What the Cloud Actually Is and Why Companies Pay for It
Cloud computing has become the default answer to a business problem: how to get computing power without owning it. Instead of buying servers, storage and software licences, companies rent IT services over the internet and pay for what they use. MarketScreener's thematic stock screen starts from that premise: firms now need to innovate faster, open new revenue streams and extract more from their data, and cloud infrastructure is the underlying catalyst.
The explanation distinguishes four main service categories. Infrastructure as a Service (IaaS) lets a business rent raw infrastructure—servers, storage and networking—on a usage-based fee. Platform as a Service (PaaS) gives developers an on-demand environment to build, test and deploy applications without managing the underlying servers. Software as a Service (SaaS) delivers finished applications over the internet, usually by subscription, with the provider handling maintenance, upgrades and security patches. Serverless computing overlaps with PaaS but removes even more day-to-day server management.
The practical trade-off is the same across models: companies shift capital and IT-operations effort to a provider-run data centre and redirect internal resources toward more strategic work. The article also distinguishes public, private and hybrid deployment—public clouds being operated by third-party providers, private clouds being reserved for a single organisation, and hybrid combining both through data-sharing technology.
What a Fundamental Screen of 100 Cloud Names Does and Doesn't Tell Investors
Why the Screen's Criteria Matter More Than the Cloud Story
The MarketScreener list is limited to 100 companies selected by fundamental criteria and market-capitalisation filters. That is a screening statement, not a performance claim: it narrows a universe, but the article does not disclose the specific financial metrics or weightings used. For investors, the practical value is therefore organisational—it frames cloud exposure as a universe to filter, not a list of endorsed names.
The Four Service Models Do Not Carry the Same Economics
The distinction between IaaS, PaaS, SaaS and serverless is not academic. IaaS revenue tends to be capacity-driven and usage-based; SaaS revenue is often subscription-based and sticky; PaaS sits between them, tied to developer workflows; serverless removes server management but still bills on consumption. Since the screen is built on fundamentals, a company's place in this stack will shape its revenue visibility, capital intensity and margin profile—an analytical lens the article invites but does not itself apply to individual names.
Deployment Choice Adds a Second Dimension of Risk
Public, private and hybrid clouds differ in control, cost structure and data-residency implications. A company whose product depends on public-cloud infrastructure carries different operating leverage from one selling software into private or hybrid environments. The article's taxonomy therefore helps an investor ask sharper questions about how much of a company's cloud revenue is recurring, usage-dependent or tied to its own data centres, even though the piece stops short of answering those questions for any specific company.
Using the Service-Model Lens Before Scanning Cloud Stocks
For investors scanning the sector, the clearest use of this piece is definitional:
- Use the four service models—IaaS, PaaS, SaaS and serverless—as a checklist before any cloud stock screen, because the article's own selection process starts from fundamentals rather than from a single cloud narrative.
- When you see a "cloud" name being promoted, ask which of the four models generates most of its revenue and whether that revenue is usage-based or subscription-based; the article's taxonomy, not its headline, is the practical filter to apply.
Do not read the 100-company reference as a published recommendation: the underlying list, its criteria and any individual names are not disclosed in this piece, so its investment value is limited to the classification framework.
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