How does WhatsApp deliver 100 billion messages per day?

Persistent connections held by Erlang-based gateways, a sharded session store for instant recipient lookup, and an offline message queue per user. Erlang's lightweight processes let one server hold a million connections, which keeps the fleet small.

How does end-to-end encryption work?

The Signal Protocol generates per-message symmetric keys from a long-lived identity key and rotating pre-keys. The server only sees ciphertext. For groups, the sender encrypts per recipient (with sender-key rotation as an optimization).

Why use Erlang for the chat gateway?

Erlang's BEAM VM schedules millions of lightweight processes on one node, which is exactly what a persistent-connection workload needs. The same load on Java or Node.js would need 5 to 10x the servers.

What happens when both sender and recipient are offline?

The sender writes to the offline queue for the recipient, sharded by recipient user_id. When the recipient reconnects, their connection server drains the queue in order. Messages are deleted after the client acknowledges receipt.

How does WhatsApp handle group messages of 1024 members?

The message router pulls the cached group member list and dispatches one ciphertext per online member. Encryption uses sender keys with rotation so the sender does not pay a 1024x encryption cost per message.

System design interview guide

Design WhatsApp: System Design Interview Guide

in this guide

Design WhatsApp, part by part

7 parts open to everyone · 3 with a free account · 3 with the course

You can read 7 of 13 parts. A free account opens the deep dive; the course opens all of it.

Requirementsopen
Scale estimatesopen

Why this question is asked

Design WhatsApp tests whether you understand persistent connections (WebSocket or XMPP), message durability, the difference between presence and message delivery, fan-out to groups, and how end-to-end encryption changes server responsibilities. Bonus points if you can talk about why WhatsApp can run on 50 engineers when Facebook Messenger runs on hundreds.

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The course goes deeper on the WhatsApp design

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The System Design course covers the WhatsApp design across a run of lessons, not one page. These 4 alone are about 91 minutes of step-by-step reading, every one with a quiz.

Requirements

Always clarify these in the first 5 minutes of the interview. Do not start drawing boxes until both lists are agreed.

Functional requirements

Users send and receive 1:1 messages in real time
Group chats up to 1024 members with the same delivery guarantees
Delivery receipts: sent, delivered, read
Presence and typing indicators

Go deeper

This guide is built on these 5 lessons. Each one teaches one piece of the WhatsApp design above, step by step.

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WhatsApp delivers 100+ billion messages per day across 2+ billion users, with end-to-end encryption and 99.99% delivery success.

Designing WhatsApp forces you to combine real-time bidirectional messaging, durable offline delivery, end-to-end encryption, presence and typing indicators, and group fan-out. It is the canonical chat system design problem and a favorite at FAANG.

Roni Das

11 June 2026 · Updated 17 October 2026 · 11 min read

Where it shows up

Commonly asked at Meta (which owns WhatsApp), Google, Amazon, Slack, Discord, Snap, and Microsoft Teams. It is the standard real-time messaging interview question.

Spec sheetWhatsApp

01Total users: 2B
02Messages per day: 100B
03Messages per second (peak): 5M
04Concurrent persistent connections: 500M

worked through below, with the maths

Data modelfree account

Deep dives (6)free account

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The hard parts of this design are taught step by step in the System Design course: WebSockets, Push Notifications and Message Queues.

WebSockets

Full-duplex, persistent connections, how the real-time web actually works.

22 min · diagrams · quiz

Push Notifications

Deliver messages to users even when they're not actively using your app.

14 min · diagrams · quiz

Message Queues

Decouple producers from consumers with a buffer that holds messages until they're processed.

20 min · diagrams · quiz

Database Sharding

Splitting a database across multiple servers, the nuclear option for scaling writes, and the architecture behind Instagram, Uber, and YouTube.

35 min · diagrams · quiz

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Live from the course bench

Before you design WhatsApp, try the questions it rests on.

Real interview questions, live diagrams and measured lab results, pulled at random from the lessons. A new set every time you come back.

Two engineers sketching a system design on a whiteboard

where the work happens

Stuck on a card?

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Laying out the cards…

Media messages (image, video, audio, document) up to 100 MB

Voice and video calls (out of scope for this writeup but worth mentioning)

Offline message queuing with delivery on reconnect

End-to-end encryption for all message content

Non-functional requirements

Message delivery latency under 500 ms at the 99th percentile when both parties online
99.99% delivery success including offline queueing
Server cannot read message content (E2E encryption)
Scale to 2B users with sub-second connection setup
Mobile-first, must work on flaky networks
Battery efficient on mobile clients

Back-of-envelope scale estimates

Show your math. Pulling numbers from thin air signals you have not thought about the load.

Total users

WhatsApp public reporting. Assume 60% daily active.

Messages per day

100B

100B+ messages per day is a publicly cited figure. That averages to roughly 80 messages per DAU.

Messages per second (peak)

100B a day averages about 1.16M a second. A 4x peak factor for busy evenings gives about 4.6M, rounded to 5M. That is an everyday peak only: planned events such as a World Cup final or New Year's Eve run several times higher (see Event peaks under the deep dives).

Concurrent persistent connections

500M

Roughly 40% of DAU online at peak. Each holds a WebSocket or XMPP-style connection.

Storage per message

200 bytes

Plus media stored separately. 100B messages per day equals roughly 7 PB per year of message metadata. Media is much larger but stored in object storage with TTL.

High-level architecture

Clients hold a persistent connection (originally XMPP, now a proprietary protocol) to a fleet of Connection Servers. When a client sends a message, the connection server hands it to a Message Router. The router looks up the recipient's connection (in a sharded session store keyed by user_id), and if the recipient is online, it pushes the message over their connection. If offline, the message is queued in an Offline Message Store (sharded by user_id) and delivered on reconnect. End-to-end encryption (Signal Protocol) is handled client-side: the server only sees ciphertext blobs. Media (images, videos) is uploaded to a Media Service that returns a URL; the URL is encrypted and embedded in the message. Group chats use the same router with a fan-out step: the router looks up group members and pushes a copy to each online member. Push notifications (APNs, FCM) are used to wake the recipient app when offline.

In a real interview, sketch this on the whiteboard before diving into any single box.

Core components

Walk through each service. The interviewer wants to hear what each one owns, not just the names.

Connection Server (Chat Gateway)

Holds millions of persistent connections per node. Originally Ejabberd (XMPP), rewritten in Erlang for high concurrency. Routes incoming messages to the Message Router and pushes outgoing messages to the client.

Session Store

A sharded KV store mapping user_id to the connection server holding that user's active connection. Reads and writes on every message. Backed by Redis or a custom in-memory store.

Message Router

Receives the ciphertext blob, looks up the recipient in the session store, and either pushes over the live connection or stores in the offline queue. For groups, fans out to all members.

Offline Message Store

Sharded by user_id. Stores messages for users not currently connected. On reconnect, the connection server drains the queue and pushes everything in order. Messages are deleted from the server after delivery (WhatsApp is store-and-forward, not durable archive).

Media Service

Handles uploads and downloads of images, videos, voice notes, and documents. Media is encrypted client-side with a per-message symmetric key (the key is encrypted in the E2E payload). Media is stored in object storage with a 30-day TTL.

Presence Service

Tracks online/offline/typing/last-seen state. Updates flow over the same persistent connection but are rate-limited. Presence is eventually consistent; a 1-2 second lag is acceptable.

Push Notification Gateway

When a message is queued for an offline user, fires a wake-up notification via APNs (iOS) or FCM (Android). The notification does not contain message content (it cannot, given E2E encryption).

the deep dive

Data model

users. Sharded by user_id hash. Device keys are public keys used for the Signal Protocol.

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Every table for WhatsApp, its keys, and which store fits it and why.

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the deep dive

Deep dives

Persistent connections at 500M concurrent. A single connection server in WhatsApp's published architecture holds 1 to 2 million persistent connections. With 500M concurrent users, that is 250 to 500 servers just…

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6 deep dives on the parts that break at scale, with 1 diagrams: Persistent connections at 500M concurrent; Message routing and offline queueing; End-to-end encryption and the server's role.

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the deep dive

Trade-offs to discuss

Erlang vs Go or Java for the gateway. Erlang's lightweight processes win at millions of concurrent connections per node. Go and Java need 5 to 10x the hardware for the same load. The trade-off is hiring: the…

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5 decisions an interviewer expects you to defend, each with the alternative and why it loses here.

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for course owners

What the interviewer asks next

A connection server holding a million live connections crashes. What happens to those users and their messages?

with the System Design course

4 follow-up questions with model answers, the interview scorecard for this question, and a mock interview on Design WhatsApp with the AI tutor.

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How WhatsApp actually does it

WhatsApp famously ran on a tiny engineering team (~50 engineers serving 900M users at the time of the Facebook acquisition) by leaning hard on Erlang and a custom version of FreeBSD-tuned servers. The chat protocol is a proprietary binary protocol derived from XMPP. End-to-end encryption uses the Signal Protocol developed by Open Whisper Systems. Media is stored in a custom blob store. The Erlang choice came from WhatsApp's hire of an Ejabberd contributor in the early days.

Sources

Was this helpful?

the question most readers have next

Your friend's phone is switched off. Where does your message wait, and how does it arrive exactly once, in order, when the phone comes back?

If the recipient is not connected, the router writes the message to an offline queue for that user, and a push notification wakes the phone. On reconnect the queue is drained in order, and the server deletes a message only after the recipient's device acknowledges it. Because a resend can happen after a lost acknowledgement, each message carries an ID the phone uses to drop duplicates.

Where this is used in industry

WhatsApp: Rick Reed's Erlang Factory talk described how WhatsApp scaled its chat servers on Erlang and FreeBSD to millions of connections per server.
Rick Reed, Erlang Factory: Scaling WhatsApp
Facebook Messenger: Keeps a totally ordered queue of updates per user. While the phone is offline its pointer stays put and new messages keep being queued.
Engineering at Meta: Building mobile-first infrastructure for Messenger
WhatsApp: Its security whitepaper documents end-to-end encryption with the Signal Protocol, so the servers relay ciphertext they cannot read.
WhatsApp Security Whitepaper

Build it yourself: what you would have to solve

Hundreds of millions of phones hold a connection open at once. You need long-lived, two-way connections that cost very little each.
WebSocketsSystem Design course22 min
A message to an offline user must wait somewhere durable and be delivered in order when they return.
Design a Chat System like WhatsAppSystem Design course

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A sleeping phone has no open connection. Only APNs or FCM can wake it to fetch the waiting messages.

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Design WhatsApp: System Design Interview Guide

Design WhatsApp, part by part

Why this question is asked

The course goes deeper on the WhatsApp design