Remote Healthcare Technology Leader: Revolutionizing DevOps with Automated Deployment Processes

Case Study

Encora Appoints Anand Birje as Chief Executive Officer


Remote Healthcare Technology Leader:

Remote Healthcare Technology Leader:

Revolutionizing DevOps with Automated Deployment Processes

Industry: Healthcare & Life Sciences

Delivery Center: India

DevOps Revolution for HealthTech client-Industry Context

Industry Context

The demand for remote healthcare technologies is increasing, driven by an emphasis on better patient outcomes and lower healthcare costs. The major challenge is ensuring seamless operations of these remote medical technologies, especially managing infrastructure and deploying them efficiently. Therefore, to remain at the forefront of delivering top-notch medical technologies, enterprises are looking for technological transformations to streamline deployment, improve availability, enhance scalability, and maintain reliability.

DevOps Revolution for HealthTech client-Client Challenge

Client Challenge

Our client, a pioneer in remote medical technology, offers comprehensive solutions to enhance quality of life and decrease healthcare costs through remote cardiac monitoring, centralized clinical trial services, and more. The client faced operational challenges within its AWS Elastic Kubernetes Service (EKS) clusters due to a complex microservices architecture and the use of diverse deployment technologies, including Helm, Ansible, and Terraform. These challenges resulted in manual, error-prone deployment processes that compromised development speed and system stability. The need for a streamlined, automated, and consistent deployment process was critical to sustaining the client’s commitment to delivering top-notch healthcare technology solutions.


Encora was enlisted to orchestrate a technical transformation for the client, focusing on automating deployment processes and enhancing infrastructure efficiency within AWS. The solution encompassed several strategic initiatives: 

  • DevOps Consulting: Initiated the transformation by deploying a new Amazon Elastic Kubernetes Service (EKS) cluster customized to the client's unique requirements, laying the groundwork for improved deployment and orchestration strategies. 
  • Continuous Integration (CI) & Continuous Deployment (CD): Established a fully automated CI/CD pipeline by integrating Jenkins with SonarQube for code quality checks. This facilitated smooth transitions from code commit to deployment and replaced the previous manual deployment methodologies. 
  • Automation & Toolchain Optimization: Introduced Kubernetes scaffolding automation for microservices hosted in Amazon Elastic Kubernetes Service (EKS), utilizing Jinja templates to enable self-service deployments via Jenkins. This innovation allowed developers to deploy updates autonomously, ensuring consistency and minimizing errors. 
  • Monitoring and Observability: Implemented a comprehensive suite of monitoring and observability tools, including Amazon CloudWatch, AWS CloudTrail, Prometheus, Grafana, and Loki, to offer deep insights into system performance and operational health, enabling proactive issue resolution and system optimization. 

AWS Services

Amazon Elastic
Kubernetes Service (EKS)

AWS CodeBuild

AWS CodeCommit

AWS CodeDeploy

AWS CodePipeline

Amazon CloudWatch

AWS CloudTrail

Amazon Simple
Storage Service (S3)

Amazon Relational
Database Service (RDS)


Encora's strategic intervention transformed the client’s DevOps landscape, ushering in a new era of efficiency, scalability, and reliability. Automated DevOps practices revolutionized the delivery and maintenance of healthcare technology solutions, ensuring the client’s continued leadership in providing modern medical technologies. 

Some of the transformative outcomes enabled by Encora and powered by AWS technologies are: 

  • Streamlined automated deployments with the newly established enterprise-grade deployment solution, significantly simplifying the process and enabling quicker development cycles. 
  • Enhanced developer efficiency by automating deployment tasks and enabling self-service deployments. This reduced the developer time spent on deployment activities, allowing for a greater focus on innovation and development of new features. 
  • Ensured scalability and resource optimization as the rearchitected system facilitated effective scaling of microservices in response to demand fluctuations. 
  • Improved system reliability and performance with the adoption of a unified deployment strategy and a comprehensive monitoring solution, including AWS CloudWatch and AWS CloudTrail, which resulted in reduced system downtime and improved availability.  

Deployment Time-1

Deployment Time

System Availability-1

System Availability