The public cloud, whether it is platform as a service, infrastructure as a service or software as a service, have all been in the area of growth for over a decade now. The Covid-19 pandemic further hard-pressed the accelerator for this growth by pushing for immediate decisions and actions on the movement towards cloud. Companies are currently investing far more than the traditional IT spending in cloud infrastructure and this is expected to keep growing faster. Very naturally, this led to a high demand for cloud enabled engineers across the globe. More companies are either aggressively rescaling on existing resources or on the lookout for skilled resources in the space. And this demand is only set to grow with time. As per a report from Seen by Indeed, between October 2015 to October 2019, the share of cloud computing jobs, per million, increased by 55 percent and also, it is estimated that India will be set to see more than a million cloud computing job roles by 2022 as per a report by Great Learning.

But then, with this demand also comes the responsibility of understanding what the best ways are to get the right skills or right resources with suitable skills. For the people who are looking at the opportunities in this space, they need to understand what the best skills are that they can have in order to enter this ever-growing industry of cloud with huge number of opportunities.

Some of the things which come along with cloud are not only the technology skills, but companies today recruit and enable people on certain set of technical skills which are required for a resource to be able to be a good cloud engineer. It is also true that most companies are realizing the fact that, with the ever-growing and rapidly changing technologies and cloud environments, the kind of resources that you need to look for or skill for is not only about skilling them on technology but also skilling them on rapid learning. The practice of continuous learning and evolution should become a habit for the resources. So, finding these kind of resources who can skill quickly and understand continuous changes are very much required. Though the demand is there, there Is basically a shortage of this in the present day. So today, companies are actually recruiting and then training resources on these skills and are also ensuring that learning becomes a habit and resources are able to adapt to evolving towards changing technologies in the environment of cloud.

The problem with the industry is that, with the cloud growing, the amount of experienced resources in this space is becoming lower day by day. Most companies are looking at picking up people from infrastructure domain and skilling them on cloud. So, people who are basically into infrastructure and are good with administration of operating systems, web servers and can understand virtualization could be the core people and can benefit from this ever-growing demand of cloud.

In terms of the Indian market space, we project more or less at least 10% of the recruitment demand of the overall recruitment from IT companies is in Cloud and non-IT companies who are in the cloud space will start focusing on recruiting people who are actually cloud enabled and are well versed with either infrastructure or at least understand cloud to certain extent. Colleges and institutes can start adapting a multi cloud culture as most customers today who are using cloud are moving towards hybrid cloud where they use multiple public cloud providers. So, most engineering institutes in the country who usually stick to enabling their students on one specific cloud should very quickly shift their strategy to be able to enable people on multiple public clouds that are available. This is to ensure that the resources are well equipped to handle any of the public cloud offerings that are available in the market today. Or indeed they can at least focus on the top three cloud providers if not all.

What Is Cloud Computing for Business Operations?

At its core, cloud computing for business operations refers to the delivery of IT resources—servers, databases, networking, software, analytics, and intelligence—over the internet. Central remote servers managed by a cloud service provider (CSP) store and process data and applications on behalf of the customer. This model lets business operators scale resources up or down on demand, pay only for what they use, and offload infrastructure management to specialised providers.

The practical benefits driving enterprise adoption include reduced capital expenditure, faster deployment cycles, built-in disaster recovery options, and global availability of services.

Service Model Segments

The cloud computing market for business operations is typically segmented by service model. Each model abstracts a different layer of the traditional IT stack:

• Infrastructure as a Service (IaaS): Provides virtualised compute, storage, and networking resources on demand. Customers manage the operating system and above, while the provider manages the underlying hardware. Examples include Amazon EC2, Microsoft Azure Virtual Machines, and Google Compute Engine.
• Platform as a Service (PaaS): Delivers a managed environment for developing, testing, and deploying applications without managing the underlying infrastructure. Examples include Google App Engine, Azure App Service, and IBM Cloud Foundry.
• Recovery as a Service (RaaS): Also known as Disaster Recovery as a Service (DRaaS), this model replicates and hosts physical or virtual servers in the cloud so that failover can occur quickly after an on-premises outage. It reduces the cost and complexity of maintaining a dedicated DR site.

Deployment Models

Beyond service models, organisations choose how to deploy cloud resources based on their security, compliance, and cost requirements:

• Private Cloud: Infrastructure is dedicated to a single organisation, hosted either on-premises or by a third-party provider. This model gives the greatest control over data sovereignty and compliance but requires significant investment.
• Hybrid Cloud: Combines private and public cloud environments, allowing workloads to move between them as computing needs and costs change. Hybrid architectures are common in regulated industries that must keep sensitive data on-premises while leveraging public cloud elasticity for less sensitive workloads.
• Others: Includes multi-cloud strategies (using services from more than one public cloud provider) and community clouds shared by organisations with common requirements.

Major Vendors in the Market

The competitive landscape spans hyperscale public cloud providers, enterprise software vendors, and specialist infrastructure companies. Prominent players include:

• Amazon Web Services (AWS) – the longest-established hyperscaler with the broadest service catalogue
• Microsoft Azure – strong enterprise integration with the Microsoft ecosystem and a large hybrid cloud portfolio
• Google Cloud Platform (GCP) – competitive in data analytics, machine learning, and Kubernetes-native workloads
• IBM Cloud – focused on enterprise hybrid cloud and AI, especially following its acquisition of Red Hat
• Red Hat – open-source middleware and OpenShift container platform, now part of IBM
• SAP Cloud Platform – targeted at enterprise ERP and business process workloads
• Oracle Cloud – strong in database-as-a-service and enterprise applications
• Salesforce Cloud – dominant in CRM and enterprise SaaS
• VMware – virtualisation and hybrid cloud management, including VMware Cloud on AWS
• Alibaba Cloud – the leading provider in China and a growing competitor in the Asia-Pacific region
• Cisco Systems – networking, security, and collaboration services in the cloud
• ServiceNow – IT service management and workflow automation delivered as SaaS
• Workday – cloud-native HR and financial management applications
• DigitalOcean – developer-focused IaaS with simple pricing and managed databases
• Adobe Cloud – creative and marketing cloud suites
• Kamatera, CloudSigma, HPE Cloud, Verizon Cloud, CenturyLink (now Lumen Technologies) – additional competitors serving enterprise and mid-market segments

Regional Landscape

Cloud adoption rates and dominant providers vary significantly by geography. Understanding regional dynamics is critical for vendors expanding internationally and for enterprises evaluating data residency requirements:

Americas

The United States remains the largest single cloud market globally, driven by mature enterprise IT spend, a concentration of technology companies, and strong demand for digital transformation. Canada, Mexico, and Brazil represent important secondary markets, with Brazil being the largest cloud market in Latin America.

Asia-Pacific (APAC)

APAC is one of the fastest-growing regions for cloud services. China’s market is dominated by Alibaba Cloud, Tencent Cloud, and Huawei Cloud alongside the global hyperscalers operating through local partnerships. Japan, South Korea, India, Southeast Asia, and Australia each present distinct regulatory and competitive environments.

Europe

Europe’s cloud market is shaped heavily by GDPR and data sovereignty concerns. Germany, France, the UK, Italy, Spain, and Russia are the largest markets. The EU’s GAIA-X initiative reflects ongoing efforts to establish European data infrastructure standards independent of US and Chinese hyperscalers.

Middle East & Africa

Adoption in this region is accelerating as hyperscalers open dedicated data centres in the Gulf Cooperation Council (GCC) countries, South Africa, Israel, Turkey, and Egypt. Government modernisation programmes and smart city initiatives are key demand drivers.

Key Market Drivers

• Cost optimisation: Shifting from capital expenditure (CapEx) to operational expenditure (OpEx) reduces upfront hardware investment and enables more predictable budgeting.
• Scalability and agility: Organisations can provision resources in minutes and scale globally without physical hardware procurement cycles.
• Remote work and collaboration: Distributed workforces require cloud-hosted productivity tools and secure remote access to applications.
• Digital transformation: Cloud platforms underpin modern application development practices such as DevOps, CI/CD, microservices, and serverless computing.
• Data and AI workloads: Managed machine learning and big data services lower the barrier to entry for AI-driven business operations.

Challenges and Risks

• Security and compliance: Storing sensitive data with a third-party provider introduces shared-responsibility security models that organisations must understand and manage actively.
• Vendor lock-in: Proprietary managed services can make it difficult and expensive to migrate between providers.
• Cost management: Without proper governance, cloud spend can grow rapidly and unexpectedly—a discipline now known as FinOps addresses this challenge.
• Latency and connectivity: Workloads requiring ultra-low latency may not be suited to centralised cloud regions, driving interest in edge computing.
• Regulatory constraints: Data localisation laws in countries such as Russia, China, and India can restrict where data may be stored and processed.

Emerging Trends

• Multi-cloud and hybrid cloud: Enterprises increasingly distribute workloads across two or more providers to avoid lock-in and improve resilience.
• Serverless and containers: Kubernetes and serverless platforms abstract infrastructure management further, letting teams focus entirely on application logic.
• AI and ML as cloud services: Pre-trained model APIs and managed ML pipelines are making artificial intelligence accessible without specialised hardware expertise.
• Edge computing: Extending cloud services to the network edge reduces latency for IoT, manufacturing, and retail use cases.
• Cloud-native security (CNAPP): Integrated security posture management tools are converging to address the complexity of protecting multi-cloud environments.

Summary

Cloud computing for business operations encompasses a broad and competitive market spanning infrastructure, platform, and recovery services. For DevOps and platform engineering teams, understanding the segmentation by service model, deployment type, and regional dynamics is essential when making architecture and vendor decisions. The market continues to evolve rapidly, with multi-cloud, AI integration, and edge computing defining the next wave of enterprise adoption.

Note: Market size figures and CAGR projections referenced in the original source report (via ReportOcean, 2019) were not independently verified and are not reproduced here. Readers requiring current market size data should consult up-to-date research from Gartner, IDC, or Synergy Research Group.