Software Dev Engineer, FTVX Team

Amazon

You are given an array of servers represented by their processing power. You want to join consecutive servers together to form larger, more powerful servers. You can only join server i with server i+1 if the processing power of server i+1 is strictly greater than the processing power of server i. This joining process can cascade, meaning that if you join i and i+1, and the new combined processing power is less than i+2, you can then join the combined server with i+2, and so on. The goal is to maximize the number of these larger servers. For example: Consider the array [1, 2, 3, 4, 5]. You can join 1 and 2 to form 3. Then you can join 3 and 3 to form 6. Then you can join 6 and 4 to form 10. Finally, you can join 10 and 5 to form 15, resulting in one server with processing power 15. Consider the array [5, 4, 3, 2, 1]. You cannot join any servers because the processing power is always decreasing. Consider the array [1, 3, 2, 4, 1, 5]. You can join 1 and 3 to get 4. You cannot join 4 and 2. You can join 2 and 4 to get 6. You cannot join 6 and 1. You can join 1 and 5 to get 6. The final servers will be [4, 6, 6]. Write a function that takes an array of integers representing server processing powers and returns the final array of server processing powers after performing all possible joins.

Amazon

Let's dive into a debugging scenario. Imagine you are working on a critical e-commerce platform used by millions of customers. During a peak shopping period (like Black Friday), you receive alerts indicating a significant slowdown in the checkout process. Customers are reporting that it takes an unusually long time to complete their purchases, and some are even experiencing transaction failures. This is directly impacting sales and customer satisfaction. Your team suspects a performance bottleneck somewhere in the system. The architecture involves multiple microservices, including a user authentication service, a product catalog service, an inventory service, a payment processing service, and an order management service. These services communicate with each other via REST APIs and message queues. The database consists of both relational (PostgreSQL) and NoSQL (Redis) databases. You have access to logging, monitoring tools (like Prometheus and Grafana), and distributed tracing (like Jaeger). How would you approach debugging this issue systematically, identify the root cause, and propose a solution? Be specific about the tools and techniques you would use at each stage. For example, walk me through what metrics you'd focus on, how you would narrow down the problematic service, and what steps you'd take to pinpoint the exact code or configuration causing the bottleneck. Provide specific examples of commands or queries you might use to gather data or test hypotheses. Also consider potential causes related to scaling, caching, database performance, and code inefficiencies. How would you ensure minimal disruption to the platform during the debugging process? How do you handle conflicting information or dead ends during debugging?

Amazon

Describe a time when a plan did not go as expected.