Inside Uber’s Tech: The Backbone of Rides and Eats! | Uber Tech Stack Explained скачать в хорошем качестве

Inside Uber’s Tech: The Backbone of Rides and Eats! | Uber Tech Stack Explained

🎬 Ever wondered how Uber powers millions of rides and deliveries every day? In this video, we break down the Uber tech stack and explore the technology behind one of the world’s leading ride-hailing and food delivery platforms. 🚀 We’ll cover: Uber’s global cloud infrastructure powered by AWS and Google Cloud. The tech behind Uber’s mobile apps, using Swift for iOS and Kotlin for Android. How Uber’s web platform utilizes React, HTML5, and JavaScript for smooth user experiences. Uber’s microservices architecture and the use of gRPC for efficient communication. Real-time capabilities enabled by Kafka, Apache Flink, and WebSocket. Data storage and management with Cassandra, MySQL, and DynamoDB. Uber Eats tech stack, optimizing delivery routes and real-time order updates using AI and machine learning. Predictive analytics and geospatial data processing to forecast demand and traffic patterns. DevOps tools like Kubernetes, Jenkins, and Spinnaker for streamlined workflows. 🔍 Learn how Uber optimizes its tech stack for scalability, real-time decision-making, and seamless user experiences. Whether you’re curious about Uber Eats’ predictive algorithms or want to understand how Uber handles millions of concurrent rides, this video has all the answers! 📺 Don’t forget to subscribe for more tech breakdowns and hit the notification bell to stay updated on the latest videos. #UberTechStack #HowUberWorks #UberBackend #UberEatsTechnology #UberCloudInfrastructure #MicroservicesUber #KafkaUber #FlinkUber #PredictiveAnalyticsUber #AIUber #GeospatialDataUber #ReactUber #SwiftUber #KotlinUber #CassandraUber #MySQLUber #AWSUber #GoogleCloudUber #UberEatsTech #UberBigData #MachineLearningUber #RealTimeUber #UberDevOps #UberArchitecture #UberDataScience #UberMobileApps #RideHailingTech #FoodDeliveryTech #UberEatsBackend #UberEatsOptimization #UberInnovation #UberML #UberDataPipeline #UberEngineering #ScalableTechUber #UberAPIIntegration PRAKRITI KUMAR