HealthTech | Healthcare and Scientific Research | LifeSciences | Biotechnology Research

Leveraging AWS to streamline cloud orchestration, improve deployment efficiency, and reduce operational complexity.

About The Client

The customer is a global biomedical company specializes in advancing healthcare through innovative diagnostic and life sciences solutions. By focusing on clinical workflows and data-driven technologies, it supports laboratories and research institutions in delivering accurate, timely results. The organization plays a key role in enhancing efficiency and reliability across the diagnostic spectrum.

The customer owns a cloud-based informatics platform built to help research scientists efficiently manage, evaluate, and share data. The platform has advanced visualization tools that allow scientists to delve deeper into the data. Considering the critical nature of the data, flawless performance is a key imperative, mandating comprehensive testing of the platform.

With advancements like generative AI and quantum computing, the landscape of DevOps is evolving from automation to intelligent orchestration. 

The Need

The client, a leading life sciences organization, wished to optimize its Flow Cytometry platform’s infrastructure to support the scalability demands of its pharmaceutical partners. The goal was to reduce deployment times, automate configuration management, and minimize human error, ensuring a faster and more reliable environment to support research workflows.

The Solution

Forgeahead implemented a solution centered on automation and centralized management, addressing key challenges in configuration, scaling, and release efficiency:

Automated cloud orchestration and configuration management

Implemented AWS Systems Manager (SSM) to automate patching, deployments, and configuration control, eliminating manual processes that slowed deployment.

CI/CD Automation with AWS CodeBuild

Established an automated build and deployment pipeline using AWS CodeBuild, which accelerated release cycles, reduced errors, and ensured consistency across environments. 

Role of AWS

AWS provided essential tools to build a robust, scalable, and secure SaaS application:

Automated Scaling and Configuration

AWS Systems Manager and CodeBuild automated infrastructure orchestration, scaling, and patching, minimizing manual intervention.

Improved Monitoring and Compliance

AWS’s centralized management features provided ongoing compliance, security, and streamlined infrastructure monitoring, significantly reducing operational risks

Reliable CI/CD Pipeline

AWS CodeBuild enabled a streamlined CI/CD workflow, ensuring quick deployments and reducing build failures.

High Availability and Consistency

AWS’s tools enabled consistent environments across multiple cloud regions, providing improved uptime and efficient resource utilization.

The Impact

Release cycles accelerated, enabling faster time-to-market.

Deployment times improved with automation replacing manual processes.

Centralized management reduced downtime and ensured system reliability.

Dynamic—automated compliance and security enhancements.

DevOps Stack

AWS, Docker, SSM, Splunk, Terraform, CloudFormation, Pulumi, Kubernetes, Pipelines