That shift didn’t just affect how companies thought about software; it changed how they thought about infrastructure itself. Instead of building everything in-house, organizations began to look for ways to stay flexible, move faster, and reduce the overhead of managing physical systems. What they found was a different approach to running IT—one that let them tap into computing power and development tools over the internet, without being locked into their own data center walls. The advent of cloud-computing solutions offered that path forward, replacing fixed infrastructure with flexible, on-demand IT in the form of cloud platforms.
No two organizations have the exact same infrastructure requirements or compliance constraints, and the deployment model a business chooses directly affects how it balances performance, security, scalability, and cost. Each model serves a distinct set of needs and comes with its own operational tradeoffs:
A private cloud is a computing environment reserved for a single organization. It can be hosted on-premises in the company’s own data center or managed offsite by a third-party provider. Either way, the key distinction is exclusivity: no other organizations share the infrastructure. This single-tenant setup allows companies to configure the environment to meet specific performance, security, or compliance standards that might not be feasible in a shared system.
Organizations in industries like finance, healthcare, and government often rely on private cloud deployments to satisfy regulatory mandates or internal governance policies. These platforms offer a high degree of control and customization, but those benefits come with significant overhead. In cases of private cloud deployment, the organization itself is often responsible for cloud management—or for maintaining a vendor relationship to handle management duties. Private clouds also tend to lack the on-demand scalability that defines public platforms, making them less agile in rapidly changing environments.
TA public cloud is operated by a third-party provider—such as Amazon Web Services, Microsoft Azure, or Google Cloud—and delivers computing services over the internet to multiple customers. These environments are multi-tenant, meaning resources are shared among users, but isolated at the software level (for security reasons). Public cloud platforms offer access to a wide range of services, including compute power, storage, databases, analytics, and artificial intelligence (AI) tooling, all delivered through a pay-as-you-go mode, platform-as-a-service (PaaS) model.
For many businesses, the public cloud offers the fastest path to scale. Companies can launch workloads in new regions, access high-performance tools, and avoid the upfront cost of buying and managing hardware on-site. It is especially valuable for organizations that experience unpredictable demand or that need to test and launch services quickly. That said, the shared nature of the infrastructure means less control over the physical environment, and costs can become unpredictable if usage is not closely monitored. Organizations also need to be mindful of where data is stored and processed.
A hybrid cloud blends elements of both public and private cloud environments, creating an adaptable infrastructure that allows workloads to move between the two based on specific needs. This model is particularly useful for organizations that want to retain sensitive data or systems on-premises while taking advantage of the public cloud’s scalability for less sensitive functions or peak processing periods. Hybrid deployments often rely on application programming interfaces (APIs), integration platforms, and unified management tools to coordinate systems across environments.
This approach gives companies more flexibility than committing to a single cloud strategy. For instance, a retail business might use a private cloud to store customer payment data for compliance reasons, while running promotional campaigns or analytics in the public cloud to take advantage of elastic resources. The tradeoff is complexity—managing two environments effectively requires a well-defined architecture, skilled staff, and a consistent approach to cyber security, data governance, and orchestration.
Implemented correctly, cloud platforms can deliver a range of clear benefits to businesses, including:
Cloud platforms allow organizations to expand or reduce their use of computing resources based on real-time needs. This is particularly valuable during seasonal spikes or unexpected surges in traffic. For example, a digital learning platform can scale up computer resources during peak enrollment periods and then scale down during academic breaks—all without investing in permanent infrastructure.
Elasticity means being able to allocate resources dynamically as workloads change. A data analytics team might process a large data set overnight, using expanded computing capacity for just a few hours. Once the task is complete, the extra resources are released, and billing returns to baseline. This level of flexibility supports faster experimentation and more cost-effective execution.
By eliminating the need to purchase and maintain physical servers, cloud platforms lower capital expenditures. A financial services firm, for instance, can right-size its infrastructure by only provisioning resources as needed and automatically shutting down idle environments after hours. This not only curbs overspending but also helps teams track and manage cloud expenses more proactively.
With access to global infrastructure and advanced networking, cloud platforms deliver faster response times and lower latency. A streaming service, for instance, can host media libraries in data centers near major viewer populations to ensure faster load times and uninterrupted playback. In traditional environments, delivering that level of performance would require significant hardware investments—in the cloud, it’s really just a matter of selecting the right regions and configurations.
Agility is about moving fast, but more than that it’s about making informed, confident decisions without being bogged down by operational delays. Cloud platforms help unify visibility across environments, allowing IT teams to manage workloads through multiple providers and regions while maintaining a centralized view. This makes it easier to pivot strategies, onboard new tools, or respond to emerging threats.
Provisioning infrastructure in a public cloud can take minutes instead of days or weeks. For DevOps teams, this means spinning up environments for testing, staging, or deployment without waiting for hardware procurement or approvals. This acceleration shortens development cycles and supports more iterative product delivery.
Cloud platforms often include automation tools designed to handle repetitive, low-effort (but still high-value) tasks. A systems administrator, for example, can set up automated job routines to run at specific intervals, freeing up time to focus on more strategic responsibilities. This helps keep teams lean without sacrificing reliability.
Leading cloud providers offer built-in security features like identity management and threat detection. Organizations can configure policies that automatically isolate compromised instances or apply patches when vulnerabilities are detected. For example, a healthcare company might use automated compliance checks to stay ahead of regulatory audits without disrupting day-to-day operations.
Distributed infrastructure helps ensure business continuity even during regional outages or hardware failures. A software vendor might mirror production environments across multiple regions to ensure that if one fails, traffic is redirected instantly—a level of failover and redundancy would be extremely expensive to replicate in a traditional data center.
Cloud platforms support a mobile workforce by allowing employees to access systems from virtually any location. A global consulting firm can equip its teams with secure access to project tools and data regardless of time zone or geography. This supports collaboration and ensures continuity in remote or hybrid work models.
Cloud platforms simplify disaster recovery planning through automated backups and multi-region replication. An accounting firm, for example, might configure backups to run every hour, with copies stored in geographically separate regions. If a primary data center becomes inaccessible, the system can restore operations with minimal downtime and data loss.
Despite the significant benefits, adopting a cloud platform does not automatically eliminate operational complexity. In fact, moving to the cloud introduces some new considerations—some technical, others organizational. These challenges do not impact all organizations in the same way; much depends on whether a business is using private, public, or hybrid models. Public and hybrid clouds typically raise concerns around security and data control, while private clouds can create their own issues related to resource management and scalability. Regardless of the deployment model, understanding and preparing for these risks is a prerequisite for achieving sustainable operations.
Even the most well-established cloud providers occasionally experience service disruptions. Public clouds might face outages due to third-party service disruptions. Private clouds depend on internal infrastructure, which can fail if not properly managed or maintained. Hybrid models inherit risks from both. To minimize disruption, organizations should adopt redundancy strategies, such as multi-region deployments or backup systems, tailored to their specific infrastructure.
Control over data can be a concern in public and hybrid models, where infrastructure is shared or managed externally. Private clouds, while giving more control, can still introduce risks if data governance processes are weak or inconsistently applied. This can create concerns around data residency and regulatory compliance—especially for companies or government agencies and financial institutions, where data needs to reside in specific countries or jurisdictions. Regardless of platform, selecting systems that support granular access control and clear data residency options can help maintain compliance and protect sensitive information.
Security challenges affect every cloud model but can manifest differently. In public clouds, the shared responsibility model means organizations must secure their own workloads while relying on providers for infrastructure security. Private clouds place full security responsibility on internal teams, which can stretch resources. Hybrid environments often complicate compliance, as data and workloads move between environments. Standardizing security policies across all platforms and investing in centralized monitoring can help reduce risk.
Selecting a cloud platform isn’t just a matter of checking feature boxes. The right choice aligns with business priorities, existing infrastructure, and long-term goals. What works for a small dev team prototyping a new product might not suit an enterprise migrating legacy systems. Here are some key considerations to help guide the selection process:
Clarify your business goals
Understand how the cloud will support your strategic objectives. Whether you're looking to modernize legacy applications, support remote teams, or launch digital services faster, your goals should shape your choice of platform.
Prioritize scalability and adaptability
Look for platforms that make it easy to grow—or shrink—your environment without friction. If your business experiences fluctuating demand, elastic infrastructure and usage-based pricing models may be especially valuable.
Check for multi-cloud compatibility
Some organizations prefer to spread workloads across multiple cloud vendors to improve resilience or avoid lock-in. Make sure your platform supports this strategy with open standards, flexible APIs, and integration support.
Evaluate the user experience
A platform that’s technically strong but difficult to navigate can slow down teams. Prioritize interfaces that are intuitive, well-documented, and aligned with how your engineers and IT professionals prefer to work.
Inspect the platform’s security and compliance features
Understand pricing models and return on investment
Assess available support options
Review feedback from other users
Don’t wait until an audit to find out if a platform meets your industry’s requirements. Choose a provider that offers built-in support for relevant standards (like HIPAA, PCI, ISO, or GDPR), along with strong access controls and monitoring tools.
Look beyond headline costs and assess how pricing scales with usage. Look for tools that offer visibility into billing, support budgeting, and help identify underused resources that could be downsized or eliminated.
Strong technical support can make or break your experience, especially when issues arise during deployment or scaling. Consider whether providers offer onboarding, dedicated account managers, or access to solution architects.
Case studies and customer reviews can reveal how the platform performs in real-world scenarios. Look for patterns in the feedback that align with your use case—whether that’s performance under load, support quality, or ease of integration with existing tools.
Planning is critical. Not all applications are equally suited for cloud deployment, and highly customized or tightly coupled systems may require modification before they’re viable in a virtual environment. Many organizations choose to work with managed service providers to guide these efforts, particularly when dealing with legacy modernization or consolidation after mergers. The goal isn’t just to relocate software—it’s to improve how it functions in a more flexible, cloud-optimized setting.
Consistent Governance: The platform ensures consistent governance by allowing organizations to define and enforce policies for cloud resources, validate assets against predefined standards, and correct any deviations. This helps in maintaining compliance and security across the cloud environment.
Real-time Visibility: ITOM provides real-time visibility into cloud assets and their configurations. Teams can track resource migration, assess their cloud environment, and maintain a clear understanding of their resources and configurations.
Policy Automation: The platform automates the enforcement of compliance policies, ensuring that resources are provisioned in alignment with organizational standards and regulatory requirements. This helps in reducing manual errors and ensuring adherence to best practices.
Streamlined Cloud Automation: ITOM Cloud Accelerate offers workflows that streamline cloud automation tasks across the cloud adoption journey. Self-service catalogs and controlled workflows enable teams to provision resources faster, expedite application migration processes, and manage multi-cloud environments efficiently.
Enhanced Application Migration: The platform facilitates assessment, planning, and resource migration tracking, leading to faster and more efficient application migration processes. It empowers teams to navigate the complexities of migration and minimize disruptions to operations.
Resource Provisioning and Management: Organizations can automate resource provisioning using prebuilt service catalog items, validate configurations as they change, and proactively remediate issues to prevent operational disruptions. This ensures that resources are provisioned correctly and are continuously compliant with policies.
Overall, by leveraging the ServiceNow AI Platform® with ITOM Cloud Accelerate, organizations can achieve improved cloud governance, enhanced visibility, efficient automation, and better control over their cloud environments, driving operational excellence and maximizing the benefits of cloud adoption.
Schedule a demo today to see how the ServiceNow AI Platform can help you govern cloud resources efficiently and transform your IT operations with confidence.