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Healthcare

Enhancing Scalability and Deployment Efficiency for Healthcare Applications

Dashboard showing real-time metrics for uptime, response time, and resource usage of healthcare applications.

Focus Areas

Application Scalability and Performance

DevOps and CI/CD Automation

Cloud-Native Architecture

Automated application ensuring functional and secure services in healthcare applications.

Business Problem

A leading healthcare software provider offering patient engagement and EHR integration tools faced bottlenecks in deploying updates and scaling services. Applications hosted on legacy virtual machines could not handle increasing user loads during peak hours, and manual deployment processes led to frequent downtimes. The organization needed a cloud-native approach to improve scalability, accelerate delivery, and ensure high availability for critical healthcare applications.

Key challenges:

  • Monolithic Architecture: Core applications were tightly coupled, limiting horizontal scaling.

  • Manual Deployment Processes: Deployments were handled manually, resulting in inconsistent environments and rollback issues.

  • Limited Observability: Lack of end-to-end monitoring made it difficult to diagnose performance degradation.

  • Environment Drift: Inconsistent configurations across development, staging, and production environments caused deployment failures.

  • Slow Feature Delivery: Releases took weeks due to code integration issues, testing delays, and manual approvals.

The Approach

Curate partnered with the healthcare software provider to implement a container-based architecture, build automated CI/CD pipelines, and apply infrastructure-as-code for consistent cloud environment management. This enabled the team to deploy updates rapidly, scale services dynamically, and improve resilience across their application ecosystem.

Key components of the solution:

  • Discovery and Requirements Gathering:

    • Architecture Review: Analyzed existing monolithic systems, deployment methods, and pain points across environments.

    • Scalability Assessment: Identified performance bottlenecks and peak load behavior across modules.

    • Developer Interviews: Gathered input on pain points related to version control, build times, and testing workflows.

    • Security and Compliance Needs: Mapped DevOps processes to HIPAA compliance requirements.

  • Solution Design and Implementation:

    • Containerization: Refactored applications into Docker containers to isolate services and simplify scaling.

    • Microservices Transition: Split core functionality into independent microservices for modular development and scaling.

    • CI/CD Pipelines: Implemented GitHub Actions and Jenkins to automate build, test, and deployment stages with approval gates.

    • Auto-Scaling and Load Balancing: Deployed services on AWS EKS with horizontal pod autoscaling and ELB to manage traffic.

    • Monitoring and Observability: Integrated tools like Prometheus, Grafana, and Datadog for real-time performance insights and error tracing.

  • Process Optimization and Change Management:

    • DevOps Training: Conducted workshops on Git workflows, CI/CD best practices, and container debugging.

    • Playbooks and Automation Scripts: Created reusable scripts and templates for rapid environment setup and rollback.

    • Release Management Process: Standardized deployment schedules, automated release notes, and rollback protocols.

    • Shift-Left Testing: Integrated automated testing earlier in the development cycle to reduce post-deployment defects.

Business Outcomes

Increased Scalability


Containerized services scaled automatically based on usage, ensuring application reliability during high-demand periods.

Faster Time to Market


CI/CD pipelines reduced deployment time from weeks to hours, enabling frequent and reliable feature delivery.

Improved Deployment Reliability


Infrastructure-as-code and consistent environments reduced configuration drift and deployment errors.

Enhanced Developer Productivity


Automation and standardized workflows reduced manual effort, freeing up engineering teams for innovation.

Sample KPIs

Here’s a quick summary of the kinds of KPI’s and goals teams were working towards**:

Metric Before After Improvement
Average deployment time 3 days 2 hours 93% reduction
Deployment frequency Monthly Daily Significant Improvement
Downtime during release 2 hours/release 5 mins 96% reduction
Scalability limit 2x peak load 10x peak load 5x improvement
Environment setup time 1 week 2 hours 94% faster setup
**Disclaimer: The set of KPI’s are for illustration only and do not reference any specific client data or actual results – they have been modified and anonymized to protect confidentiality and avoid disclosing client data.

Customer Value

Operational Agility


Delivered the ability to respond rapidly to evolving business and regulatory requirements.

Service Reliability


Ensured high availability for mission-critical healthcare applications.

Sample Skills of Resources

  • DevOps Engineers: Built CI/CD pipelines and managed Kubernetes deployments.

  • Cloud Architects: Designed scalable AWS-based microservices infrastructure.

  • Site Reliability Engineers (SREs): Developed observability tools and handled production incident response.

  • Backend Developers: Refactored legacy code into containerized microservices.

  • Automation Specialists: Created IaC templates, monitoring scripts, and release workflows.

Tools & Technologies

  • CI/CD and SCM: GitHub Actions, Jenkins, Argo CD

  • Containerization: Docker, Kubernetes, Helm, AWS EKS

  • IaC and Deployment: Terraform, Ansible, CloudFormation

  • Monitoring & Observability: Prometheus, Grafana, Datadog, ELK Stack

  • Cloud Services: AWS EKS, RDS, S3, CloudWatch, Route53

  • Collaboration & Workflow: Jira, Confluence, Slack

Containerized application components being deployed using Docker and Kubernetes for better scalability.

Conclusion

By transforming its development and deployment ecosystem, the healthcare organization significantly enhanced its application scalability and operational agility. Curate’s cloud-native, automated solution empowered the client to meet patient needs faster, reduce operational friction, and build resilient applications in a regulated healthcare environment.

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