About Client
The client is a fast growing workforce intelligence platform operating in the employee productivity and workforce analytics domain. With an expanding customer base and increasing platform demand, the organization required a more scalable, secure, and cost-optimized cloud environment. To strengthen operational resilience and support future growth, the client initiated a strategic migration of its infrastructure from Microsoft Azure to Amazon Web Services (AWS), focusing on enhanced governance, improved security controls, and long-term scalability.
The Workforce Intelligence Platform’s infrastructure was hosted on Microsoft Azure and had expanded rapidly in line with platform growth and increasing user adoption. Over time, the cloud environment became complex, making it difficult to maintain consistent governance, security controls, and operational visibility across development and production environments. The workforce intelligence platform faced challenges in establishing a structured network architecture to support containerized workloads and ensure high availability and efficiently managing Kubernetes workloads, migrating databases with minimal downtime, and securely transferring large volumes of object storage data ensured smooth operations and high system reliability. Limited centralized logging, monitoring, and cost governance further reduced visibility into system performance, security events, and cloud expenditure. These constraints highlighted the need for a secure, scalable, and well-governed AWS foundation capable of supporting Kubernetes-based applications, managed database services, and long-term cloud growth..
To support the migration from Microsoft Azure to AWS, Comprinno designed and implemented a secure, scalable, and governance-driven AWS environment aligned with the organization’s growth objectives. The engagement followed a structured lift-and-shift strategy while simultaneously establishing a strong architectural foundation to improve resilience, visibility, and operational efficiency. Security guardrails, identity federation, and structured access controls were implemented to ensure consistent compliance and controlled resource access.
Containerized workloads were re-deployed on Amazon EKS to provide high availability and auto-scaling capabilities across multiple Availability Zones. Database workloads were migrated to Amazon RDS PostgreSQL using AWS Database Migration Service (DMS) to ensure minimal downtime and data integrity during cutover. Large-scale object storage was securely transferred from Azure Blob Storage to Amazon S3 using AWS DataSync. A secure three-tier VPC architecture was implemented to isolate web, application, and database layers, while encryption, monitoring, and auditing services were enabled to strengthen security posture. Centralized logging, cost governance, and proactive monitoring mechanisms were introduced to enhance operational visibility and financial transparency. The resulting AWS environment provided a resilient, well-governed, and future-ready cloud platform capable of supporting Kubernetes-based workloads and long-term scalability. The resulting AWS setup provided a secure, scalable, and compliant foundation capable of supporting the company’s digital initiatives and future growth.
Secure and Resilient Network Architecture :
Kubernetes-Based Application Modernization :
Managed Database Migration with Minimal Downtime :
Secure and Efficient Data Transfer :
Enhanced Security, Observability, and Compliance Controls :
The architecture is designed within a secure and scalable AWS multi–Availability Zone setup to ensure high availability, resilience, and operational stability. External user traffic is routed through Amazon Route 53 and protected by AWS Web Application Firewall (WAF) before reaching the Application Load Balancer (ALB). The ALB distributes incoming requests across application instances deployed on Amazon EC2 within private subnets, ensuring secure and controlled access to backend services. The infrastructure is hosted inside a dedicated Amazon VPC spanning multiple Availability Zones. Public subnets host NAT Gateways to enable secure outbound internet access for private resources, while application and database layers remain isolated within private subnets for enhanced security. The database tier consists of Amazon RDS (MySQL and PostgreSQL) and Amazon ElastiCache deployed in a multi-AZ configuration to ensure reliability, fault tolerance, and improved performance.
Container images are managed through Amazon Elastic Container Registry (ECR), while centralized monitoring and observability are enabled using Amazon CloudWatch and Managed Grafana. Security and compliance are strengthened through AWS IAM, AWS KMS, AWS Secrets Manager, AWS CloudTrail, GuardDuty, and Security Hub. Governance controls are implemented using AWS Organizations and Control Tower to standardize account management and enforce guardrails.
This layered and well-segmented architecture ensures secure traffic flow, workload isolation, high availability, centralized monitoring, and strong governance across the AWS environment, providing a resilient and scalable foundation for workforce intelligence platform company operations.
The Azure-to-AWS migration and infrastructure modernization established a secure, scalable, and performance driven cloud foundation for the workforce intelligence platform. By containerizing workloads, strengthening governance controls, and adopting managed services, the environment transitioned into a more resilient and operationally efficient setup. Enhanced monitoring, security standardization, and cost visibility improved overall control while reducing operational complexity. This transformation has positioned the workforce intelligence platform to scale confidently, accelerate product innovation, and support growing user demand with a stable and future-ready AWS ecosystem.
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