3 Real‑Life IaaS Use Cases Across Industries in 2025

Over the last few years,  Infrastructure as a Service (IaaS) has gained substantial recognition for its ability to increase application deployment speed, remarkable uptime, and overall improvement in operational efficiency. According to Gartner, spending on cloud system infrastructure services jumped from 21.3% in 2024 to 24.8% in 2025. 

Simply put, IaaS has evolved into a sophisticated, foundational cloud model that delivers on-demand compute, storage, networking, virtualization, and edge-ready infrastructure, often with built-in AI/ML acceleration, over the internet.

This blog post focuses on real-life uses of IaaS models and the future trends of IaaS in various sectors. 

Why IaaS is essential

Although there are several public cloud providers, some organizations prefer to have their applications run on their own private capabilities instead. Nonetheless, Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), Alibaba Cloud, and IBM Cloud continue to be the leaders as public IaaS vendors.

Whether it’s a healthcare provider needing to meet Health Insurance Portability and Accountability Act (HIPAA) compliance or a retail giant preparing for holiday-season traffic spikes, IaaS helps organizations scale with demand, reduce capital expenses, and deploy new applications faster. 

Here are three major reasons why there is an uptick in the adoption of IaaS across industries. 

• Scalability - IaaS delivers instant horizontal and vertical scaling capabilities, spin up VMs, container clusters, load balancers, and block/object storage on demand. This elasticity supports bursty workloads without over-provisioning or delays. 
• Cost‑Efficiency - Transitioning from CapEx (data centers) to OpEx (pay-as-you-go) models means organizations only pay for what they use. Tools like cloud cost analytics and FinOps frameworks help optimize consumption and avoid waste.
• Agility - IaaS supports faster deployments—for dev/test environments, new product launches, disaster recovery drills, or scaling online services. Developers and IT teams can provision infrastructure in minutes versus weeks or months.

How industries are leveraging IaaS adoption

GE Healthcare is widely known for its medical imaging equipment and diagnostic imaging agents. As part of their digital transformation, the company launched GE Health Cloud, which runs on AWS IaaS to support petabytes of imaging data and analytics. It achieves global availability, secure access to medical images, and elastic compute for AI diagnostics, without the burden of physical hardware. This architecture handles regulatory compliance and uptime guarantees, which are essential in healthcare. The company also has plans to expand its use to Amazon SageMaker for its ML models. This move will significantly reduce time-to-insight for critical diagnoses, empowering radiologists and healthcare providers with AI-supported decision-making tools at scale.

Another important example comes from the e-commerce giant eBay. As one of the world’s largest e-commerce platforms, eBay experiences massive fluctuations in web traffic, especially during major shopping events like Black Friday, Cyber Monday, and holiday sales. Managing this unpredictable surge without overinvesting in permanent infrastructure poses a significant challenge.

To address this, eBay adopted a cloud-first, Infrastructure as a Service (IaaS) strategy that enables dynamic resource scaling in real-time. eBay reported a 25% reduction in infrastructure costs compared to maintaining fixed, over-provisioned server capacity on a year-round basis. This elasticity not only improves operational efficiency but also enables consistent site performance during traffic spikes, reducing cart abandonment and lost revenue.

J.P. Morgan Chase, one of the largest and most technologically advanced banks in the world, has been at the forefront of blockchain adoption in the financial services sector. As digital assets, decentralized finance (DeFi), and real-time settlement models gain traction, the bank has strategically leveraged Infrastructure as a Service (IaaS) to scale its blockchain operations, particularly in the area of high-frequency trading (HFT). By scaling blockchain nodes across IaaS instances, J.P. Morgan significantly reduced system lag and increased the number of trades processed per second.

Other core uses of IaaS 

Beyond those flagship examples, IaaS is routinely deployed in other core cases. 

Industry‑wide patterns: scalability, compliance and cost optimization

Across these sectors, recurring IaaS adoption patterns emerge:

• Elastic Scalability - Businesses allocate compute and storage dynamically, scaling up for peak demand (e.g. imaging workloads, web traffic) and scaling down when idle, thus eliminating waste and ensuring responsiveness.
• Regulatory & Security Alignment - IaaS offerings often include compliance-ready templates and secure environments. Sectors like healthcare or finance rely on audit logs, encryption, data isolation, and disaster recovery SLAs embedded in IaaS packages.
• Cost Optimization & Control - Operational cost management tools and consumption visibility allow companies to forecast spend, implement auto-shutdown or rightsizing policies, and adopt FinOps practices to control cloud budgets. 

Future trends: sector‑specific customization in IaaS

IaaS is becoming increasingly aligned with sector‑specific requirements. Key future directions include:

• Healthcare: GPUs for imaging/data processing; edge‑cloud architectures for on‑site diagnostics and telemedicine; HIPAA‑compliant, AI‑integrated computing pipelines.
• Finance & Fintech: Real‑time analytics, low‑latency trading platforms, blockchain‑ready infrastructure, quantum-safe encryption layers.
• Retail & E-Commerce: AI‑driven personalization engines, localized edge zones for fast fulfillment, serverless APIs scaling instantaneously during flash sales.
• Manufacturing & Logistics: Digital twin infrastructure, real‑time IoT sensor analytics, hybrid IaaS with on‑prem factory edge nodes and cloud back‑end for predictive maintenance.
• Media & Entertainment: Cloud rendering farms using GPU instances, global content distribution networks (CDNs) built into IaaS offerings, AI moderation and content tagging pipelines.
• Education: Virtual labs, remote exam environments, AI‑based proctoring, and blockchain-based credential systems hosted on elastic infrastructure.

By grounding the IaaS use cases in real-life examples, we see how IaaS supports scalable workloads, reduces infrastructure complexity, aligns to regulatory needs, and enables cost‑efficient operations. Whether for big data, disaster recovery, or compute-heavy applications, these cases showcase why IaaS remains a powerful enabler of digital transformation across industries.