Project Name
How a Healthcare Organization Cut Infrastructure Costs and Modernized VMs with OpenShift
Our client is a healthcare technology organization providing digital platforms for hospital operations, electronic medical records (EMR), and patient engagement. Its solutions are used by hospitals, clinics, diagnostic centers, and telehealth providers, supporting high-volume, mission-critical workloads such as patient data processing, clinical reporting, and system integrations.
As digital healthcare adoption accelerated, the organization experienced rapid growth in users and data volumes. To meet strict requirements around data security, availability, and compliance, the client relied on an expanding on-premises, VM-based infrastructure. Over time, this approach increased operational complexity and costs, prompting the organization to modernize its infrastructure and reduce its data center footprint without disrupting patient services.
Our client faced several critical infrastructure and operational challenges tied to its traditional data center model:
- High Data Center Footprint & Costs: The client operated multiple on-premises data centers across India to host VMs for its applications, databases, and analytics workloads. This resulted in high power, cooling, hardware procurement, and maintenance costs.
- Scalability Constraints: Managing peak loads, especially during seasonal outbreaks or increased telehealth usage, was difficult due to rigid VM provisioning and limited automation.
- Application Modernization Bottlenecks: Several core applications were built on legacy architectures running on virtual machines, which made it hard to adopt microservices, CI/CD, and cloud-native capabilities.
- Resource Inefficiency: Many VMs were underutilized, leading to wasted compute resources and inefficient capacity planning.
- Long Provisioning Times: Spinning up new VMs for development, testing, or new regions took days or weeks, slowing business velocity.
With our OpenShift consulting services, our experts designed and executed a full-scale migration of VM workloads to Red Hat OpenShift, which is a Kubernetes-based container platform. The approach was structured around these key phases:
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Assessment & Planning
- Conducted a detailed workload assessment, identifying 120+ VMs suitable for containerization.
- Classified applications by criticality, dependencies, and modernization roadmap.
- Built an OpenShift migration strategy with clear timelines, risk mitigation plans, and KPIs (e.g., footprint reduction, time-to-provision, cost savings).
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Containerization & Modernization
- Repackaged legacy VM workloads into containers where feasible; used the Strangler pattern to decouple monoliths.
- Migrated databases to managed clusters, and containerized stateless services for portability.
- Implemented CI/CD pipelines using GitOps with Argo CD and Tekton for automated deployments.
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OpenShift Implementation
- Deployed an OpenShift 4.x cluster across a hybrid environment – co-located in the client’s own data center and public cloud for elasticity.
- Enabled autoscaling, health monitoring, and multi-tenant namespaces to support teams independently.
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Migration & Cut-Over
- Incrementally migrated services from VMs to OpenShift using blue-green and canary deployments to avoid downtime.
- Integrated enterprise logging, monitoring (Prometheus/Grafana), and centralized security policies (RBAC, NetworkPolicies).
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Training & Operational Support
- Conducted hands-on workshops for DevOps and infrastructure teams on OpenShift operations and Kubernetes patterns.
- Delivered post-migration support with performance optimization sessions.
- 70% Reduction in Virtual Machines: Consolidated legacy VM workloads into containerized applications on OpenShift, significantly simplifying infrastructure management.
- 30% Annual Infrastructure Cost Savings: Optimized resource utilization and reduced licensing and maintenance overhead.
- 7× Faster Environment Provisioning: Reduced provisioning time from days to under 30 minutes through automation and standardized deployment pipelines.
- 40% Faster Release Cycles: Enabled teams to deploy updates more frequently using CI/CD and GitOps practices.
By migrating virtual machine–based workloads to Red Hat OpenShift with our consulting services, the client successfully reduced its data center footprint while modernizing its application platform. The shift enabled better resource utilization, faster deployments, and lower operational costs, without compromising on security or availability. With a scalable, cloud-native foundation in place, the organization is now positioned to support future growth, adopt microservices incrementally, and respond faster to evolving healthcare demands.
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