Updated in April 2026
While the infrastructure and computing resources that run today’s businesses, such as storage, hardware, servers, and networking components, are critical, they are often underrated when it comes to being ranked as business priorities. That’s because, although the infrastructure is expected to perform predictably and reliably to support the business, it isn’t necessarily viewed as a differentiator that delivers a competitive advantage. This belief, however, is far from the truth. In fact, today’s industry leaders are turning to infrastructure and infrastructure services to help them drive efficiencies and power digital transformation across their businesses.
One way they are doing this is by utilizing the Infrastructure-as-a-Service (IaaS) model. IaaS is a cloud computing model where an organization outsources the fundamental infrastructure equipment used to support operations, i.e., storage, hardware, servers, and networking components, and access to computing resources is delivered through a virtualized, cloud-based environment. This creates a joint delivery model where organizations own “up stack” from the virtual machine, but everything required to run that virtual machine is managed and maintained by someone else.
According to Gartner, worldwide sovereign cloud infrastructure as a service (IaaS) spending is forecast to total $80 billion in 2026, a 35.6% increase from 2025. Not only that, but the market is also dominated by big players. Studies report 66% of the IaaS market is served by AWS (Amazon Web Services) at 28-30% share, Microsoft Azure at 20-21% share, and Google Cloud with a growing share at 14%.
With IaaS, instead of purchasing hardware outright, users access virtualized computing resources over the internet, with the flexibility to scale up and down resources as circumstances and priorities change.
IaaS delivery options include the public cloud, private cloud, hybrid cloud, or a multi-cloud model. More companies are turning to a hybrid cloud or a multi-cloud approach to strike the optimal balance between cost and flexibility, enabling them to move workloads between private and public infrastructure as needed.
Benefits of IaaS are the reduction of hardware infrastructure costs coupled with greater flexibility and business agility, with pay-as-you-go pricing models that let users pay only for the services they consume. Because businesses can spin up resources quickly, developers are also free to run temporary workloads, test new applications, or prepare for seasonal traffic spikes.
| Key Benefits of IaaS | |
| Flexible cost model |
|
| Scalability and agility |
|
| Hybrid and multi-cloud options |
|
| Resilience and security foundation |
|
Ready to get more out of your technology while saving money? Bluewave can help.
A successful IaaS strategy can help companies focus on business growth and on meeting business-critical objectives. Let’s take a closer look at the best use cases for adopting IaaS:
In addition to providing day-to-day computing resources, IaaS allows users to layer a wide range of services on top of the infrastructure. That might include computing-as-a-service, disaster recovery-as-a-service, analytics or BI-as-a-service, and more.
Example scenario
A SaaS company running its core applications on IaaS wanted to add advanced analytics and stronger recovery capabilities without rebuilding its stack. Working with its cloud provider, the team layered on analytics-as-a-service to pull data from production databases into a managed BI environment, and added disaster-recovery-as-a-service to protect key workloads in a secondary region.
Both services run on top of the existing IaaS footprint, so the company gains richer reporting and a tested failover option without standing up new infrastructure or distracting internal teams from product work.
Managing, storing, and analyzing massive amounts of data, both structured (i.e., databases) and unstructured (i.e., social media, images, web, emails, Internet of Things (IoT) sensors), requires tremendous processing power. AI and ML analytics, especially, require way more than basic cloud computing and servers. IaaS is a perfect environment to manage these workloads, and with the rise of AI-optimized IaaS, you can tap into powerful GPUs, high-speed networks, and scalable storage that are built for heavy data processing and real-time inference. That makes it a strong foundation for big data and AI workloads, and turns raw data into insights that help uncover trends earlier.
Example scenario
A global shipping company was paying steep demurrage fees every time bad weather threw their schedules off. The company sets up an AI-optimized IaaS environment with a cloud data lake that ingests weather and sea conditions, AIS signals, voyage plans, and satellite data.
Several deep learning models were trained on this data and deployed using a serverless architecture running on top of IaaS, allowing the company to predict ship arrival times to within minutes in near real time. This allows for fewer delays and sharply reduces demurrage charges, all powered by scalable cloud infrastructure built for big data and AI workloads.
With a robust, scalable infrastructure layer, organizations can consolidate their disparate disaster recovery systems into a single virtualized environment. This diversification of the backup systems gives businesses peace of mind knowing that their data is secure.
Example scenario
A large grocery chain with more than 800 stores across the U.S. needs to exit its mixed, aging on-prem environment and meet an imminent deadline to move to the cloud.
The company migrated its core IT operations into a hosted private cloud that includes integrated firewall and disaster recovery capabilities. Instead of juggling separate DR tools by site, the chain now relies on a single, virtualized environment to protect critical systems and data. In the event of an outage at the primary location, workloads can fail over to the hosted environment, helping keep stores online while reducing risk and simplifying ongoing recovery testing.
The computing and networking power behind IaaS makes it a perfect place to run and manage testing and development cycles. With SLAs in place from providers and a high-level of security, enterprises can trust IaaS to run business-critical projects and get to market faster with a higher scalability of computing resources.
Example scenario
A software team building a new customer portal uses IaaS to create short-lived test environments for each major feature branch. Environments spin up automatically from templates, run automated tests, then shut down. The team ships faster, without IT scrambling to find capacity.
Because the network continues to grow in complexity, many are turning to IaaS service providers to deliver networking-as-a-service support. This may be for a short-term big data project or to support ongoing initiatives, freeing up internal IT staff for other priorities.
When deciding to move infrastructure to the cloud and evaluating service providers, look for those that match business requirements such as expertise, availability guarantees, price, and security certifications. Those vendors that deliver 24/7 support and make it easy to move workloads to and from the cloud environment can help businesses improve efficiencies and differentiate themselves from the competition.
Example scenario
A rapidly growing professional services firm was struggling to manage VPNs, firewalls, and site-to-site connections across dozens of offices and multiple clouds. Instead of expanding its small network team, the firm partnered with an IaaS provider that offered networking-as-a-service, including managed virtual WAN, load balancers, and secure connectivity into each major cloud.
The provider now handles 24/7 monitoring, routing optimization, and policy updates, while making it easy to spin up new sites or shift workloads between regions. Internal IT can focus on security and application projects, knowing the underlying network is resilient, supported, and aligned with SLAs.
This is one of the most common cloud infrastructure use cases for IaaS and a major opportunity to rationalize your environment. In many cases, a lift-and-shift migration into IaaS is the fastest way to exit or consolidate aging data centers and avoid large hardware refresh investments. It also lets you shrink your physical footprint while you plan deeper modernization on your own timeline.
In a lift-and-shift model, organization and move virtual machines as they are, with minimal code changes, and recreate network and security controls in the cloud. It also creates the opportunity to stabilize workloads, then decide which ones to refactor to PaaS or SaaS.
Example scenario
A global media measurement company needs to expand beyond the footprint of its existing AWS environment while bringing spiraling egress costs under control.
With the help of an advisor, they execute a lift-and-shift migration from AWS to Akamai Connected Cloud, moving more than a thousand GBs of compute and over 2,500 TBs of egress traffic into a distributed edge infrastructure.
By largely rehosting workloads as they were and recreating the necessary network and security policies, the team avoided a risky full rebuild, improved global coverage and performance for latency-sensitive services, and significantly reduced ongoing cloud spend.
While IaaS has its place in a cloud computing strategy, it is far from the only tool organizations have.
Software-as-a-Service (SaaS) applications are the most recognized cloud-based IT services category, and they include popular applications like Salesforce, MS Dynamics, or Workday. A Platform-as-a-Service (PaaS) example would be a development platform that is used to build and run applications in the cloud. This might be comprised of application servers or database management systems.
Each model moves the demarcation of control to a different point in the computing stack, so it’s important to map the right as-a-service approach to the right business needs and align them with the right IT operations strategy.
Choosing between IaaS, PaaS, and SaaS essentially boils down to how much control you require and how much infrastructure you and your team can manage.
You can think of this as a spectrum of control vs convenience. IaaS gives you the most control, SaaS gives you the most convenience, while PaaS sits somewhere in the middle. Most organizations use a combination of all three.
IaaS is a great tool and option, but it might not necessarily be the right answer for every workload. It’s extremely effective in situations where you might need a lot of control over operating systems and configurations, or when your applications aren’t ready for PaaS or SaaS, or if you are trying to move into the cloud fast and need to modernize in phases. It’s also a good fit when you have specific compliance or performance requirements that demand carefully designed architecture.
In other situations, IaaS can be overkill, causing more issues and complexity than it solves. For example, do you have a mature SaaS product that covers your needs?
If you do, then that requires way less operational overhead, especially if your team doesn’t have the time to handle OS patching and hardening. Additionally, if a workload is simple or highly event-driven, it can run efficiently on serverless or PaaS, sometimes even more so than on an IaaS solution. Often, modern strategies leverage a blend of IaaS, PaaS, SaaS, as well as on-prem. This way, each application can be matched to the platform that fits best.
In order to have a successful cloud infrastructure strategy, organizations need to ensure their technology choices are properly aligned with business goals and team capabilities.
At Bluewave, we act as an independent advisor and partner that helps you to:
If you aren’t sure where to start or want an objective view of your options, we can help!
Next step: Request a conversation with one of our advisors to evaluate your IaaS strategy and design a cloud infrastructure roadmap that works for your business.
A: IaaS gives you virtualized infrastructure. PaaS gives you a managed application platform. SaaS gives you a complete application. As you move from IaaS to SaaS, you manage less of the stack and gain more convenience, but also give up some control.
A: IaaS is ideal when you need control over infrastructure, want to migrate existing workloads quickly, or have applications that aren’t ready for PaaS or SaaS. It is also a strong foundation for DR, dev/test, and big data workloads.
A: The market is led by large public cloud providers that offer compute, storage, and networking services, along with many supporting tools for security, analytics, and operations.
A: It can be, but it isn’t automatic. Savings depend on right-sizing resources, turning off what you don’t use, and applying strong cost management practices. Many organizations see better value when they combine IaaS with FinOps and a clear workload strategy.
A: IaaS provides scalable compute and storage that can be paired with managed AI, ML, and analytics services. You can burst compute for training runs, store large datasets, and integrate with higher-level tools without building the underlying infrastructure yourself.
© 2026 Bluewave Technology Group, LLC. All rights reserved.