Updated October 2026 with 2026 survey data on cloud spending and hybrid setups, a section on where AI changes the decision, and an FAQ.
Summary: Cloud computing helps software teams scale on demand, keep applications available, and skip the up-front hardware purchase. The trade-offs in 2026 are spending that’s hard to predict and new questions about where data and AI workloads should run, which is why 73% of organizations in Flexera’s 2026 cloud survey run a hybrid setup.
Cloud computing has changed the way software is developed, deployed, and managed, giving businesses the ability to build and launch applications that can handle the demands of modern users. With its three primary benefits of scalability, reliability, and cost savings, cloud computing has made it easier than ever for businesses to develop software quickly and efficiently.
This article explores how cloud computing can benefit software development, where it falls short, and how companies decide which applications belong in the cloud. The ability to scale resources up or down on demand, the highly available and fault-tolerant infrastructure, and the pay-as-you-go pricing model have made software development faster and, for many workloads, cheaper.
Accessibility also means reducing cloud costs while improving resource management and support, so businesses can get more out of their IT budgets.
Scalability
Scalability is one of the primary benefits of cloud computing for software development.
With traditional software development, scaling was a significant challenge, as developers had to predict the workload and design their systems to handle it. This time-consuming approach often meant paying for servers that sat idle most of the year.
With cloud computing, businesses can scale their resources up or down as needed, based on the current demand. Cloud providers offer highly scalable infrastructure and services that can be provisioned on demand, ensuring that companies have the necessary resources when needed.
This approach enables developers to focus on building the application rather than managing the infrastructure, making the development process more efficient and cost-effective.
For example, a business that experiences a sudden increase in website traffic can use auto-scaling to automatically adjust the resources based on that demand. It keeps the application running well regardless of the workload. Once the traffic subsides, the resources can be scaled back down, allowing the company to cut costs.
Reliability
Reliability is another benefit of cloud computing for software development. With traditional software development, high availability and handling failover scenarios were notable challenges that required a lot of expertise and resources.
Cloud providers deliver highly available and fault-tolerant infrastructure and services, making it easier for businesses to ensure the reliability of their applications. The cloud also offers tools for monitoring and managing applications, so developers can detect and resolve issues quickly and keep the application available.
For example, an organization can use application performance monitoring to detect and resolve performance issues before they affect users. This helps keep the application available and provides a positive user experience.
Cost Savings
For business owners, cost savings are at the top of the list of their favorite topics to discuss. Cloud computing for software development belongs in this conversation, as it can save companies heaps of money by providing them with reliable and flexible solutions.
Without such tools, businesses have to make significant upfront investments in infrastructure and hardware, which means high costs and the risk of buying more capacity than they use.
On the other hand, with cloud computing, enterprises only pay for the resources they use. Many cloud providers offer a pay-as-you-go model. Thanks to it, companies can scale their resources up or down based on demand, saving money and lowering the risk of over-provisioning.
Additionally, cloud providers usually offer discounts for long-term usage, reducing costs even further.
Cloud providers also have tools for optimizing resource usage, helping businesses identify and eliminate wasteful spending. For example, an enterprise can use cost optimization tools to identify idle resources and terminate them, saving money.
Other Benefits
Cloud computing brings other benefits to software development beyond scalability, reliability, and cost savings. These include flexibility, security, collaboration, and accessibility.
Flexibility refers to the ability of developers to choose tools suitable for their needs and deploy applications in the best way possible. With cloud providers offering a variety of services and deployment models, businesses can adapt quickly to changing market conditions.
Security is another advantage of cloud computing, with built-in security features, dedicated security teams, and compliance with regulatory requirements protecting applications and data from cyberattacks.
Collaboration matters when a development team works from different places. Cloud services let developers share code and work on the same project in real time, wherever they are.
Finally, accessibility makes software development possible for businesses of all sizes. With cloud-based tools and services, companies can build and deploy software applications quickly, regardless of their size or technical expertise.
What the Cloud Does Well
Cloud computing has made software development faster, more efficient, and more cost-effective for many workloads. It gives organizations of all sizes a scalable way to build and deploy applications.
The ability to scale resources up or down on demand, the highly available and fault-tolerant infrastructure, and the pay-as-you-go model have opened up new possibilities for businesses looking to develop software applications quickly.
Where the Cloud Pitch Falls Short in 2026
Those benefits come with a monthly bill that’s hard to predict. In Flexera’s 2026 State of the Cloud survey of more than 750 cloud decision-makers and users, 85% said managing cloud spend is still a top challenge, and wasted cloud spend rose to 29%, its first increase in five years. Flexera links that rise to the surge in cloud-based AI workloads.
Pay-as-you-go pricing works well for workloads that spike and drop. It works less well for an order-entry app or a reporting portal that runs the same way every day. In an analysis of AI infrastructure costs, Deloitte found that on-premises deployment may become more economical than cloud services for consistent, high-volume workloads once cloud costs pass 60% to 70% of the total cost of buying equivalent on-premises systems.
That’s why most companies don’t pick one side. In the same Flexera survey, 73% of organizations run hybrid environments, with some applications in a public cloud and others on servers they control. For the companies moving some workloads back in-house, we covered the reasons in what’s driving cloud repatriation in 2026.
These questions usually decide where an application should run:
- Where does the data live? An app that reads a database in your data center all day will be slower and harder to secure if the app runs in a cloud region and the data doesn’t.
- Is the workload steady or spiky? A seasonal web store or a quarter-end batch job suits pay-as-you-go. An app that 200 people use every weekday often costs less on servers you already own.
- What do regulators and customers require? Contracts in healthcare, finance, government and manufacturing often spell out where data can be stored.
- How hard is it to move later? If a development platform only runs in its vendor’s cloud, bringing an app back in-house means rebuilding it.
AI Adds a Data Question
AI adds a new question to the cloud decision: Where does the data go when an AI model reads it? Flexera found that 53% of cloud leaders name security and compliance as their top challenge for cloud-based AI projects.
When an employee pastes a customer list into a public chatbot, nobody in IT knows it happened. When IT builds the AI tool, IT decides which tables it can read, who can use it, and which AI model it sends questions to.
Where m-Power Fits
m-Power is mrc’s low-code development platform. It builds web applications, reports, and AI tools over the databases you already run, and it installs where you choose: On your own Windows, Linux, or IBM i servers, or in a private cloud account you control. It connects over JDBC to databases such as SQL Server, Oracle, MySQL, PostgreSQL, and IBM i (Db2), and it generates standard HTML, JavaScript, and Java that runs on a standard application server.
For AI tools, the same rules apply as for every other m-Power app. IT controls what data the AI can access, who can use each tool, and which model it calls. And because the license is perpetual, with no per-user fees, adding users doesn’t change the cost, wherever the applications run.
“I can now do five projects in the time that I would have done one,” said Roisin Bowen of Autochair.
If you’re deciding where your next round of applications should run, request a demo and we’ll walk through how m-Power would run in your environment.
Frequently asked questions
Is cloud computing always cheaper than on-premises?
Not always. The cloud removes the up-front hardware purchase, but monthly fees add up. For steady, predictable workloads, owning the servers can cost less over several years, and Deloitte puts the tipping point at cloud costs of 60% to 70% of the cost of equivalent on-premises systems. Work out the total cost for your own workloads before you decide.
What is a hybrid cloud approach to software development?
Some applications run in a public cloud and others run on servers you control, usually chosen app by app based on where the data lives, how steady the workload is, and what compliance requires. In Flexera’s 2026 survey, 73% of organizations run hybrid environments.
What are the main risks of cloud computing for software development?
Costs that are hard to predict, dependence on one provider’s services, slower performance when an app and its data sit in different places, and less control over where data is stored. In Flexera’s 2026 survey, 85% of organizations named managing cloud spend as a top challenge.
How does AI change the cloud decision?
AI tools need data to be useful, so the question becomes which data the AI can read and where that data is sent. When IT builds AI tools on its own platform, IT can set which tables each tool reads, who can use it, and which AI model it calls.