Distributed systems questions are where senior interviews get serious. Interviewers want to see that you understand the fundamental impossibility results, the real-world trade-offs between consistency and availability, and how production systems actually handle failures like network partitions and node crashes.
These 14 questions cover the distributed systems concepts that come up repeatedly in senior-level interviews: consensus protocols, leader election, vector clocks, eventual consistency, and the practical differences between CP and AP system designs. Each question rewards depth over breadth.
Consistent hashing is a distributed hashing technique designed to minimize the number of keys that must be remapped when the number of nodes changes.
Read full answer →Rate limiting is a traffic control mechanism that restricts how many requests a client can make within a time window.
Read full answer →A Content Delivery Network (CDN) is a geographically distributed network of servers (edge nodes or PoPs—Points of Presence) that cache and serve content closer to end users than a single origin server can.
Read full answer →L4 and L7 load balancers operate at different layers of the OSI model and serve different purposes.
Read full answer →Distributed transactions arise when a single business operation must update data across multiple services or database nodes atomically.
Read full answer →Exactly-once delivery means a message is processed by the consumer exactly one time — neither lost nor duplicated.
Read full answer →Leader election is the process by which a group of distributed nodes agrees that exactly one node — the leader — is responsible for coordinating writes, holding a lock, or running a singleton process.
Read full answer →Feed fanout is the mechanism by which a post from one user is delivered to the feeds of all their followers.
Read full answer →RPO and RTO are the two fundamental metrics that define a system's disaster recovery requirements.
Read full answer →The circuit breaker pattern is a fault-tolerance mechanism that prevents a service from repeatedly calling a dependency that is failing or slow, which would otherwise waste resources, increase latency, and propagate failures upstream.
Read full answer →Load balancing algorithms determine how incoming requests are distributed across a pool of backend servers.
Read full answer →CDNs (Content Delivery Networks) reduce latency by caching content at edge nodes geographically close to users.
Read full answer →A CDN caches origin responses at geographically distributed edge nodes so that subsequent requests are served locally without hitting the origin.
Read full answer →Load balancer failover is the process by which a load balancer detects that a backend instance has become unhealthy and automatically removes it from the pool of eligible targets, redirecting traffic to healthy instances without manual intervention.
Read full answer →Read the papers or watch the talks — Raft (Ongaro), Dynamo (Amazon), Kafka replication (Confluent). Understanding one consensus protocol deeply beats knowing all of them shallowly. When an interviewer asks “how does leader election actually work,” you want to be able to sketch the state transitions from memory, not paraphrase Wikipedia.
Then practice reasoning about CAP-adjacent trade-offs live: “at what point in this system do you sacrifice consistency, and what does the client see when you do?” Senior interviewers test whether you can hold multiple failure modes in your head at once and explain the visible consequences.
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