I had a pseudonymous social media project and talked through multithreading and a few other concurrency angles.
Start by briefly describing the project's purpose, your role, and the architecture, then focus on the scalability challenges you observed. Propose concrete improvements like horizontal scaling, caching, and database sharding, and explain the trade-offs involved, especially in the context of Walmart's high-traffic e-commerce environment.
Pro tip: Quantify the impact of your improvements with metrics like latency reduction or throughput increase, and relate them to Walmart's scale (e.g., millions of concurrent users during peak events).
Briefly describe the project's goal, your role, and the tech stack. Highlight the system's scale and any scalability issues encountered.
Explain the existing architecture and identify specific bottlenecks (e.g., database, application servers, network) that limit scalability.
Propose concrete improvements such as horizontal scaling, caching, database sharding, asynchronous processing, and load balancing. Explain how each addresses the bottlenecks.
Discuss the trade-offs of your proposals, including cost, complexity, consistency, and maintainability. Show awareness of Walmart's constraints like cost-efficiency and reliability.
Quantify the expected improvements (e.g., reduced latency, increased throughput) and how you would measure success. Tie back to business goals like handling peak traffic.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by defining load balancers and their core purpose, then explain how they are used in backend systems with examples of algorithms and deployment patterns. Finally, connect to Walmart's scale by discussing trade-offs like health checks, session persistence, and global load balancing.
Pro tip: Mention that load balancers are not just for distributing traffic but also for improving reliability and security, and that at Walmart's scale, they often use a combination of L4 and L7 load balancers with health checks and auto-scaling.
Explain that a load balancer is a system that distributes incoming network traffic across multiple servers to ensure no single server is overwhelmed.
Discuss key benefits: high availability, scalability, fault tolerance, and improved performance.
Mention algorithms like round robin, least connections, IP hash, and weighted distribution, and when to use each.
Cover hardware vs software load balancers, cloud-based (e.g., AWS ELB), and global server load balancing (GSLB) for multi-region setups.
Relate to Walmart's e-commerce scale: handling peak traffic, session persistence, health checks, and integration with auto-scaling and microservices.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.