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Early Cloud Adopters Bridge the Data and Security Gap in Travel

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Early Cloud Adopters Bridge the Data and Security Gap in Travel


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Doesn’t matter if you’ve finished ticking off your travel bucket list, chances are you’re already well familiar with Expedia and Airbnb, which have become huge success stories both within and outside of the travel industry. As one of the first online travel agencies and property marketplaces respectively, Expedia and Airbnb have no doubt blazed the trail by adopting AI and cloud computing relatively early in their business. With Amazon Web Services (AWS) at the back-end, the companies have bridged the gap in data processing and security, successfully standing out from the pack to create exciting new experiences for customers. 

Maximizing Performance to Accommodate Customer Demand

Airbnb in particular, has come a long way since its humble beginnings. What started as two flatmates hosting conference attendees on air mattresses for extra cash, grew into an international peer-to-peer lodging platform that has since welcomed over 1.5 billion guests, forever changing how wanderlusts find accommodation. However, faced with service administration challenges in 2009, the one-year-old startup was struggling due to high customer demand, thus migrating nearly all of their functions to Amazon Web Services (AWS) for better efficiency. The entire database migration was done within just 15 minutes, meaning that users did not have to experience prolonged downtime, and Airbnb now uses Amazon Elastic MapReduce to process plus analyze over 50 Gigabytes of data daily, while housing backups and static files on Amazon Simple Storage Service. To simplify time-consuming administrative tasks, AWS Management Console completes replication, scaling and other difficult procedures associated with databases with a basic API call, enabling maximum performance across the board.

“One of our metrics for success is the reduction of time to deploy within our teams. We use this method to launch applications pretty quickly compared to a traditional deployment. Moreover, reducing the cost of a rollback to zero means we can be fearless with deployments.” Murari Gopalan Technology Director
“One of our metrics for success is the reduction of time to deploy within our teams. We use this method to launch applications pretty quickly compared to a traditional deployment. Moreover, reducing the cost of a rollback to zero means we can be fearless with deployments.” Murari Gopalan Technology Director

Fueling Business Growth with Data Processing Prowess

Expedia had engaged the AWS team in 2010 with a similar goal: improve processing speed and accuracy to keep site abandonment rates at a minimum. By involving AWS in the development of Expedia Suggest Service, the partnership not only solved Expedia’s long-standing latency issue, the introduction of an AI-driven typeahead system also served as a first-of-its-kind surprise to the industry at the time. By going all in switching from traditional data centers to cloud, average network latency dropped from 700 milliseconds to less than 50 milliseconds. Even more importantly, a 230 percent CPU consumption efficiency in data processing was achieved. Streams of data such as clickstream, user interaction, and supply data have since been stored on Amazon Simple Storage Service then processed through Amazon Elastic Map Reduce. It may not come as a shock, but Expedia Group processes approximately 240 requests per second, and this high volume that is dreamt about by every business leader requires efficient yet reliable support.



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