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I applied via Referral and was interviewed in Jul 2024. There were 2 interview rounds.
It was about DS Algo and Java garbage collection,multithreading
Rate limiter is a system that controls the rate of traffic sent or received by a network interface.
Implement a token bucket algorithm to track and limit the rate of requests
Use a sliding window algorithm to track the number of requests within a specific time frame
Consider using a distributed rate limiter for scalability and fault tolerance
I applied via LinkedIn and was interviewed before Jun 2022. There were 4 interview rounds.
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Calculate the number of subsets of a given set
The number of subsets of a set with n elements is 2^n
Include the empty set and the set itself in the count
For example, a set with 3 elements will have 2^3 = 8 subsets
Whatsapp low level design involves messaging, encryption, media sharing, and user authentication.
Use end-to-end encryption to secure messages
Implement message queues for real-time message delivery
Allow media sharing through file transfer protocols
Use OAuth for user authentication and authorization
I applied via Recruitment Consulltant and was interviewed in Apr 2024. There were 3 interview rounds.
Find the length of the longest consecutive elements sequence in an array.
Sort the array to ensure consecutive elements are adjacent
Iterate through the array and keep track of the current consecutive sequence length
Update the longest consecutive sequence length as you iterate
Executor Service is a framework provided by Java for managing and executing asynchronous tasks.
Executor Service allows you to easily create and manage threads for executing tasks.
It provides a way to control the number of threads used for executing tasks, which can help prevent resource exhaustion.
You can submit tasks to an Executor Service using methods like execute() or submit().
Executor Service can be used to execut...
posted on 22 May 2025
I appeared for an interview in Nov 2024, where I was asked the following questions.
Design a scalable task scheduler to manage and execute tasks efficiently based on priority and timing.
Define task attributes: ID, priority, execution time, and status.
Use a priority queue to manage task scheduling based on priority.
Implement worker threads to execute tasks concurrently.
Consider persistent storage for tasks to survive system restarts.
Provide an API for adding, updating, and removing tasks.
I have extensive experience in software development, focusing on scalable applications and team collaboration.
Led a team of 5 developers in creating a microservices architecture for a healthcare application, improving scalability by 40%.
Implemented CI/CD pipelines using Jenkins and Docker, reducing deployment time from hours to minutes.
Collaborated with cross-functional teams to gather requirements and deliver features...
posted on 25 Jun 2024
I applied via Approached by Company
Implement rate limiting for a platform serving 100K requests per second.
Use a token bucket algorithm to limit the rate of incoming requests.
Set a maximum number of tokens in the bucket to control the rate.
Refill the bucket at a constant rate to allow bursts of requests.
Track the timestamp of the last request to enforce the rate limit.
Consider using a distributed rate limiting system for scalability.
Monitor and adjust t...
I appeared for an interview in Jun 2025, where I was asked the following questions.
A rate limiter controls the number of requests a user can make to a service in a given timeframe.
Use a token bucket algorithm to allow bursts of requests while enforcing a limit over time.
Implement a sliding window counter to track requests in a specific time frame.
Consider using Redis for distributed rate limiting across multiple servers.
Example: Limit to 100 requests per minute per user.
Use HTTP headers to inform use...
I applied via Referral and was interviewed in Mar 2024. There was 1 interview round.
In-memory SQL databases store data in memory for faster access and processing.
In-memory databases keep all data in RAM for quicker retrieval compared to disk-based databases.
Examples include SQLite in-memory database and Redis.
They are commonly used for caching, real-time analytics, and temporary data storage.
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