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Real-Time Predictions at DoorDash
Raghav Ramesh presents DoorDash’s thoughts on how to structure machine learning systems in production to enable robust and wide-scale deployment of machine learning, and shares best practices in designing engineering tooling around machine learning.
By DoorDash engineers · DoorDash · Added 2026-10-12
All content belongs to DoorDash engineers / DoorDash. We only link to it and give credit. Report a problem
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About 37 min left. Your work is saved as you go.
What you are about to study
DoorDash explains a real system. You should know the basics: caching, queues and replication.
Ideas you will meet
- WebSockets
- Persistent bidirectional connections for real-time features.
- Distributed Systems
- Consensus, time, failure and the fundamentals of scale-out.
- Machine Learning Systems
- Recommendations, ranking, feature stores and serving models at scale.
What we already know about this
Our own lessons on these ideas. Read them here before you start, so it makes sense.
Core Concepts: How Things Actually Work · 7 minPolling, long polling, SSE and WebSocketsFour ways to get live updates to a browser, and how to choose between them.Read here
The problem
HTTP is request and response: the client asks. How does the server tell a browser something now?
The four options
Technique How Good Weak Short polling Client asks every N seconds Trivial, works everywhere Wasteful, delayed by N Long polling Client asks; the server holds the request until there is news (or a timeout), then the client asks again Near real time, plain HTTP A held request per client, awkward at scale Server-sent events (SSE) One long HTTP response streams events Simple, auto-reconnect, text over HTTP One-way only WebSockets HTTP upgrades to a two-way connection Low latency both ways Stateful connections, more infrastructure 100%Figure SDA-CORE-08-1 · The four options · © forcsguy.com
Before: polling: keep asking
100%After: WebSocket: server pushes
100%What changed
- No wasted requests when nothing has changed
- Updates arrive the moment they happen
- The server must hold many open connections
Choosing
- Updates are rare or delays are fine: polling.
- The server pushes, the client mostly listens (feeds, scores, notifications, progress): SSE.
- Both sides send often (chat, games, collaborative editing): WebSockets.
Running persistent connections
Connections are long-lived, so capacity is about how many connections a server can hold, not requests per second.
- Put connection handling in servers that are separate from your stateless API.
- Use heartbeats to detect dead connections, and reconnect with backoff and jitter.
- Track which server holds which user so messages can be routed (a presence or session store), and use a pub/sub system between servers.
- When a client reconnects, let it ask for what it missed (events after id X), because connections drop.
- Authenticate on connect and again when tokens expire.
More on this site
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Concurrent and Distributed Systems (Cambridge lecture notes)
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