow-up questions if needed.

• You can always do better and can improve by iterating:

  • Consider edge cases and evaluate your solution

  • Be creative and explore multiple alternatives

• Manage your time

• Practice is the key to success

Let’s discuss top system design interview questions asked at Google.

System design interview questions by Google

Google focuses on asking open-ended questions to analyze how a candidate approaches a problem. The system design interview is the main round to analyze such skills because the questions require problem-solving skills to define an optimal solution. The commonly asked system design problems at Google are listed below:

Let’s explore a few of the commonly asked system design problems.

Design Google Maps

Problem statement: Design a scalable system that helps users travel by providing optimal paths through a map, distance, and estimated travel time.

We can start with the requirements of the system as described in the problem statement:

High-level design

We use an API gateway, a load balancer, and microservices such as maps, places, location finder, route finder, and navigation services to handle user requests. We also employ a pub-sub service to communicate effectively between the services and users. We can use a graph database to efficiently store and retrieve locations along with other databases.

Common concerns

In a system design interview, candidates should be able to answer the following questions while approaching a design:

• How can the system efficiently handle real-time data from millions of users?

• What data structure and algorithm is best for quickly finding the shortest path?

• How can the system remain available during server or network failure?

• How do we ensure real-time data accuracy for traffic conditions, road closures, and new routes?

• What caching strategies can be employed to lower response time?

To explore in depth to get the answer to the above questions, check out the detailed chapters on the Google Maps system and Google Maps API designs.

Design Uber

Problem statement: Design a ride-sharing service that connects/matches riders with drivers based on location. The service should also be able to navigate the route and notify the rider and driver about updates.

Based on this, we can think of a few requirements as listed below:

High-level design

The system should accept riders’ requests for rides, and in return, the trip service should provide an ETA based on different vehicle types. The system should return nearby drivers to connect with based on the selected vehicle type. The system should also provide real-time updates to both and should be able to update ETAs based on different conditions for an ongoing trip.

Common concerns

• In a scenario of an event in a city, how would you keep the latency as low as possible?

• How would you design an efficient geospatial indexing to quickly match riders with drivers?

• How would you update the ETA during a ride in peak hours?

• How would you design the ride request handling system to efficiently manage the surge in demand?

Designing the Uber backend addresses the system design, advanced issues, and key considerations of Uber. Our chapter on the Uber system design covers all the necessary details to design a scalable ride-sharing service.

Design a typeahead

Problem statement: Design a typeahead system that provides a list of suggestions to complete a query based on the user’s search history, the current context of the search, and trending content across different users and regions.

High-level design

The system should be able to take a query when a user starts typing and quickly return the top $N$ suggestions based on the typed characters. The services that compute suggestions should be responsive and adaptable to changing characters. Moreover, it should analyze the query and store it for future use. It should be able to handle millions of concurrent requests from the users.

Common concerns

• How would you ensure fast response time for user input?

• How will you enable the system to handle millions of concurrent user requests?

• How will the system handle typos, misspellings, and partial inputs?

• How will the system adjust to the users who type very quickly?

We’ve discussed the common problems and tools to consider for a search-engine-related service like this. We also have a chapter that comprehensively discusses a complete system design of typeahead.

Design a video streaming service

Problem statement: Design a video streaming service like YouTube that allows users to upload and stream videos. The service should be able to store numerous videos and their metadata and should return accurate results for a search query.

High-level design

We expect that the system should be able to manage millions of simultaneous requests for searching, streaming, and uploading videos for a service like YouTube. The upload service should seamlessly handle content uploads, passing them through encoders and decoders to support multiple formats. The streaming service should generate a manifest file, allowing the nearest CDN to deliver the content to users efficiently. The search service must also deliver quick and relevant results based on user queries.

Common concerns

There are some common issues with streaming services like YouTube, Netflix, Amazon Prime Video, etc. Consider the following:

• How will the system scale to handle millions of users and video streams concurrently?

• How to store numerous videos and encode and transcode them in different formats efficiently?

• How will the system provide a personalized experience to each user with recommendations?

• How does the system react to a sudden drop in the network, shifting to low-quality, buffering content, etc.?

You can explore the YouTube system design and YouTube API design to better understand the steps or tools to address the above concerns.

Design a messenger

Problem statement: Design a chat service that allows users to securely chat with each other individually or in a group. The service should allow sharing of media files, storing chat data along with media files, and providing chat statuses like read receipts or viewed.

Let’s list the requirements of the service based on the problem statement:

High-level design

The messaging service should allow real-time communication between users, enabling instant message delivery and allowing users to send photos, videos, and files. Consistency is paramount in delivering messages to the correct recipients and in order. Moreover, the system should store messages securely so users can access their chat history across different devices. Finally, security is important, and the system should ensure privacy and protect user data from unauthorized access.

Common concerns

• How would you ensure instant delivery of messages?

• How would you enable the system to deliver messages in order even when the recipients are offline?

• How would you ensure the security and privacy of messages?

• How would the system efficiently store and retrieve large amounts of messages and media files?

• When the app is not in use, how are the notifications delivered or messages queued to be sent later?

We’ve figured out the common issues that arise when designing a chat service. You can explore the WhatsApp system design and Facebook messenger API design to dive deeper and find answers to the listed issues.

You now know how to approach a design problem in an interview. We have provided resources that can help you understand the concepts better to answer the interviewer’s questions (listed as common concerns) by exploring those resources.

Now, let’s go through the approach to prepare for system design interviews.

How to prepare for the interview

After conducting many interviews at Meta, Microsoft, and Educative, my advice for you is to follow a strategic plan to prepare and ace the system design interview at Google. A typical approach would be to consider the following steps:

1. The first step is to revise the fundamental concepts of a system. The system design guide covers all the basic concepts that you should be able to talk about. Moreover, you should explore the building blocks of a system to better understand their use and functionality in different systems.

2. You should use a practical approach to design a system that tackles all the details needed to design. RESHADED, a high-level system design interview strategy, can help you easily crack complex system design problems.

3. Practice is the key to success, so try to design real-world problems and continuously improve with feedback from peers, seniors, and ex-Google employees.

4. Mock interviews can help you improve, as you can understand the possible questions you might face during a real interview. You can take advantage of the AI mock interviews to get hands-on practice with real-world problems and constructive feedback to improve.

Conclusion

In this blog, I’ve discussed the hiring process of Google, which I hope will help you prepare accordingly. Google’s system design interview is challenging, but this blog covered the most commonly asked system design problems at Google and possible challenging questions or common issues for each that my colleagues at Google might ask.

I also made sure to link you to the most related content to enhance your knowledge and understanding of distributed systems. You can explore the following courses:

Happy learning!