Visualization Platform Migration to Cloud

Client / Industry

Enterprise Analytics Platform (OEM-based Visualization Product)

Problem Statement

A Qlik Sense OEM–based visualization platform deployed on on-premise infrastructure was facing significant challenges in scalability, reliability, and cost efficiency. As data volumes and concurrent user demand increased, the platform experienced: Performance degradation during peak usage Limited horizontal scalability for visualization workloads High infrastructure and maintenance overhead Inefficient resource utilization due to static capacity planning The business required a cloud-native, highly available, and cost-optimized architecture to support enterprise-scale analytics while improving reliability and reducing operational costs.

Architecture Overview

Led the migration and modernization of the Qlik Sense OEM visualization platform to AWS, transforming it into a highly available, scalable, and cost-optimized cloud architecture. Designed a resilient architecture: Multi-AZ deployment of Qlik Sense nodes for high availability Decoupled compute and storage using Amazon EC2 and S3 Centralized data layer with optimized data ingestion pipelines Load-balanced access layer using Application Load Balancer Auto-scaling for supporting components to handle variable workloads Key enhancements: Implemented Reserved Instances and Savings Plans to optimize long-running workloads Right-sized compute instances based on workload profiling Introduced failover mechanisms and redundancy to eliminate single points of failure Enabled centralized monitoring and alerting for proactive issue resolution Optimized data refresh and caching strategies for faster dashboard performance Delivered a highly reliable, enterprise-grade visualization platform with improved performance and optimized cost structure.

AWS Services

Amazon EC2, Application Load Balancer, Amazon S3, Amazon RDS (if metadata DB), AWS IAM, Amazon CloudWatch, AWS Backup, AWS Auto Scaling, Savings Plans, Reserved Instances

Outcomes

Significant improvement in platform reliability (99.9%+ uptime) Optimized infrastructure cost using Reserved Instances & Savings Plans Improved dashboard load performance and user experience Enhanced scalability to handle concurrent enterprise users Reduced operational overhead through cloud-native management Improved system resilience with multi-AZ deployment Better resource utilization through right-sizing and capacity planning