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Transforming Home Fitness
Peloton was founded in 2012 by a team of five people, and launched on Kickstarter in 2013. The company was born on AWS and delivered its first bike in 2014. In seven years, Peloton has grown to more than 1.4 million members who collectively have ridden hundreds of million of virtual miles.
Powering Communities at Scale
Peloton uses AWS to power the leaderboard in its live-streamed and on-demand fitness classes, and it requires high elasticity, low latency, and real-time processing to deliver customizable rider data for the community of more than 1.4 million members riding together from their homes.
Launching New Features to Serve Members Better
Using AWS, Peloton can quickly test and launch new features to improve the unique experience of home-based community fitness.
Growing Demand for Speed and Scale
When Zillow created its home-valuation tool—Zestimate—nearly 15 years ago, it had to develop an on-premises machine learning framework to process an array of data. But, as its popularity and complexity grew, Zillow needed a better way to deliver Zestimates on nearly 100 million homes across the country.
Faster, More Dynamic Home Valuations
Zillow moved its Zestimate framework to AWS, giving it the speed and scale to deliver home valuations in near-real time. The more dynamic valuations better reflect both the unique features of each home and what’s happening in the local housing market, so customers have the latest data as they explore the buying or selling process.
Reaching Customers at the Market’s Pace
In hot housing markets, homes can go from listing to offer in just days. Zillow built AWS technologies into its infrastructure to quickly and reliably deliver hundreds of millions of emails each month, keeping customers apprised of the latest listings, home statuses, and more.
A Mission to Improve Lives
*510(k) pending at US FDA. Not available for sales in the United States.
Better Care Using Machine Learning
GE Healthcare uses AWS and Amazon SageMaker to ingest data, store data compliantly, orchestrate curation work across teams, and build machine-learning algorithms.
Better, Faster Models
GE Healthcare reduced the time to train its machine-learning models from days to hours, allowing it to deploy models more quickly and continually improve patient care.
Epic Games Uses AWS to Power Worldwide Game Fortnite
Learn how Epic Games uses AWS to deliver Fortnite to more than 200 million players around the world.
Building a Foundation on the Cloud
Epic Games has been using AWS since 2012 and is now all in on the AWS Cloud, running its worldwide game-server fleet, backend platform systems, databases, websites, analytics pipeline, and processing systems on AWS.
An Overnight Sensation
In 2017, Epic Games launched Fortnite, a cross-platform, multiplayer game that became an overnight sensation. In its first year, Fortnite’s user base grew by more than 100 times to 200 million players worldwide.
Pushing the Boundaries of Scale
AWS is integral to the success of Fortnite. Using AWS, Epic Games hosts in-game events with hundreds of millions of invited users without worrying about capacity, ingests 125 million events per minute into its analytics pipeline, and handles data-warehouse growth of more than 5 PB per month.
Providing the Best Gaming Experience
Using AWS, Epic Games is always improving the experience of its players and offering new, exciting games and game elements. The company plans to expand its use of AWS services in the future, including machine learning and containerized services.
Real-Time Container Tracking
Matson built a flagship mobile application for global container tracking that allows customers to perform real-time tracking of their freight shipments. Other valuable features in the application include interactive vessel schedule searching, location-based port map lookups, and live gate-camera feeds.
Mobile Device Access
All mobile devices access AWS via Amazon API Gateway. This provides highly available edge located endpoints for access into resources within Matson's existing virtual private clouds.
The AWS Lambda functions are designed using the microservices pattern and are modeled around specific ocean-based business contexts, such as shipment tracking and vessel schedules.
Database Configuration and Storage
Amazon DynamoDB manages configuration as well as user-feedback configuration and user-feedback notifications sent from mobile devices. DynamoDB Streams provides real-time notifications to Matson's customer service team.
Data Monitoring and Alerts
End-to-End Serverless Application
Matson can now offer customers an end-to-end serverless application to help track their shipments, and has no infrastructure to maintain.
BP Improves Effectiveness and Gains Cost Agility and Speed for Its Critical Business AppsLearn More
Managing Critical Business Apps
BP's IT organization manages SAP applications used by thousands of employees worldwide for supply chain, procurement, finance, and more.
Improving Speed & Cost Agility
To improve speed and gain cost agility, BP used Amazon EC2 to migrate these core business apps to the cloud. In addition, the team built EC2 X1 instances to increase scale and to power their real-time analytics.
The team can now stand up systems on demand in hours instead of weeks or months. BP is seeing performance increases across the board, including a 40 percent speed improvement for the Lubricants ERP system.
Live Nation Entertainment Innovates Faster, Reduces Costs, and Improves Application Availability Using AWSLearn More
Seeking a Better Customer Experience
Live Nation is the global leader in live entertainment that produces concerts, sells tickets, and connects brands to music. In 2016 Live Nation announced it was moving its global IT infrastructure to AWS in an effort to deliver better experiences to its customers.
An Easy Migration
The company moved 118 applications and 668 servers to AWS within 17 months without adding headcount or budget.
By moving to AWS, Live Nation has moved from troubleshooting hardware to delivering on innovative ideas that serve its customers better. Since implementation, Live Nation realized a 58-percent reduction in total cost of ownership, supported 10 times as many projects with the same staff, and saw a 99-percent improvement in application availability.