Distributed Systems Engineer (L4), Content Engineering

Netflix

Design and implement an LRU (Least Recently Used) cache. Your cache should support the following operations: get(key) - Gets the value (will always be positive) of the key if the key exists in the cache, otherwise returns -1. put(key, value) - Sets or inserts the value if the key is not already present. When the cache reaches its capacity, it should invalidate the least recently used item before inserting a new item. For the purpose of this question, when a new key is inserted, regard it as most recently used. The cache is initialized with a positive capacity. Example: LRUCache cache = new LRUCache(2); // capacity is 2 cache.put(1, 1); cache.put(2, 2); cache.get(1); // returns 1 cache.put(3, 3); // evicts key 2 cache.get(2); // returns -1 (not found) cache.put(4, 4); // evicts key 1 cache.get(1); // returns -1 (not found) cache.get(3); // returns 3 cache.get(4); // returns 4 Follow up: Could you do both operations in O(1) time complexity?

Netflix

High-Level Design for Zero-Downtime Live Production Systems Imagine you're tasked with designing a live production system that requires zero downtime during deployments and updates. This system handles a large volume of requests and is critical to the business. Let's consider a scenario: Scenario: You are building a service that provides real-time stock quotes to users. The service needs to be highly available and scalable to handle peak loads. Deployments must not interrupt the service, ensuring users always receive the latest data. Questions to address in your design: High-Level Architecture: Describe the overall architecture of the system. Include key components, their responsibilities, and how they interact. Deployment Strategy: Detail the deployment strategy you would use to achieve zero downtime. Explain the steps involved in deploying new versions of the service. Load Balancing: How would you distribute traffic across different instances of the service to ensure high availability and prevent overload? Monitoring and Rollback: What monitoring tools and metrics would you use to detect issues during deployment? Describe the rollback strategy in case of a failed deployment. Data Consistency: How would you ensure data consistency across different instances of the service during updates? Scaling: How would you scale the system horizontally to handle increased traffic? Explain each of these areas with consideration to both the design and the practical steps required for running such a system in live production. Consider specific technologies and tools where appropriate to illustrate your understanding. This question aims to assess your understanding of designing and operating highly available systems, your knowledge of deployment strategies, and your ability to handle real-world challenges in a production environment.

Netflix

Tell me about a time you had to make a difficult decision with incomplete information. What was the situation? What information was missing? What decision did you make and how did you arrive at it? What was the outcome? What did you learn from the experience? For example, perhaps you had to decide whether to launch a new feature without complete user testing data, or whether to pursue a new market opportunity without a full understanding of the competitive landscape. Maybe you had to make a critical hiring decision without all the information you needed about the candidate's past performance. The key is to show that you can assess risks, weigh potential outcomes, and make sound judgments even when things are uncertain. Be sure to articulate the reasoning that led you to your decision, and reflect on the lessons you learned from the experience. This demonstrates your adaptability, problem-solving abilities, and your capacity for learning and growth.