GenomeNext DevOps Process

GenomeNext DevOps Process

GenomeNext is a genomic informatics company dedicated to accelerating the promise and capability of predictive medicine and scientific discovery. It commercializes genomic analysis tools and integrated systems for the evaluation of genetic variation and function.

The advanced informatics and data management solutions are designed to simplify, expedite and enhance genetic analysis workflows. GenomeNext solutions provide the market with genomic data and analysis at an unprecedented combination of performance, quality, cost and scale without requiring the investment in high-performance computing resources and specialized personnel. The proprietary platforms address a broad range of highly interconnected markets, including sequencing, genotyping, gene expression, and molecular diagnostics. GenomeNext customers include leading genomic research centers, academic institutions, government laboratories, and clinical research organizations, as well as pharmaceutical, biotechnology, agrigenomics, and consumer genomics companies.

The Challenge

GenomeNext needed a more efficient way to develop and deploy application changes to its Amazon Web Services Genomics Cloud Platform while maintaining high level of security and compliance.

The Solution

We worked with GenomeNext to design efficient development and agile management process, setup internal DevOps software and AWS infrastructure components, mapped processes to appropriate security and compliance controls, integrated third party DevOps tools with the GenomeNext Cloud platform, implemented development life cycle environments (Dev, QA, and Prod) on AWS, monitored and reduced AWS costs, and architecture high availability and disaster recovery. Our solution enhanced GenomeNext’s ability to quickly and securely roll out application development and infrastructure changes with minimal to zero downtime through the use of tools such as AWS Elastic Load Balancing, AWS CloudWatch, AWS CloudFormation, and AWS CodeDeploy.

The Benefits

Automation

GenomeNext recognized the advantages of DevOps automation by a significant increase in deployment frequencies, a dramatic decrease in deployment failures, immediate recovery of failed deployments, and reduction in the time required for changes.

Disaster Recovery

By combining AWS and DevOps, GenomeNext can automate the deployment of an exact copy of its Production solution within minutes into any AWS region, allowing it to meet its recovery time objectives.

Cost Savings

GenomeNext realized cost saving utilizing DevOps and AWS. Cost saving came in terms of maintaining a small staff, increased quality of products, reduction deployment complexity, and faster time to market.

Real-time logging of Tsunami Data Aids in Disaster Response

Real-time logging of Tsunami Data Aids in Disaster Response

Effectual worked with a federal government customer to provide information for local land-use and emergency response planning to avoid development in hazardous zones and to plan evacuation routes to communities along low-lying coastlines vulnerable to tsunamis.

The Challenge

The customer looked to our team to quickly and effectively move their public-facing web applications and internal applications to the AWS cloud to ensure resiliency, availability, and real time logging of tsunamis.

The Solution

We implemented a solution comprised of Amazon CloudWatch, AWS CloudTrail, Alarms, and Serverless Storage. This ensured the clients ability to collect data to help scientists understand tsunamis through their application to develop how to most effectively improve preparedness and response to tsunamis.

The Benefits

Resiliency
We implemented Amazon CloudWatch to schedule data collection that self-triggers when a tsunami is detected.

Availability
By implementing AWS CloudTrailthe client was able to easily access tsunami data to help scientists understand the sources of local tsunamis so that the impacts of future events may be mitigated.

Real Time Logging
Our team set up serverless storage to collect data from these seismic networks to process key components in the impact of tsunamis.