This was a follow-up to whatever the base design question was.
Start by clarifying requirements and scale, then propose a data model that isolates channel state and message history, and finally discuss trade-offs in storage, consistency, and bot state management. Emphasize extensibility and how you would handle cross-channel concerns like user identity and rate limiting.
Pro tip: Demonstrate awareness of operational concerns by mentioning how you would monitor per-channel metrics and handle channel lifecycle (creation, archival, deletion) without impacting other channels.
Ask about expected number of channels, messages per channel, concurrency, and whether channels are public/private or ephemeral. This shapes storage and consistency choices.
Propose a schema where each channel has its own message history and bot state, using channel_id as a partition key. Consider separate tables/collections per channel or a shared table with channel_id index.
Explain how bot state (e.g., conversation context, variables) is stored per channel, possibly in a key-value store or document DB, and how it's updated atomically with message processing.
Discuss trade-offs between strong vs eventual consistency for message ordering, and how to scale reads/writes via sharding by channel_id. Mention caching strategies for hot channels.
Cover user identity mapping, rate limiting per channel, and how to handle channel creation/deletion without affecting others. Mention monitoring and metrics per channel.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.