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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...
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posted on 13 Feb 2025
I was interviewed in Jan 2025.
posted on 5 Jun 2024
Design an ad-click aggregation service for tracking and analyzing ad clicks.
Use a distributed system to handle high volume of ad click data
Implement real-time processing for immediate insights on ad performance
Utilize a database to store aggregated ad click data for reporting and analysis
I applied via Approached by Company and was interviewed in Jul 2024. There were 3 interview rounds.
Normal DSA round from hacker rank
DSA round from hacker rank or leetcode
I applied via LinkedIn and was interviewed in Jan 2024. There was 1 interview round.
Merge two sorted arrays into the first array
Start from the end of both arrays and compare elements
Place the larger element at the end of the first array
Continue this process until all elements are merged
To scale a monolith architecture and improve response time, use horizontal scaling and implement caching.
Implement horizontal scaling by adding more instances of the monolith application behind a load balancer
Use a distributed cache to store frequently accessed data and reduce database queries
Implement caching at different levels such as application-level caching, database query caching, and HTTP response caching
Use a ...
Design a cache class with get(), put(), and initialization methods.
Define a class with a data structure to store key-value pairs.
Implement a get() method to retrieve a value from the cache based on a given key.
Implement a put() method to add or update a key-value pair in the cache.
Implement an initialization method to set the initial capacity and eviction policy of the cache.
Consider using a hash map or a linked list t...
I applied via LinkedIn and was interviewed in Apr 2024. There was 1 interview round.
Concurrency is the ability of a system to execute multiple tasks simultaneously.
Concurrency allows multiple tasks to run concurrently, improving performance and efficiency.
Concurrency can be achieved through multithreading or multiprocessing.
Example: A web server handling multiple requests simultaneously using multithreading.
ACID principles are a set of properties that guarantee database transactions are processed reliably.
Atomicity: Transactions are all or nothing. If one part of the transaction fails, the entire transaction is rolled back.
Consistency: Transactions bring the database from one valid state to another. All constraints are satisfied.
Isolation: Transactions are isolated from each other until they are completed.
Durability: Once...
posted on 25 Mar 2024
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