Objective: Migrate the legacy on-premises healthcare claims processing system to AWS for scalability, efficiency, and cost-effectiveness.
Phase 1: Assessment and Planning
AWS Migration Hub: Used to track the progress of application migrations. This provided visibility into the status of migrations, improving coordination among multiple teams.
AWS Application Discovery Service: Helped identify dependencies between applications and services. This ensured that no component was overlooked during migration.
Phase 2: Data Migration and Storage
Phase 3: Application Migration and Modernization
Amazon EC2: Hosted the primary claims processing application. Used various instance types optimized for the computational needs of the application.
Amazon ECS with Fargate: Containerized microservices related to claims validation, adjudication, and payment processing. This ensured scalability and efficient resource usage.
AWS Lambda: Built serverless functions for tasks like notifications, data validation, and minor data transformations.
Amazon API Gateway: Managed and exposed APIs for third-party integrations, including integrations with hospitals, clinics, and pharmacy systems.
Phase 4: Data Processing and Analytics
Phase 5: Security and Compliance
AWS IAM (Identity and Access Management):
Amazon VPC with Private Subnets: Isolated the migrated applications and data, ensuring data privacy and security.
AWS Shield and AWS WAF: Protected the claims processing application from external threats and DDoS attacks.
Amazon Macie: Used AI to help spot and rectify any personally identifiable information (PII) that was inadvertently stored, maintaining HIPAA compliance.
Phase 6: Monitoring, Management, and Optimization
Amazon CloudWatch: Monitored the performance of applications and set alerts for anomalies.
AWS Trusted Advisor: Gave recommendations related to cost optimization, security, and performance.
AWS Auto Scaling: Automatically scaled resources, ensuring the application could handle varying loads, especially during peak claim submission times.