Security Engineer, AWS Security Vulnerability Management

Amazon

Implement a Stack data structure using one or more Queues. Your stack should support the standard push, pop, top (peek), and empty operations. push(x):** Adds element x to the top of the stack. pop():** Removes the element on the top of the stack and returns it. top():** Returns the element on the top of the stack without removing it. empty():** Returns whether the stack is empty. For example, consider the following sequence of operations: push(1) push(2) top() // returns 2 pop() // returns 2 empty() // returns false Explain your approach clearly, focusing on how you would use queue operations (enqueue and dequeue) to achieve stack-like behavior. Discuss the time complexity of each operation in your implementation. Consider edge cases and potential optimizations.

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

Tell me about a time you exemplified one of Amazon's leadership principles. For example, consider the 'Customer Obsession' principle. Can you describe a situation where you went above and beyond to meet a customer's needs, even when it was challenging or required you to think outside the box? What specific actions did you take, and what was the outcome? Alternatively, let's explore the 'Bias for Action' principle. Share an instance where you had to make a quick decision with limited information. What was the situation, what factors did you consider, and how did you mitigate the risks associated with acting swiftly? Or perhaps you can elaborate on a time you demonstrated 'Ownership.' Describe a project or task where you took full responsibility for the outcome, even when things didn't go as planned. How did you handle the setbacks, and what did you learn from the experience? Another good principle to discuss could be 'Invent and Simplify.' Tell me about a time you created an innovative solution to a complex problem, while keeping it simple and easy to use. What was the problem, what was your solution, and how did you ensure its simplicity? Finally, tell me about a time where you had to 'Learn and Be Curious'.