Airbnb DevOps Engineer Coding Questions

Airbnb employs a complex microservice architecture, and it's critical that our images are efficient and quick to build and deploy. Large image sizes can significantly slow down deployment and lead to wasted resources.
Problem statement: Given a base Dockerfile, optimize it for a microservice to improve build times and reduce image size. Your submission should include various best practices for Dockerfile optimization such as layering, caching, and minimizing unnecessary files.

• FROM: defines the base image.


• RUN: optimizes the build process by managing layers.


• COPY: only copies necessary files into the image.

Example 1:
Input: Dockerfile content with multiple unnecessary layers
Output: Optimized Dockerfile structure with minimal layers and required dependencies
Explanation: The optimized structure combines layers and properly adds only the necessary packages to reduce the final image size.
Constraints:

• Dockerfile must comply with best practices for microservices.


• Output must highlight trade-offs between simplicity and efficiency.

In order to protect our backend services from being overwhelmed by high traffic and ensure fair usage among our users, we need to implement a rate limiter. The rate limiter should allow only a certain number of requests within a defined time window.
Problem statement: Create a class RateLimiter that implements a sliding window mechanism to track requests per user and allows or denies requests based on the predefined limits.

• def __init__(self, limit: int, window: int) -> None: Initializes the rate limiter with a request limit of limit within a time window of window seconds.


• def allow_request(self, user_id: str, timestamp: int) -> bool: Returns True if the request from user_id at timestamp is allowed; otherwise returns False.

Example 1:
Input: limit = 5, window = 60, user_id = 'user1', Requests = [(1, 'user1'), (2, 'user1'), (3, 'user1'), (4, 'user1'), (5, 'user1'), (61, 'user1')]
Output: [True, True, True, True, True, False]
Explanation: The first five requests are allowed, but the sixth request is beyond the limit within the same time window.
Constraints:

• 1 <= limit <= 100


• 1 <= window <= 3600


• 1 <= timestamp <= 10^9