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Load Balancing and Traffic Distribution Questions

Covers why load balancers are used and how traffic is distributed across backend servers to avoid single server bottlenecks, enable horizontal scaling, and provide fault tolerance. Candidates should know common distribution algorithms such as round robin, least connections, weighted balancing, and consistent hashing, and understand trade offs among them. Explain the difference between layer four and layer seven load balancing and the implications for routing, request inspection, and protocol awareness. Discuss stateless design versus stateful services, the impact of session affinity and sticky sessions, and alternatives such as external session stores or token based sessions to preserve scalability. Describe high availability and resilience patterns to mitigate a single point of failure, including active active and active passive configurations, health checks, connection draining, and global routing options such as DNS based and geo aware routing. At senior and staff levels, cover advanced capabilities like request routing based on metadata or headers, weighted traffic shifting for canary and blue green deployments, traffic mirroring, rate limiting and throttling, integration with autoscaling, and strategies for graceful degradation and backpressure. Also include operational concerns such as secure termination of transport layer security, connection pooling, caching and consistent hashing for caches, monitoring and observability, capacity planning, and common debugging and failure modes.

MediumTechnical
0 practiced
Define retry and timeout strategies at the client, load balancer and server layers to balance availability and the risk of duplicate processing. Address idempotency classification, retry-after headers, exponential backoff limits, and how load balancers should differentiate retriable versus non-retriable errors.
HardTechnical
0 practiced
Your API gateway returns intermittent 503 errors only under moderate load. Backend instances pass health checks and show low CPU. As a Solutions Architect, outline a step-by-step diagnostic plan to determine if the problem is LB connection pool exhaustion, ephemeral port exhaustion (SNAT/TCP TIME_WAIT), DNS TTL/config issues, or application thread exhaustion. Include commands, metrics, logs and experiments to run.
HardSystem Design
0 practiced
Design a globally consistent distributed rate limiter to enforce per-customer quotas across hundreds of load balancer nodes with low latency. Compare centralized counter (e.g., Redis) vs distributed token leases vs probabilistic sketches, and discuss correctness under partitions, performance and latency trade-offs.
EasyTechnical
0 practiced
Compare common traffic distribution algorithms used by load balancers: round robin, least connections, weighted balancing, and consistent hashing. For each algorithm explain behavior under variable request latencies, long-lived connections (e.g., WebSockets), and heterogeneous server capacities. Provide practical guidance on when to pick each algorithm for production services.
MediumTechnical
0 practiced
Design load balancing and routing controls to satisfy data residency and privacy requirements (e.g., GDPR). Ensure that user traffic and logs remain within specified jurisdictions while still providing cross-region failover. Discuss DNS, geo-routing, logging redaction/retention and operational processes required.

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