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Computer Science & IT 18 min read

System Design: Scalable Architecture for High-Traffic Govt Portals & CAP Theorem

Senior technical roles in NIC, C-DAC, and PSUs increasingly assess architectural design principles for national-scale digital public infrastructure (like Aadhaar, UPI, and Sarkari result portals).

#System Design#Scalability#CAP Theorem#Redis#Microservices

In-Depth Interview Questions & Model Solutions

Q1How would you architect a Government Result Checking Portal that must handle 5 million concurrent requests upon result release?

Architecture strategy: (1) Static Asset Decoupling: Offload HTML/CSS/JS to a CDN (Cloudflare/Akamai/NIC CDN). (2) Multi-Tier Caching: Pre-generate student result payloads and cache them in an in-memory Redis cluster with Read Replicas (sub-millisecond lookups). (3) Rate Limiting & Queue: Implement token bucket rate limiting at NGINX API Gateway with Kafka queue to throttle surge queries. (4) Read-Only Database Replicas: Separate write OLTP database from sharded read replicas. (5) Static PDF Offloading: Host bulk result merit PDFs on distributed object storage with signed CDN links.

Key Technical Takeaways:
  • CDN edge caching prevents 80% traffic from hitting backend servers.
  • Redis cluster with key sharding handles millions of Read QPS.
  • Graceful degradation with fallback static mirror servers.

Q2Explain the CAP Theorem and PACELC extension with practical examples.

CAP states that in a distributed data store experiencing a Network Partition (P), you can guarantee either Consistency (C - every read receives the most recent write) or Availability (A - every request receives a non-error response without guarantee of latest write). PACELC extends this: if there is a Partition (P), how does system trade Availability (A) vs Consistency (C); Else (E), how does it trade Latency (L) vs Consistency (C)? Example: MongoDB is PC/EC; Cassandra is PA/EL; DynamoDB is configurable PA/EL.

Key Technical Takeaways:
  • RDBMS (Postgres/MySQL master-slave): CP or CA without partitions.
  • Cassandra / DynamoDB: AP prioritizing high availability and eventual consistency.
  • PACELC addresses normal operating conditions when no network fault exists.

Technical Panel Interview Strategy Tips

  • Mention horizontal scaling over vertical scaling and explain stateless application server clusters.
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