Infrastructure-as-a-service (IaaS) is a business model in which companies rent fundamental IT resources—such as servers, storage, and networking—on demand instead of owning the physical hardware. The global IaaS market was valued at $154.39 billion in 2024 and is expected to grow to $276.81 billion in 2029.

IaaS pricing refers to how cloud providers charge for these resources. Unlike outright equipment purchases, which involve large up-front costs, IaaS lets companies pay for infrastructure as an ongoing expense. You’re billed for what you use, when you use it​.

Below, we’ll explain IaaS pricing, including its main components, how cloud providers can structure it, the challenges it poses, and how businesses can fine-tune IaaS costs.

What’s in this article?

• What is IaaS pricing?
  
• How do cloud providers structure IaaS pricing?
  
• What are the main cost components in IaaS pricing?
  
• What challenges do businesses face with IaaS pricing?
  
• How can businesses manage IaaS costs?
  

What is IaaS pricing?

If you’re running a business, you almost certainly need computing power, storage, and networking. You could buy the hardware yourself, set up data centers, and hire a team to keep it all running. Or you could rent what you need, when you need it, from a cloud provider. That’s infrastructure-as-a-service (IaaS): computing resources on demand, without the overhead of owning physical infrastructure.

The way the rental pricing model for IaaS is set up, you’re charged based on usage, not a fixed fee. If you need a virtual server for two hours, you pay for two hours. If you want to store 500 gigabytes of data, your bill will reflect that amount of storage. There’s no large up-front investment; there’s just a rolling cost that adjusts to your needs. It’s a shift from capital expense to operating expense.

How IaaS compares to PaaS and SaaS

There are different layers of cloud services, and IaaS is the foundation. Software-as-a-service (SaaS) sits at the top and offers fully built applications (e.g., email services, collaboration tools) with simple, per-user pricing. Platform-as-a-service (PaaS) sits in the middle and gives developers managed environments to build apps without worrying about infrastructure. IaaS is more fundamental because you’re renting raw computing power, not a finished product.

That means IaaS pricing is more granular than SaaS or PaaS pricing. You’re billed for computing cycles, storage, and bandwidth, and each component is priced separately. This model is flexible, but that also means your bill depends on how much you use and how efficiently you use it.

Why businesses choose IaaS

Businesses choose IaaS for cost and flexibility. With traditional infrastructure, business owners often have to guess their future needs, buy hardware in advance, and hope they got it right. If they overestimate their needs, they might have to pay for unused servers, while underestimation might lead to a last-minute rush to add capacity.

IaaS eliminates that guesswork. If you need more power, you can scale up instantly. If you need less, you can scale down and stop paying for what you don’t use. Startups often use IaaS because it lets them begin operations without sinking money into infrastructure. But it’s just as valuable for enterprises that run large, intricate systems because they can expand without needing to buy and manage physical servers.

With IaaS, you can access the latest hardware and global infrastructure without needing to worry about upgrades, security patches, or maintenance. That responsibility lies with the cloud provider.

How do cloud providers structure IaaS pricing?

Cloud providers sell infrastructure by renting it out and metering the computing power, storage, and bandwidth you use. The way they price that service can vary depending on how predictable your needs are and how much flexibility you want. IaaS pricing falls into three main models.

Pay-as-you-go

This is the simplest, most flexible option. You use resources as needed and pay for what you consume—usually billed by the second, minute, or hour. If you operate a virtual machine (VM) for six hours, your bill reflects those six hours. If you store a terabyte of data for a month, you pay for that month.

Pay-as-you-go is ideal for unpredictable workloads, because you can scale up when demand rises and scale down when it drops. But this convenience and availability comes at a premium: pay-as-you-go rates are the highest per-unit cost. Startups, testing environments, and companies with volatile traffic often start here before they fine-tune costs with the other two models.

Reserved instances

If you know you’ll need a certain amount of infrastructure consistently—for example, a database server that runs 24/7—it makes sense to commit up front. Reserved instances let you prepay (in part or in full) for a set capacity over 1–3 years in exchange for steep discounts. For example, Azure’s reserved instances cost significantly less than its pay-as-you-go pricing.

The catch is that you’re paying for that capacity whether you use it or not. This makes reserved instances a good option for stable, predictable workloads. If you’re running core services that won’t be shutting down anytime soon, this is a smart way to lock in a discount.

Spot pricing

Cloud providers generally have extra capacity sitting idle. Instead of letting it go to waste, they sell it at a significant discount. This is called spot pricing (or preemptible instances, depending on the provider).

The trade-off is that there’s no guarantee your instance will keep running. If the cloud provider needs that capacity back, your instance could be shut down with little notice. That makes spot pricing a good fit for batch jobs, background processing, or workloads that can handle interruptions. But it’s risky for anything that requires constant availability, unless you’ve built redundancy into your system.

Mixing and matching for maximum efficiency

Most businesses mix and match models to fulfill their needs. Here’s an example of a typical strategy:

• Use reserved instances for core services that need to be running 24/7.

• Keep some on-demand instances for variable workloads that scale with demand.

• Use spot pricing for cost-sensitive tasks that can tolerate interruptions.

What are the main cost components in IaaS pricing?

IaaS pricing is a running tab on the infrastructure you use. While every cloud provider has its own pricing, most IaaS costs fall into four main categories.

Computing (VMs and processing power)

This is often the biggest expense. Cloud providers charge for VMs or containers, typically by the second, minute, or hour. If you leave a VM running—even if it’s doing nothing—you’re still paying for it. The more central processing unit (CPU) power and memory you need, the higher the cost will be: a small VM might cost pennies per hour, while a high-performance machine equipped with a graphics processing unit (GPU) could cost hundreds of dollars a day. Due to local infrastructure costs, running a server in one cloud region might cost more than it would in another.

Storage (saving data and backups)

Data has to live somewhere, and the way it’s stored affects the price you pay. Cloud providers typically charge per gigabyte per month, but storage comes in different forms:

• Block storage: This is akin to a virtual hard drive. Options include the speedy yet expensive solid-state drives (SSDs) and slower but high-capacity hard disk drives (HDDs).

• Object storage: This is space in the cloud to store files, images, or backups. Prices drop if you move infrequently accessed data to colder storage tiers.

• Snapshots and backups: Every time you take a snapshot of a VM or database, you’re storing a full copy somewhere, for a fee.

Data transfers (bandwidth and network costs)

Moving data into the cloud is usually free. Moving it out can get expensive. Be aware of the following:

• Egress fees apply when you send data from your cloud servers to the public internet (e.g., serving content to users) or between cloud regions.

• Multicloud architectures can get pricey. If you’re moving data between different cloud providers, you’ll probably pay double fees, because one provider charges to send the data out and the other might charge to receive it.

• If you have a high-traffic app or website, using a content delivery network (CDN) can lower costs by caching content closer to users. That reduces the amount of expensive outbound data transfers.

Application programming interface (API) requests and managed services

Many cloud services charge for storage and computing, as well as per request or per operation. Here are some examples:

• Object storage requests: Every time your app retrieves or writes a file, there’s a small fee. If your app makes millions of these requests, the costs can be significant.

• Managed database and serverless functions: These services charge per query, per execution, or per gigabyte processed. They’re known for their ease of use but can quietly drive up costs if you’re not careful.

• Logging and monitoring: Cloud providers charge for collecting and storing logs and metrics. While keeping years of logs might seem harmless, at cloud scale, it can become a serious cost.

What challenges do businesses face with IaaS pricing?

IaaS is flexible and cost-efficient. But for all its benefits, its pricing structure is complicated and costs can accumulate in ways that aren’t always obvious. Here’s where companies encounter issues.

Variable bills

High cloud bills can be a common complaint about IaaS. Unlike traditional IT costs, where infrastructure is a fixed expense, cloud bills are variable. That’s good when you need to scale up, but it also means you can accidentally increase costs, as in these examples:

• A developer starts a large instance for testing and forgets to shut it down.

• A sudden peak in traffic triggers autoscaling, which doubles computing costs overnight.

• Data transfer fees pile up because an application is moving massive amounts of data across regions.

Cost-effective scaling

IaaS makes it easier to scale resource usage up or down in real time, but that can get expensive fast if it isn’t controlled. Below are a few common mistakes:

• Improperly configured autoscaling: If your autoscaling is improperly configured, you can end up using more infrastructure than you actually need.

• Hoarded resources: Many teams overprovision resources just to be safe so they pay for capacity they rarely use. Adding elements is easy but cutting back is harder.

• Ignorance about how each service scales: Some services don’t scale as well as others. While computing scales predictably, API requests, logging, and data transfer fees can increase behind the scenes. If you have this knowledge, you can create a cost-effective management plan.

Regional pricing and compliance costs

Cloud pricing can vary. The same VM might cost more in one region than in another, and compliance requirements can add layers of complexity. The following costs don’t always show up in initial cloud cost estimates, but they can have a big impact on long-term spending:

• Running workloads in Europe or Asia might be more expensive than in the US due to local infrastructure costs.

• If you need to comply with the General Data Protection Regulation (GDPR) or Health Insurance Portability and Accountability Act (HIPAA), you might have to store data in specific regions, even if they aren’t the cheapest options.

• It costs money to transfer data across regions. For example, if you move customer data between Europe and the US, you’ll incur additional egress charges.

Insight into who (or what) is driving costs

One of the hardest parts of managing IaaS costs can be figuring out where the money is going, as seen in the scenarios below:

• If multiple teams share cloud resources without attribution for who uses what, costs can be difficult to track.

• Some expenses, such as API requests and background data processing, don’t always tie directly to a specific service. This makes cost attribution complicated.

• A lack of budget alerts or cost-tracking tools hinders many companies.

How can businesses manage IaaS costs?

With the right strategy, you can control your cloud spending without sacrificing performance. The goal is to ensure that you pay only for what delivers value.

Stop paying for what you don’t use

It’s easy to overprovision cloud resources. Maybe you’re running VMs that are twice as powerful as they need to be, or old instances could be sitting idle but still accumulating charges. Avoid excessive charges by taking these actions:

• Match instances to actual workloads: If your CPU usage is consistently low, you probably don’t need the biggest instance size.

• Turn things off when you’re not using them: Development and testing environments don’t need to run 24/7. Schedule them to shut down outside working hours.

• Consolidate workloads: Instead of running multiple small instances, see if you can merge tasks onto fewer, more effective machines.

Automate scaling (but set limits)

Autoscaling is designed to keep up with demand, but without guardrails, it can spiral out of control. When done right, it can keep performance strong without unnecessary overhead:

• Set upper limits: If your app scales aggressively during high-traffic hours, do not double the infrastructure use when a 20% increase would be sufficient.

• Use scheduled scaling: If you know your traffic peaks at certain hours, scale beforehand instead of reacting to increased loads in real time.

• Scale down, too: Just because demand drops doesn’t mean your infrastructure use will shrink automatically. Ensure you’re scaling down when traffic decreases.

Lock in discounts where they make sense

If you know you’ll need certain resources in the long term, don’t pay full price for them:

• Reserved instances (one- to three-year commitments) can save money compared to on-demand pricing.

• Savings plans let you commit to spending levels rather than specific instances and this gives you more flexibility.

• Spot instances offer big discounts, but they can be interrupted so they’re best for batch jobs or noncritical workloads.

Watch out for hidden costs (especially data transfer fees)

Computing and storage are obvious costs. But data transfer fees—the price of moving data between regions, services, or providers—can be an overlooked expense. Understand how your data moves and remember the following:

• Minimize cross-region data transfers: Keeping workloads in the same cloud region avoids unnecessary egress fees.

• Use CDNs: They cache frequently accessed data closer to users, which reduces outbound data transfer costs.

• Be mindful of multicloud setups: Transferring data between different cloud providers often means paying both sides—one charges to send it, the other to receive it.

Use a cost-monitoring tool

You can’t fix what you don’t measure. Cloud providers have built-in cost dashboards, alerts, and recommendations, but these work only if you use them. Add these tasks to your to-do list:

• Set up spending alerts to be notified when costs peak instead of waiting for the monthly bill.

• Tag resources by team or project so you can track who’s spending what and then hold teams accountable.

• Review cost reports regularly. A simple monthly review can catch unnecessary expenses before they accumulate.