Discord·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate

Jun 2026

Summary

Discord SWE interview where I prepped the wrong thing entirely. The coding round was way more hands-on than I expected, basically pair programming a distributed systems problem from scratch with the interviewer sitting next to you (virtually) the whole time.

Questions Asked (1)

Implement a leader-follower distributed system locally. Nodes should know who the current leader is, support new nodes joining, and handle automatic failover with leader re-election when the leader goes down.

System DesignTechnical Trade-offsAlgorithms & Data Structures

Author's notes

I had spent a solid chunk of prep time on a chat server design I'd seen floating around, so when this came up I had to context-switch pretty fast.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a consensus-based design (e.g., Raft) with a clear leader election and membership change protocol. Walk through the core components—leader election, heartbeats, log replication, and failure detection—and explain how you would implement and test them locally using multiple processes or containers.

Pro tip: Emphasize that you would implement a simplified version first (e.g., using a well-known algorithm like Raft) and then discuss trade-offs and potential improvements, showing you can balance pragmatism with depth.

1. Clarify requirements and constraints

Ask about expected scale, consistency vs. availability trade-offs, and whether the system needs to handle network partitions. Confirm that the implementation is local (e.g., multiple processes on one machine) and discuss any language or tooling preferences.

2. Choose a consensus algorithm

Select a consensus algorithm like Raft or Paxos that handles leader election and membership changes. Explain why Raft is often preferred for its understandability and strong leader model.

3. Design core components

Outline the key components: leader election (using randomized timeouts and RequestVote RPCs), heartbeats (AppendEntries RPCs), failure detection (timeouts), and membership changes (joint consensus or single-server changes). Describe how nodes discover the leader and how new nodes join.

4. Address failover and re-election

Detail the failover process: followers detect leader failure via missed heartbeats, transition to candidate, and initiate election. Discuss how to avoid split votes (randomized timeouts) and ensure safety (majority quorum).

5. Plan implementation and testing

Describe how to implement locally: use multiple processes/threads with inter-process communication (e.g., sockets), simulate network partitions, and test scenarios like leader crash, network delays, and concurrent joins. Mention logging and metrics for observability.

Key Points to Mention

Raft consensus algorithm: leader election, log replication, and safety guarantees
Heartbeat mechanism and failure detection using timeouts
Membership changes: adding/removing nodes safely (e.g., joint consensus)
Handling network partitions and split-brain scenarios
Local implementation details: multiple processes, sockets, and testing with fault injection
Trade-offs: consistency vs. availability, complexity vs. simplicity, and performance overhead

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