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LinkedIn·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
Jul 2026

Summary

LinkedIn system design screen for a software engineer role. One question, but it had a lot of surface area and I don't think I covered everything they were looking for.

Questions Asked (1)

Q1

You're given a basic web architecture: client hits DNS, then a load balancer, then an app service, then a database. The app service also calls a third-party external API. Walk through the potential issues with this setup and propose concrete improvements around scalability, reliability, and observability.

System DesignTechnical Trade-offsAPI & Integrations
Author's notes

I jumped straight into database scaling and talked about read replicas for a while, which felt safe.

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AI HintsAI Generated

Suggested Approach

Start by mapping each component and its failure modes, then systematically address scalability, reliability, and observability with concrete improvements. Prioritize high-impact changes and tie them to LinkedIn's scale and reliability expectations.

Pro tip: Frame trade-offs explicitly (e.g., caching vs. consistency) and mention how you'd measure success with SLOs and dashboards—this shows you think like an owner, not just a coder.

1. Map the architecture and failure modes

Walk through each hop (DNS, LB, app, DB, external API) and identify single points of failure, bottlenecks, and dependency risks. Call out what happens when each component degrades or fails.

2. Address scalability

Propose horizontal scaling for app and DB (read replicas, sharding), caching layers (CDN, Redis), and async processing for external API calls. Discuss load balancing strategies and auto-scaling.

3. Improve reliability

Introduce redundancy (multi-AZ, multi-region), circuit breakers, retries with exponential backoff, timeouts, and fallbacks for the external API. Consider rate limiting and bulkheads.

4. Enhance observability

Add structured logging, distributed tracing (e.g., OpenTelemetry), and metrics (latency, error rates, saturation). Define SLOs and alerts, and use dashboards for real-time monitoring.

5. Prioritize and summarize trade-offs

Rank improvements by impact and effort, and explain trade-offs (e.g., consistency vs. availability). Conclude with a phased rollout plan and success metrics.

Key Points to Mention

  • DNS: TTL, failover, and geo-routing for latency and resilience.
  • Load balancer: health checks, SSL termination, and layer 4 vs. layer 7 considerations.
  • App service: stateless design, horizontal scaling, and caching to reduce DB load.
  • Database: replication, sharding, connection pooling, and read/write splitting.
  • External API: circuit breaker, retry with backoff, timeout, fallback, and caching.
  • Observability: distributed tracing, metrics, logging, SLOs, and alerting.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.