When I first interviewed at a big tech company, one of the toughest rounds was system design. They’d throw vague, massive problems at me — “Design a system that handles millions of users streaming product data simultaneously.” Intimidating, right?
Fast forward to when I was tasked with designing a Walmart-level interview platform for system design rounds. This project taught me loads about scalability, reliability, and user experience — and today, I want to share those lessons with you.
Whether you’re prepping for a system design interview or building a platform for interviews in your team, here’s a story-driven, technically rich guide to help you navigate the process.
1. Start With Core Requirements: What Does a Walmart-Scale System Design Interview Platform Even Need?
Before jumping into architectures or tech stacks, clarify what you’re building.
My starting point was simple questions:
- Will candidates and interviewers be on video calls or just in a text-based environment?
- How many simultaneous interviews should the platform support? Walmart interviews can run hundreds daily.
- How complex are the tasks? Will candidates design distributed systems live? Will they need a shared whiteboard?
- What about recording, note-taking, and evaluation?
For example, Walmart’s interviewing might involve:
- Real-time code collaboration
- System design diagram tools (think UML, sequence diagrams)
- Stable video/audio communication
- Automated interviewer scheduling & feedback collection
(Pro tip) Use a checklist like this before you design: Educative.io guide to system design requirements.
2. Make Scalability a Non-Negotiable Foundation
Walmart’s scale means thousands of interviews monthly across multiple regions. So, your platform must scale horizontally.
What this taught me:
- Build the platform as microservices instead of a monolith. For example, separate services for video streaming, code collaboration, scheduling, and notifications.
- Use load balancers and auto-scaling groups — AWS Elastic Load Balancer and Kubernetes pods work wonders here.
- Cache frequently accessed data like candidate profiles or past interviews with Redis or Memcached.
Engineering tradeoff: Microservices add complexity and operational overhead but vastly improve scalability and development velocity.
For a low-level walkthrough of scalable interview platforms, ByteByteGo offers fantastic architecture explanations.
3. Real-Time Collaboration Needs Real-Time Systems
System design often involves whiteboards and collaborative coding shared in real time.
My first version used polling for updates — every 5 seconds, the front end would query the backend for changes. Ugh. That caused latency and poor user experience.
Solution? WebSockets or WebRTC.
- Use WebSockets for bidirectional, low-latency message passing (updates to diagrams, code).
- Use WebRTC for peer-to-peer video/audio streams — reduces server load, improves video quality.
Lesson: Real-time systems require event-driven architectures. Use messaging queues like Kafka or RabbitMQ to connect components asynchronously.
4. Handling Network Failures and Edge Cases
During a stakeholder demo, the video feed froze—dread moment. I realized we had no retry or failover logic.
Solution:
- Implement client-side buffering and reconnection logic.
- Use health checks and circuit breakers on services.
- For the backend, use multi-region replication to handle outages—AWS Global Accelerator helps with routing users to the nearest healthy data center.
Framework: Plan for failure early. Design your platform on the assumption that network partitions and server outages will happen.
DesignGurus.io has great failover patterns for distributed systems.
5. Recording and Playback: More Than Just Storage
We wanted interviewers to review past sessions. But raw recordings take terabytes quickly!
Insights:
- Store video streams in compressed formats and segment files.
- Use AWS S3 with lifecycle policies to expire old recordings.
- Build a player UI allowing timestamped annotations.
- Index recordings with metadata (candidate name, interviewer, score) for search.
Tradeoff: Real-time recording adds latency. Offload recording responsibilities to a dedicated service so it doesn’t degrade interaction quality.
6. Security and Privacy: Because Candidate Data Is Sensitive
The platform would handle resumes, interview recordings, and feedback — sensitive data.
Key security measures:
- Use end-to-end encryption for video streams.
- Secure sensitive APIs with OAuth 2.0.
- Audit logs for interview actions (who viewed what, when).
- GDPR compliance if interviewing candidates internationally.
I also implemented role-based access control to limit data exposure.
Security is not just implementation, it’s culture. Start early and review often.
7. Automate Recruiting Workflow Integration
The tech is useless if interview data isn’t captured and integrated.
I built hooks from the interview platform into Walmart’s ATS (applicant tracking system):
- Auto-send scores and feedback after each session.
- Use webhooks to update candidate status automatically.
- Enable interviewers to schedule follow-ups directly inside the platform.
Pro tip: APIs and webhooks are your friends for seamless workflow automation. Without them, recruiters are stuck double-entering data.
Final Thoughts: You’re Closer Than You Think
Designing this platform pushed me into deep systems thinking and real-world constraints. What started as a dry feature list turned into a living product with users, failures, and lessons.
If you’re prepping for system design interviews or building your own interviewing tool:
- Start with clear requirements.
- Prioritize scalability and reliability.
- Embrace real-time architectures.
- Plan for failure modes.
- Secure user data meticulously.
- Ensure smooth integration with existing workflows.
Remember, no design is perfect. Iterate fast, listen to users, and keep learning.
And hey—whenever I feel stuck, I remind myself: If I can build a platform that scales to Walmart’s hiring needs, you can definitely design better systems too.
Stay curious and keep building.
References and Further Reading
- Grokking the System Design Interview - Educative.io
- ByteByteGo YouTube Channel – System Design Deep Dives
- DesignGurus.io – Distributed Systems Patterns
- AWS Architecture Guides
Did this story help you? Share your system design wins and war stories below — let’s learn together!
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