Technical Lead Software Engineer, Cloud Interconnect Networking

Google

Imagine you are developing a racing game. You need to implement a system that determines the placement of each car in the race at any given moment. The race track is a circular track of a fixed length. Each car has a unique ID and a current distance traveled from the starting line. Design a function that takes a list of cars, where each car is represented by its ID and distance traveled, and returns the current placement of each car, considering the circular nature of the track. For example, if the track length is 1000 meters and a car has traveled 1200 meters, its actual position on the track is 200 meters. Consider edge cases such as multiple cars having the same position. Can you implement a function that efficiently calculates and assigns placements to the cars based on their positions on the track?

Google

Let's design a simplified distributed key-value store. Assume we need to handle a high volume of read and write requests. The key-value store should support the following operations: get(key): Retrieves the value associated with the given key. put(key, value): Stores the value associated with the given key. Here are some specific considerations for the design: Scalability: The system should be able to scale horizontally to handle increasing amounts of data and traffic. Consider how data will be distributed across multiple servers. Consistency: Discuss the consistency model you would implement. Would you choose strong consistency or eventual consistency? What are the trade-offs? Provide a rationale for your choice. Elaborate on how your design ensures that reads return the most up-to-date data (or how it handles potential inconsistencies, if any). Fault Tolerance: How would the system handle server failures? Describe the mechanisms you would implement to ensure data durability and availability in the face of node failures. Explain the role of replication and how it impacts consistency. Data Partitioning: Describe your data partitioning strategy. Consider using techniques like consistent hashing or range-based partitioning. Explain how your chosen strategy affects load balancing and data locality. Provide a concrete example of how keys would be mapped to specific servers in your design. Caching: Where would you incorporate caching in your system to improve read performance? Discuss different caching strategies (e.g., client-side caching, server-side caching) and their implications. Walk me through the architectural components of your key-value store, including the roles of different servers, the communication protocols used, and the data flow for get and put operations. Explain any potential bottlenecks and how you would address them. For example, if consistent hashing is used, how do you handle nodes being added or removed from the cluster?

Google

Where do you see yourself in 5 years?