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Load Balancing and Horizontal Scaling Questions

Covers principles and mechanisms for distributing traffic and scaling services horizontally. Includes load balancing algorithms such as round robin, least connections, and consistent hashing; health checks, connection draining, and sticky sessions; and session management strategies for stateless and stateful services. Explains when to scale horizontally versus vertically, capacity planning, and trade offs of each approach. Also includes infrastructure level autoscaling concepts such as auto scaling groups, launch templates, target tracking and step scaling policies, and how load balancers and autoscaling interact to absorb traffic spikes. Reviews different load balancer types and selection criteria, integration with service discovery, and operational concerns for maintaining availability and performance at scale.

HardSystem Design
63 practiced
Design autoscaling and load balancing strategies for stateful data stores such as Redis clusters or PostgreSQL replicas. Cover how to scale reads vs writes, proxy vs DNS-based routing to primaries and replicas, handling failovers, scaling down safely, and coordinating LB and autoscaler changes to avoid split-brain or data loss.
MediumSystem Design
65 practiced
Design a scalable load-balancing architecture for a Kubernetes-hosted microservices application expected to handle 20,000 requests/sec. Specify ingress controller choices (NGINX, HAProxy, cloud-managed ingress), service mesh considerations, HPA settings, node pool sizing, external LB configuration (timeouts, connection draining, TLS termination), and how to support sticky sessions and WebSocket traffic within this cluster.
MediumTechnical
54 practiced
Given a caching layer (memcached or Redis) served to application instances through a load balancer, propose a horizontal scaling strategy to maintain low latency under growing traffic. Discuss consistent hashing vs proxy-based sharding, replication for high availability, cache warm-up strategies, rebalancing procedures when nodes change, and implications for client libraries.
MediumSystem Design
53 practiced
Design an autoscaling and load balancing strategy for an e-commerce checkout service that must tolerate flash sale spikes up to 10x baseline for short bursts (around 10 minutes) while keeping p99 latency <200ms and minimizing cost. Discuss choosing between target-tracking and step policies, pre-warming/warm-pools, predictive scaling, use of serverless or queueing to absorb bursts, and LB settings like connection draining and health-check grace periods.
HardTechnical
62 practiced
You are tasked with reducing cloud costs for a load-balanced fleet that is overprovisioned during off-peak hours. Draft a step-by-step operational plan that includes analyzing usage metrics, right-sizing instances, modifying autoscaling thresholds and schedules, leveraging spot/preemptible instances, implementing scheduled scaling for off-peak, and safely testing changes. List risks and rollback strategies.

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