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Case Study

Leading Global Life Sciences Company

Industry

Life Sciences/Genomics

Use Case

Genomic Sequencing

Deployment

Cloud Native Qumulo on AWS

Location

United States

Company Overview

A leading global life sciences company with one of the world’s largest clinical lab networks, sought to migrate from Dell EMC Isilon to AWS. They needed petabyte-scale storage with a single namespace, multi-protocol support, and lower latency for NGS workflows.

Requirements

Results

Partner

Empowering Genomic Discovery with Qumulo & AWS

A leading global life sciences company that operates one of the largest clinical laboratory networks worldwide provides a comprehensive range of medical laboratory tests and services to healthcare providers, pharmaceutical companies, and individuals.

The Challenge

This organization wanted to migrate from on-premises Dell EMC Isilon to AWS. They were looking for a petabyte-scale storage solution that offers a single namespace with multi-protocol support. In addition, they had latency issues with NGS (Next Generation Genomic Sequencing) workflows.

The Solution

Cloud Native Qumulo on AWS that leverages EC2, EBS, and S3 provided this organization with a high-performance, multi-protocol, scalable storage platform that is petabyte-scale. They currently have 3 Qumulo on AWS environments – production, non-prod, and disaster recovery. They deployed the solution quickly and accurately using Terraform to create the persistent storage and the cluster compute and cache resources.

Business Impact

By leveraging Qumulo on AWS with Illumina DRAGEN, the organization was able to reduce the latency of their NGS runs by 6x [24 hours -> 4 hours], leading to faster drug discovery. They were also able to migrate their Genomics data pipeline from on-premises to AWS successfully, ~1B files totaling 7.14 PB.

With the organization leadership’s push to move out of the data center into the AWS cloud, Qumulo was the only solution that could meet the scale, performance, and multi-protocol needs of their next-generation genomic sequencing workload.