Twitter (now X) operates one of the most sophisticated distributed systems in the world. As of 2026, its architecture has shifted toward a heavy focus on AI-driven ranking (via xAI’s Grok), real-time event streaming, and a highly optimized microservices model.
Below is the breakdown of the project structure and technologies powering the platform.
The frontend is designed to be a Progressive Web App (PWA), meaning the web experience is built to feel like a native app with high responsiveness.
Web Framework: React.js with TypeScript. It utilizes React Server Components (RSC) to reduce client-side bundle sizes.
State Management: Traditionally Redux, though they have moved toward more localized state and React Query for server-state synchronization.
Styling: A custom utility-first CSS framework (similar to Tailwind) and the Chirp font for brand identity.
Mobile (iOS): Swift with a heavy reliance on dynamic frameworks and Swift Package Manager (SPM).
Mobile (Android): Kotlin using Jetpack Compose for modern, declarative UI.
Package Managers: * Yarn/npm for the web.
Swift Package Manager (SPM) (migrated from CocoaPods).
Gradle for Android.
X transitioned away from its original Monolithic Ruby on Rails architecture years ago to a JVM-based microservices architecture.
Primary Languages: Scala (core services) and Java.
Performance Framework: Finagle. This is an extensible RPC system for the JVM used to build high-concurrency servers.
API Layer: GraphQL and Apache Thrift. Thrift is used for efficient cross-language communication between services.
Real-time Processing: Apache Storm and Apache Heron handle the massive influx of tweets (event streams) in real-time.
Orchestration: Kubernetes (migrated from Apache Mesos/Aurora) for managing containers across massive data centers.
Handling 500 million+ tweets a day requires a multi-tiered storage strategy.
| Layer | Technology | Use Case |
| Distributed DB | Manhattan | A proprietary distributed key-value store (Twitter-built) for core tweet data. |
| Relational DB | MySQL | Used in massive clusters for user data and metadata. |
| NoSQL | Cassandra | High-availability storage for timelines and certain activity logs. |
| Caching | Redis & Pelikan | Pelikan Cache is a custom Twitter framework designed to handle petabytes of cached data. |
| Search | Earlybird | A real-time search engine based on Apache Lucene. |
In 2026, the "secret sauce" is the open-source recommendation algorithm.
Machine Learning: Python is the dominant language here, using PyTorch and TensorFlow.
Algorithm Pipeline:
Candidate Sourcing: Uses SimClusters (community-based clustering) to find relevant tweets.
Ranking: A heavy-duty Neural Network scores ~1,500 candidates in milliseconds.
Filtering: Applies "Heuristics" (e.g., filtering out blocked users or "not interested" content).
AI Integration: Grok AI (powered by xAI) is integrated into the backend to summarize trends and enhance search intent.
Observability: Grafana, Prometheus, and Zipkin for distributed tracing.
Cloud Providers: A hybrid-cloud approach using AWS and Google Cloud (GCP) alongside private data centers.
CI/CD: Bazel (monorepo build tool) and GitHub Actions.
Security: Hystrix for fault tolerance and custom rate-limiting services to prevent scraping/DDoS.
To Be Continued...
- Frontend: React, JavaScript, and HTML5
- Backend: PHP, Java, and Python
- Database: MySQL, Memcached, and Cassandra
- Package Manager: npm (Node.js)
- Frameworks: React, GraphQL, and Thrift
- Tools: Jenkins, Git, and Docker
To wrap up our deep dive, let's look at the Real-Time Direct Messaging (DM) system. This is a massive engineering feat because it must feel instantaneous while being battery-efficient on mobile.
💬 The DM Architecture: MQTT vs. WebSockets
Most web apps use WebSockets for real-time chat. However, Instagram (and Facebook Messenger) uses MQTT (Message Queuing Telemetry Transport).
Why MQTT?
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Battery Efficiency: WebSockets require frequent "keep-alive" pings to stay open, which can drain a phone's battery by keeping the radio active. MQTT is much "quieter" and can stay connected with far fewer pings.
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Low Bandwidth: MQTT headers are tiny (as small as 2 bytes), making it perfect for users on unstable 3G or 4G networks.
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The "Iris" Sync System: Instagram uses a system called Iris. Instead of sending a full message object every time, Iris treats the chat history as a sequence of deltas. Your phone simply tells the server, "I have up to sequence #1005," and the server sends only the new changes (sequence #1006 and #1007).
🏗️ The Direct Message Flow
When you send a "Hi" to a friend:
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Publish: Your app publishes a message to a Topic (e.g., ig/messages/user_B_id).
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The Broker: An MQTT Broker (likely a highly customized version of Mosquitto or a proprietary Meta service) receives the message.
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Persistence: The message is simultaneously written to a high-speed Key-Value Store (like Cassandra or RocksDB) so it can be retrieved if the recipient is offline.
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Push:
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If User B is Online: The Broker pushes the message directly to their active MQTT connection.
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If User B is Offline: The system triggers the Notification Service (using Firebase Cloud Messaging for Android or APNs for iOS) to wake up their phone.
🛡️ Real-Time Presence & "Seen" Receipts
Managing the "Online" green dot for billions of users is a "write-heavy" nightmare.
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Presence Service: This is often written in Go or C++ for raw speed. It keeps the "last active" timestamp in a massive Redis cluster.
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Fan-out: When you go online, Instagram doesn't tell everyone. It only "fans out" your status to your closest friends and people you are actively chatting with to save resources.
🎨 Final Summary of the "Instagram Stack"
If you were to build a "Mini-Insta" today, this is the stack you'd mirror:
Layer
Technology
Language
Python (Django) & Go
Real-time
MQTT (for DMs & notifications)
Primary DB
PostgreSQL (sharded by User ID)
Feed/Cache
Redis & Memcached
Storage
AWS S3 / Google Cloud Storage
Search
Elasticsearch or Vector DBs (for AI recs)
This architecture is what allows Instagram to remain stable even when a celebrity like Cristiano Ronaldo posts to 600+ million followers simultaneously.