Round-Robin Load Balancing
Asked of: Software Engineer
Last updated

What's being tested
These problems test stateful request selection: implementing a correct, health-aware round-robin router while servers are added, removed, or marked unhealthy. Interviewers probe index invariants, concurrency safety, fault handling, and whether you can compare simple rotation with consistent hashing when request affinity matters.
Patterns & templates
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Round-robin pointer — keep
nextIndex; chooseservers[nextIndex % n], then increment;O(1)selection,O(n)storage. -
Health-aware scan — skip unhealthy nodes with at most
nprobes; return explicit error when no backend is available. -
Dynamic membership invariant — after
addServerorremoveServer, normalizenextIndex %= len(servers)to avoid out-of-bounds and skew. -
Concurrent router state — protect
nextIndexandserverswithMutex/RWMutex, or use atomic index plus immutable server snapshots. -
Retry vs reroute — retry transient failures with bounded attempts/backoff; avoid infinite loops when every backend fails.
-
Consistent hashing template — hash each request key and server virtual node; lookup via sorted ring in
O(log V), whereV = servers * replicas. -
Testing matrix — cover empty pool, one server, unhealthy servers, removal before current index, wraparound, concurrent calls, and distribution sanity.
Common pitfalls
Pitfall: Incrementing
nextIndexbefore validating availability can skip servers or produce uneven routing after failures.
Pitfall: Removing a server without adjusting the pointer causes out-of-bounds errors or repeated routing to the wrong backend.
Pitfall: Claiming round-robin preserves request affinity; use consistent hashing when the same customer/order/session should usually hit the same backend.
Practice these
The practice cards below cover the canonical variants — solve all of them and time yourself.
Featured in interview prep guides
Practice questions
- Build Resilient Aggregation and Debug RoutingDoorDash · Software Engineer · Onsite · medium
- Compute courier pay and implement load balancingDoorDash · Software Engineer · Onsite · medium
- Implement and compare round-robin and consistent hashingDoorDash · Software Engineer · Onsite · Medium
- Implement round-robin load balancerDoorDash · Software Engineer · Onsite · Medium
- Debug round-robin request routerDoorDash · Software Engineer · Technical Screen · medium
- Debug round-robin, DashMap, and simple cacheDoorDash · Software Engineer · Technical Screen · Medium
Related concepts
- Load Balancing And Resource Lifecycle SimulationCoding & Algorithms
- Consistent HashingCoding & Algorithms
- Greedy, Heaps, And Scheduling OptimizationCoding & Algorithms
- Robust Networking, REST, And Concurrency ControlSystem Design
- Distributed Job Scheduler SystemsSystem Design
- Leaderboards And Real-Time RankingSystem Design