Scaling Disaster Recovery: Achieving Cost-Effective and Efficient Solutions for a Gaming Company


A gaming company, with over 200 users worldwide, had their on-premise mobile solutions running in their primary Data Center in Oregon. Their basic disaster recovery approach involved failing over to a secondary Data Center in Las Vegas in the event of application downtime. However, this approach had several limitations:

  • Procuring and provisioning new infrastructure was time-consuming, impacting their time to market.
  • Recovery Time Objective (RTO) and Recovery Point Objective (RPO) were higher, resulting in longer application downtime.
  • Resource overheads to manage the resources in primary and secondary data centers were higher.


The task was to design and implement a more scalable and efficient disaster recovery solution for the client's mobile applications. Aplima was assigned to provide a comprehensive solution that addressed the limitations of the existing approach.


To tackle the challenges and meet the client's requirements, Aplima took the following actions:

  • Conducted a review of the existing infrastructure and identified the shortcomings of the current disaster recovery approach.
  • Performed a cost analysis of various disaster recovery solutions to determine the most suitable and cost-effective option.
  • Proposed a solution involving running the mobile application on a minimal footprint of Amazon EC2 Instances or AWS infrastructure. In case of a failure, the standby environment would be scaled up for production load, and traffic would be directed to AWS.
  • Used Virtual Private Cloud (VPC) to provision a logically isolated section of the AWS Cloud.
  • Set up OpenVPN and Bastion hosts to allow corporate users to securely access the AWS infrastructure.
  • Created and maintained Amazon Machine Images (AMIs) using t2.small instances for the web and application servers, ensuring efficient deployment and management.
  • Developed CloudFormation templates to automate and streamline the scaling of the infrastructure to handle production load.
  • Configured an AWS RDS MySQL instance to replicate (mirror) data from the on-premise MySQL server, ensuring data consistency and availability.
  • Deployed Elastic Load Balancers to efficiently distribute traffic to web and application servers, optimizing performance and availability.
  • Leveraged Simple Storage Service (S3) to store CloudFormation templates and logs securely.

In the event of a failover, the following actions were taken:

  • Utilized the highly scalable and available Route 53 service to route end-user requests to the infrastructure running in AWS.
  • Increased the size of the web and application EC2 instances in service with the Elastic Load Balancers to accommodate the production load.
  • Scaled up the RDS MySQL database instance to handle the increased production load and maintain performance.
  • Created read replicas for improved database performance and scalability.
  • Utilized CloudWatch and AutoScaling to monitor the system and dynamically adjust resources to accommodate the increased load and ensure optimal performance.

Aplima provided a comprehensive solution, including a detailed cost analysis, pre-configured AMIs, CloudFormation templates, database mirroring to RDS, failover capability, monitoring using CloudWatch, automated scaling with AutoScaling.


The implementation of the warm standby disaster recovery solution in AWS achieved the following business results:

  • Cost-effective DR solution: The proposed solution reduced costs by 55% compared to a traditional disaster recovery approach.
  • Scalable DR infrastructure: The solution provided the scalability required by the client, enabling efficient handling of production load during failover events.
  • Failover capability: The system successfully handled failover events, ensuring minimal disruption and maintaining service availability.
  • Minimal downtime: The solution met the client's Recovery Time Objective (RTO) and Recovery Point Objective (RPO), minimizing application downtime and data loss.

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