How Health Systems Can Optimize Their Virtualization Strategy

How AI Impacts Virtualization Needs

Integrating AI and automation with virtualization allows health systems to gain visibility into their data and manage it.

Health systems such as Mary Washington Healthcare in Fredericksburg, Va., have deployed VCF to gain visibility across IT operations. Mary Washington plans to automate its vCenter virtual machines with VCF Automation.

As health systems leverage AI as part of their virtualization strategy, they will experience a learning curve, according to Sachin Mullick, director of product management for OpenShift Virtualization and OpenShift Edge at Red Hat.

“Built-in generative AI assistants from the virtualization provider can significantly reduce the learning curve for these new technologies while providing troubleshooting assistance to solve hard problems in minutes,” Mullick says.

Health systems can use AI to detect sensitive patient health information and control access to sensitive data while also preventing leakage, he adds.

READ MORE: Meet the demand for modern data centers in healthcare.

“Integrating applications with proper sovereignty controls and data management tools is providing an improved patient experience,” Mullick says.

Miller says full-stack virtualization and full-stack automation can be considered “almost table stakes” when it comes to running AI workloads, including large language models.

“In a modern platform, you have to have both VMs and Kubernetes workloads supported on top of the platform to support AI,” Miller says.

The stack that runs LLMs should be both container-based and VM-based, he adds.

Here are some steps health systems can take to fine-tune their approach to virtualization.

Optimizing Virtualization Strategy in Healthcare

Upgrading core infrastructure should be a key approach to virtualization, according to Shannon Germain Farraher, senior analyst for healthcare at Forrester.

“Virtualization optimization is most effective when aligned with enterprise-wide modernization efforts,” Germain Farraher says.

Modernizing Core Infrastructure

To boost the performance and resilience of virtualized workloads, health systems should invest in cloud, security, SaaS/PaaS ecosystems and data infrastructure. In addition, by embedding a virtualization strategy into broader digital transformation goals such as clinician enablement, automation and analytics, health systems can avoid “siloed, piecemeal modernization,” she says.

Germain Farraher recommends that large health systems modernize their compute, network and storage capabilities to aid advanced analytics, AI and enterprise-wide digital platforms. Meanwhile, midsize health systems should build a robust cloud-ready base, and small practices should stabilize their infrastructure by developing compliance-first IT and secure telehealth capabilities.

“This ensures the virtual environment can handle clinical, operational and data‑intensive workloads reliably and cost‑effectively,” Germain Farraher says.

Mullick also sees a need to modernize and streamline operations.

“The focus is on moving away from legacy operational models to modernize infrastructure, automate deployments and adopt DevOps processes to speed up application delivery,” Mullick says.

He notes that if health systems simply renew an existing environment and “stay put,” they are postponing addressing their infrastructure needs.

“If they just continue down the current path by renewing an existing environment, they are essentially paying a ‘status quo tax’ — kicking the can down the road without solving the lock-in problem or preparing for AI,” Mullick says.

Instead, pursue modernization in steps and use a “factory approach” to incorporate virtual machines from your existing environment “as is,” according to Mullick.

“Traditional applications in VMs can continue to run while the platform provides additional capabilities around automation, creation of cloud-native applications, and bringing in brand-new AI applications,” Mullick says. “This approach helps ensure that as health organizations build out internal AI capabilities for things like clinical decision support or medical billing, infrastructure isn’t the thing that holds them back.”  

Opting for a Hybrid Approach

Health systems can benefit from an open-source hybrid cloud strategy, according to Mullick.

“Healthcare organizations need to understand their workload portability needs across on-premises, sovereign and public clouds,” Mullick says. “There is opportunity to move some applications to being container native.”

Meanwhile, private cloud brings benefits around data control and cost, according to Miller.

“People want more control on how they get charged, and they can have more control in private cloud than they can in public cloud,” Miller says. “And they can save more money as well.”

DISCOVER: Consider these strategies for virtualization software decisions.

Employ Platform Engineering

Platform engineering, which involves constructing the cloud-based technologies that power software systems, is a key component of a virtualization strategy and an evolution of DevOps.

“For the majority of the applications that still remain as virtual machines, adopting platform engineering concepts will help to improve security, developer productivity, business efficiency and agility,” Mullick says.

Go for Proof of Value

Health systems can shore up their virtualization and platform by pursuing a proof of value strategy, Mullick advises.

“These practices include adopting concepts such as a self-service portal for launching and managing compliant applications, streamlined infrastructure management through automating deployments, and adopting DevOps practices,” Mullick says.

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Healthcare Partnerships

To optimize virtualization strategies, health systems should partner with cloud-managed service providers and healthcare-specialized vendors, Farraher advises.

“These partners mitigate risk, accelerate cloud migration, ensure correct configuration and help build co‑innovation capabilities — all of which reduce friction in virtualization modernization,” Farraher says.

Miller notes that organizations such as health systems lack the time and resources to manage complex architectures like they had in the past with many solution vendors.

“They’re really seeking more strategic partnerships with more full-featured platforms to move together with them over time,” Miller says.