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Innovation

​Qantas.com heads for the cloud

Qantas has begun deploying parts of Qantas.com into the cloud to help improve real-time business processing capabilities.
Written by Aimee Chanthadavong, Contributor

Qantas has announced that it is in the process of moving its website, Qantas.com, into Amazon Web Services' (AWS) cloud platform as part of the company's next phase of shifting workloads into the cloud.

Speaking at the AWS Summit in Sydney on Wednesday, Qantas chief technology officer Chris Taylor said he is "absolutely confident" that once the full deployment is completed, the site would not fail.

According to Taylor, the company has already deployed its first microservices into the cloud.

"We've gone from no test automation to almost 90 percent test automation: Regression testing, performance regression testing, functional, security," he said.

Additionally, the deployment will mean access to real-time information.

"For me, as an IT manager, the line of site of governance that I get in real time with that platform is transformational," Taylor said.

The move comes off the back of Qantas' overall strategy to simplify its business operations, and has since moved some of its other operations to the cloud.

"Cloud computing was transformational for us. We recognised it was completely different and enabled us to rethink everything we do," Taylor said.

"For Qantas, it's a platform for innovation, meaning testing, learning, trialling, and finding out if it works or doesn't work, and be able to industrialise what does work."

Among the outcomes the company has seen as a result of leveraging AWS' cloud is the ability to accelerate compute time from four months to four hours to figure out optimum flight routes. Taylor said the algorithms were able to calculate up to 15,000 different routes when the company was looking to increase flight frequency to North America.

The company has also managed to speed up booking processing times from batch to batch to real-time. As a result that has increased data processing time by 100 times, and reduced the amount of code required to do the same workload by 90 percent, and the cost to run the service by 80 percent.

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