ARCHITECTING AWS-ENABLED TRAVEL AND LIFESTYLE PORTAL FOR LOYALTY AND REWARD MANAGEMENT COMPANY

THE SOLUTION

We designed a flexible, scalable and cost-effective AWS-enabled portal

AWS was the solution to the challenges faced by the client. It offered a low cost, scalable and highly reliable infrastructure platform that could replace the costly infrastructure which the portal was running on. AWS was selected due to the wide range of services it offers, which aligned with the long-term technology roadmap and business goals of the client.

Mphasis architects and the development team developed Proof of Concept (PoC) with various AWS services to find the best fit for the problem in hand. As part of the application migration, traditional servers were replaced with Amazon Elastic Compute Cloud (Amazon EC2) instances. Coupled with Amazon Route 53, AWS Elastic Load Balancer (ELB) and Amazon EC2 Autoscaling, the solution provided a highly available and scalable platform for the portal. With Amazon EC2 Autoscaling, the client could –

• Perform periodic health checks to ensure the unhealthy instances are replaced with healthy ones
• Follow the demand curve for the portal closely, reducing the need to manually provision Amazon EC2 capacity in advance. This eliminated the need to do complex calculations for predicting the load during a campaign, and for provisioning the infrastructure in advance in anticipation of the load. This also helped in keeping just the required number of instances running at any point of time, resulting in cost optimization and improved experience to members regardless of the traffic

Amazon Relational Database Service (Amazon RDS) was used to power the portal with data persistence, providing cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups.

For storage of static content, Amazon Simple Storage Service (Amazon S3) was used. The highly durable, available and scalable nature of Amazon S3 helped in further improving the performance of the portal without any additional management overheads.

AWS Lambda was used for running batch jobs which needed high compute resources for a short duration. This resulted in cost optimization as the client need to pay for the compute time consumed. AWS Lambda also enables to run code without provisioning or managing servers.

Since analyzing the huge number of logs generated for application monitoring, and taking corrective and preventive actions was a key requirement, Amazon CloudWatch was used with Amazon Elasticsearch Service. As it is a fully managed service, Amazon Elasticsearch provides easy, cost-effective and scalable deployment, security and run.