AWS Case Study: Xignite
Xignite, a financial services start-up, provides an on-demand platform for delivering reliable financial market data to enterprise applications, portals, and websites for more than 400 corporate clients all over the world, such as Citi, GE Commercial Finance, ING, Marsh & McLennan, kaChing, and Starbucks.
When Forbes.com, the No. 1 business news source in the world, approached Xignite about powering their real-time stock quotes, Xignite knew they needed an infrastructure solution that was equally scalable and cost-efficient. Xignite’s leadership team looked for a solution that effectively and dynamically scaled their delivery of real-time financial information with minimal waste of computing and network resources.
Why Amazon Web Services
They found the cloud computing infrastructure from Amazon Web Services (AWS) to be a natural fit. “It was an obvious decision," says Leo Chan, Xignite CTO. "AWS is a leader in providing redundant computing infrastructure with multiple Availability Zones and a high level of economy of scale in computing and network bandwidth costs."
Currently, Xignite employs Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3) to power a host of on-demand application servers (which increase or decrease according to bell-curve traffic load), a redundant cluster of load-balancers, and cache financial information. As they roll out new services and new clients, they can quickly expand their computing infrastructure on AWS to improve scalability and reduce costs.
Using AWS, Xignite reduced their time-to-market by two months and saved thousands in personnel costs by not needing a full-time operations engineer to procure and install servers at an additional collocation space. “We estimate that the overall cost savings including hardware, infrastructure and network bandwidth, and personnel, is estimated to be in the hundreds of thousands of dollars,” Chan says.
Xignite especially appreciates that AWS provides zero up-front infrastructure costs and has higher efficiency in resource utilization. “Capacity is added during peak times and reduced off-peak, and there is no need for standby capacity for redundancy," Chan says. "It is highly cost-prohibitive to achieve this with fixed capacity and traditional computing models.” Before moving to AWS, Xignite deployed their services on server clusters at a premium collocation facility with higher fixed costs with underutilized capacity.
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