LinkedIn is one of the most popular professional networking platforms, with over 800 million members worldwide as of 2022. LinkedIn’s mobile app allows users to access many of the same features as the desktop website, such as viewing profiles, connecting with other professionals, applying for jobs, and more.
But what exactly goes into building a complex mobile app like LinkedIn? What programming languages, frameworks, databases, and other technologies power the LinkedIn app on iOS and Android devices? Let’s take a deep dive into the technical stack behind LinkedIn’s mobile apps.
General Architecture
Like most modern mobile apps, LinkedIn’s iOS and Android apps likely follow a client-server architecture. This means that the mobile app itself (the client) handles the user interface and interactions, while linking back to LinkedIn’s servers to fetch data, upload content, and conduct other backend operations.
The LinkedIn mobile apps connect to servers hosted on LinkedIn’s internal infrastructure, as well as various third-party cloud computing services. APIs (application programming interfaces) allow the client apps to communicate with these backend systems.
While the exact architecture is proprietary, we can make educated guesses about the key components powering LinkedIn’s mobile apps based on common patterns and industry best practices.
Frontend Mobile Frameworks
The LinkedIn iOS app is likely built using Apple’s native development frameworks like UIKit, which provides user interface components and views for iOS apps. For LinkedIn’s Android app, core Android frameworks like the Android SDK and Java/Kotlin are most likely used for the UI and client-side logic.
In addition, LinkedIn may use cross-platform mobile development frameworks like React Native to share business logic across the iOS and Android clients. React Native allows developers to write mobile app code in JavaScript/Typescript that compiles to native UI components on both platforms.
Other potential frameworks/libraries used on the frontend include:
- Redux – for state management
- Apollo – for integrating with GraphQL APIs
- React Navigation – for navigation and routing
Backend Services and APIs
The LinkedIn mobile apps would rely heavily on LinkedIn’s own proprietary backend services and APIs to power core functionality like profiles, feeds, messaging, jobs, and more. These services likely consist of internal microservices, databases, caching layers, search services, recommendation engines, and more.
Some examples of the types of internal APIs and services that LinkedIn’s mobile apps might use include:
- User Profile API – for fetching user data like name, photo, experience, etc.
- News Feed API – for getting streamed updates and feed posts
- Search API – to power searching for jobs, people, groups, etc.
- Messaging API – to send/receive messages between connections
- Notifications API – to get notifications for the user
- Media Storage API – for uploading and downloading images/videos
The mobile apps likely access these APIs over HTTPS using REST or GraphQL patterns. Authentication is handled via OAuth tokens.
Data Stores
With hundreds of millions of users and a massive amount of data, LinkedIn relies on distributed databases and storage engines to power their platform. While the details are not publicly known, we can speculate that LinkedIn likely uses:
- Redis – An in-memory data store used for caching and queuing
- Kafka – A stream processing platform for feed data and activity streams
- Cassandra/DynamoDB – NoSQL distributed databases for storing user data and feed posts
- Hadoop/Spark – For big data processing and analytics
- Elasticsearch – For powering search functionality
- MySQL/Postgres – Relational databases for structured application data
- AWS S3 – Cloud object storage for media assets and files
The mobile app backend would leverage these managed data services to persist and query for the data needed to power the app experience.
Cloud Infrastructure
LinkedIn operates on a complex cloud infrastructure leveraging services and data centers from major providers like Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
Key cloud services that are essential to running LinkedIn’s mobile apps likely include:
- EC2/ECS – For hosting microservices and web application backends
- Lambda – For running serverless functions
- S3 – For storage and serving files/media
- CloudFront/CDN – For fast content delivery
- Cognito – For mobile authentication
- Push notifications – For sending mobile push notifications
The apps would connect to APIs and services hosted across this distributed cloud infrastructure, which provides scalability, reliability, and global reach.
Third-Party Services
In addition to LinkedIn’s own backend services, the mobile apps likely integrate with various third-party platforms via APIs and SDKs for additional functionality like:
- Google Sign-In – For account login/registration
- Facebook SDK – For social sharing capabilities
- Apple Sign-In – For iOS login with Apple ID
- Branch.io – For deep linking and attribution
- Segment – For analytics and tracking
- Crashlytics – For crash reporting
- Google Vision – For image analysis and processing
By leveraging these third-party integrations, LinkedIn can provide a richer experience in their mobile apps without having to build everything in-house.
Continuous Integration and Delivery
Given LinkedIn’s massive engineering organization, they certainly utilize CI/CD pipelines to automate building, testing, and deployment of their mobile apps. Some of the popular tools and services they likely use include:
- Jenkins – An open source automation server for CI/CD pipelines
- Fastlane – Automated mobile release pipelines for deploying iOS/Android apps
- GitHub Actions – Code workflow automation
- App Center – Mobile app DevOps platform by Microsoft
These solutions allow LinkedIn to rapidly develop and release updates to their mobile apps by automating repetitive tasks and providing a consistent, auditable release process.
Design and Prototyping
LinkedIn’s design and product teams likely leverage tools like:
- Figma – Collaborative design and prototyping
- Adobe Creative Cloud – Graphics, iconography, image editing
- InVision – Interactive prototyping and usability testing
- Principle – Animated transitions and microinteractions
These help them mockup and refine the UI/UX of new LinkedIn mobile features before development begins.
Testing and Monitoring
Thorough testing is critical for LinkedIn to maintain quality and stability across their mobile apps. They likely employ various testing techniques like:
- Unit testing – Low-level component tests
- Integration testing – End-to-end API testing
- UI testing – Frontend acceptance and flows
- Performance testing – Stress tests, load tests, etc.
- Beta testing – Real-world testing with a subset of users
In addition, LinkedIn monitors its apps in production using tools like Datadog, New Relic, AppDynamics, and Sentry to detect issues and performance problems in real-time.
Conclusion
LinkedIn leverages a wide array of modern platforms, frameworks, services, and tooling to build, deliver, and refine its mobile apps. Key technologies likely include:
- React Native and native iOS/Android for the frontend
- REST/GraphQL APIs and microservices on the backend
- CI/CD pipelines for continuous delivery
- Distributed data stores like Redis, Kafka, Cassandra, and Elasticsearch to power core functionality
- Major cloud platforms like AWS, Azure, and GCP for the infrastructure
- Third-party SDKs for richer integrations
Of course, the actual technical stack powering LinkedIn’s mobile apps is proprietary and subject to change. But hopefully this gives a realistic overview of some of the technologies likely used based on LinkedIn’s scale, industry best practices, and technological trends.
Building a massive platform like LinkedIn mobile requires world-class engineering talent leveraging cutting-edge languages, frameworks, and infrastructure. With mobile usage dominating today’s social networking landscape, LinkedIn’s technical investments in its mobile apps allows it to reach users wherever they are.