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== Factors Influencing Adoption and Suitability of Cloud Computing ==
==Challenges and limitations==▼
The decision to adopt cloud computing or maintain on-premises infrastructure depends on factors such as scalability, cost structure, latency requirements, regulatory constraints, and infrastructure customization. <ref name=":3">{{Cite book |title=Cloud Computing For Dummies |isbn=978-0470484708}}</ref><ref name=":4">{{Cite book |title=Hybrid Cloud for Architects: Build robust hybrid cloud solutions using AWS and OpenStack |isbn=9781788623513}}</ref><ref name=":5">{{Cite book |title=Security Architecture for Hybrid Cloud: A Practical Method for Designing Security Using Zero Trust Principles |isbn=9781098157777}}</ref><ref name=":6">{{Cite book |title=Architecting the Cloud: Design Decisions for Cloud Computing Service Models (SaaS, PaaS, and IaaS) |isbn=978-1118617618}}</ref>
Organizations with variable or unpredictable workloads, limited capital for upfront investments, or a focus on rapid scalability benefit from cloud adoption. Startups, SaaS companies, and e-commerce platforms often prefer the pay-as-you-go operational expenditure (OpEx) model of cloud infrastructure. Additionally, companies prioritizing global accessibility, remote workforce enablement, disaster recovery, and leveraging advanced services such as AI/ML and analytics are well-suited for the cloud. In recent years, some cloud providers have started offering specialized services for high-performance computing and low-latency applications, addressing some use cases previously exclusive to on-premises setups. <ref name=":3" /><ref name=":4" /><ref name=":5" /><ref name=":6" />
On the other hand, organizations with strict regulatory requirements, highly predictable workloads, or reliance on deeply integrated legacy systems may find cloud infrastructure less suitable. Businesses in industries like defense, government, or those handling highly sensitive data often favor on-premises setups for greater control and data sovereignty. Additionally, companies with ultra-low latency requirements, such as high-frequency trading (HFT) firms, rely on custom hardware (e.g., FPGAs) and physical proximity to exchanges, which most cloud providers cannot fully replicate despite recent advancements. Similarly, tech giants like Google, Meta, and Amazon build their own data centers due to economies of scale, predictable workloads, and the ability to customize hardware and network infrastructure for optimal efficiency. However, these companies also use cloud services selectively for certain workloads and applications where it aligns with their operational needs. <ref name=":3" /><ref name=":4" /><ref name=":5" /><ref name=":6" />
In practice, many organizations are increasingly adopting hybrid cloud architectures, combining on-premises infrastructure with cloud services. This approach allows businesses to balance scalability, cost-effectiveness, and control, offering the benefits of both deployment models while mitigating their respective limitations. <ref name=":3" /><ref name=":4" /><ref name=":5" /><ref name=":6" />
▲== Challenges and limitations ==
{{Main|Cloud computing issues}}
One of the main challenges of cloud computing, in comparison to more traditional on-premises computing, is data security and privacy. Cloud users entrust their sensitive data to third-party providers, who may not have adequate measures to protect it from unauthorized access, breaches, or leaks. Cloud users also face compliance risks if they have to adhere to certain regulations or standards regarding data protection, such as [[GDPR]] or [[HIPAA]].<ref name="ttarget">{{cite web|url=https://www.techtarget.com/searchcloudcomputing/tip/Explore-the-pros-and-cons-of-cloud-computing|title=The pros and cons of cloud computing explained|last1=Marko|first1=Kurt|last2=Bigelow|first2=Stephen J.|date=10 Nov 2022|website=TechTarget}}</ref>
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