re:Invent 2024

Pharmaceutical company maximizes application scalability and resiliency with AWS microservices

Healthcare & Life Science
Infrastructure & DevOps Modernization
Application Modernization

60%

Lower Infrastructure Scaling Costs

Company

Allergan Data Labs (A-DL) exists to disrupt the aesthetics industry through data, design, and technology. We operate with the rigor and agility of a start-up and, with the encouragement of our corporate backers, we drive innovation.

allergandatalabs.com

Location

Irvine, CA

Industry

Healthcare & Life Science

Share

Through adopting microservices architecture and DevOps best practices, Allergan Data Labs now benefits from seamless and automated scalability, resilience to high traffic stresses, and reliability that is desirable from an application serving an enterprise use case.

Allergan Data Labs is an innovative technology and marketing intelligence division within Allergan Aesthetics, one of the world’s largest pharmaceutical companies. With a mandate to transform their medical aesthetics business, Allergan Data Labs utilizes machine learning to rethink and improve digital consumer experiences. In use throughout nearly 20,000 medical offices and spas, their platform services over 3.5 million users across the US. 

Challenge

Allergan Data Labs started out as a small team trying to create a new digital platform for services such as gift card processing, rewards programs, payment management across different methods, reimbursements and more. On National Botox day, Allergan experienced unexpectedly high traffic volume on their application that was burdening their existing system, negatively impacting digital customer experience. 

In order to avoid overwhelming their infrastructure in the future, Allergan Data Labs sought Caylent’s help to improve the resilience, scalability and reliability of their infrastructure while optimizing costs.

Solution

When Allergan Data Labs began their collaboration with Caylent, they had already started on the path to adopting Serverless Architecture on AWS for their new application. They were looking to leverage Kubernetes in addition to the AWS Lambda serverless compute service, to optimize performance and costs. Caylent brought their expertise to enable Allergan Data Labs on their transformation journey, providing them with the knowledge and implementation skillset needed to make the most out of their serverless adoption.

The company’s infrastructure needs had also further expanded beyond their rewards program application. Leaving aside their existing Serverless applications, all their digital functions would now require integration into Kubernetes. The Caylent team helped Allergan from the ground up, developing a containerizing workflow so that future product features can follow DevOps best practices in Amazon EKS, setting up AWS organizations and OKTA, building custom landing zones using AWS Control Tower, custom VPCs and more.

The team reworked both the front end and back end of the infrastructure to comply with a CI/CD deployment methodology. The architecture went from monolithic pipelines to smaller microservices, reducing deployment times from hours to minutes. These measures improved the environment significantly, boosting the team’s confidence in adding more workloads.

For security, Caylent helped Allergan develop a content delivery network with restrictions for data access across the organization. AWS Shield Advanced was enabled, protecting against DDoS threats. Audits were performed utilizing Veracode to check all of the infrastructure’s functions. AWS CloudWatch Metrics & Alarms, AWS X-Ray and DataDog were utilized for observability, monitoring, logging and alerting and Caylent helped Allergan migrate to a new and improved VPC architecture. Amazon EC2 Reserved Instances were leveraged to optimize costs.

The Caylent team also prioritized educating the Allergan Data Lab team in how to optimally utilize and manage the suite of services behind the infrastructure as well as adopt a DevOps culture within their team to improve the efficiency and speed of deployments for their application. The team provided documentation and held tutorials and lunch and learn sessions to tackle various key topics, from understanding and utilizing best practices in CI/CD to managing and operating in Kubernetes. One of the main objectives behind this education focus was to enable Allergen Data Labs to be independent and avoid vendor lock-in – something that happens often when vendors utilize proprietary tools and methodologies to solve problems, limiting the client’s ability to understand and manage their own solutions.

Beyond transforming the application environment, the Caylent team realized that for events such as Botox Day to be successful, transformation would be required across other applications managed by other Allergan organizations, that were hosted upon traditionally configured virtual machines, treated like data center servers. This was because the new application Allergan was developing, had shared dependencies with this older platform. To resolve this, the Caylent team proactively reached out to the other organizations, helping them improve the scalability and resilience of the infrastructure supporting their applications.


Tory Brady

Caylent has a high level of expertise for everything we are doing or considering doing on AWS, they know how to move fast and get results.

Tory Brady

Associate Vice President

Through adopting microservices architecture and DevOps best practices, Allergan Data Labs now benefits from seamless and automated scalability, resilience to high traffic stresses, and reliability that is desirable from an application serving an enterprise use case. Adopting a DevOps culture and CI/CD pipeline-based development methodology has helped the company reduce their application deployment time from hours to minutes, while also improving deployment frequency through smaller, iterative updates.

The Caylent team also helped Allergan Data Labs optimize the costs of scaling their environment. The initial setup was configured for manual provisioned concurrency tuning which was proving very expensive. The team was able to help them lower these costs from $75,000 per month to $30,000, representing a savings of 60%.


Company

Allergan Data Labs (A-DL) exists to disrupt the aesthetics industry through data, design, and technology. We operate with the rigor and agility of a start-up and, with the encouragement of our corporate backers, we drive innovation.

allergandatalabs.com

Location

Irvine, CA

Industry

Healthcare & Life Science

Share

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