The agriculture division of a leading global science and engineering company maps the genome of different strains of seeds to help make informed decisions.
The company’s previous on-premise infrastructure limited the amount of genetic sequences it could capture, process and store. They wanted to utilize the scalability and cost effectiveness of the cloud to process and store more data.
The company has been able to retire 200 servers and avoid the cost and resource of a tech refresh. The business can now process 10x as many genomes per year utilizing the scalability of the AWS cloud—it used to take 8 days to complete, now it takes just 8 to 10 hours. This project brought down the cost of processing and storing genetic sequence data by 50% and has made the processing of an individual genetic sequence 5x faster.
A multi-faceted project saw us replatforming three genomics applications into the AWS Cloud, and redesigning them to be almost serverless. We used automation to deploy all cloud resources, introduced modernized code, and built out a fully automated CI/CD pipeline utilizing a hybrid cloud model in AWS.