6 Key Challenges in Adopting a Cloud Operating Model

Moving to the cloud isn’t just about swapping on-prem servers for cloud infrastructure; it's a total transformation of how businesses function. This is where a cloud operating model comes in.

Consider it the strategy for how your teams will deploy, manage, and secure cloud resources. It outlines roles and responsibilities, scalability methods, cost management, and security protocols. Without a well-defined cloud operating model, companies often encounter escalating costs, security vulnerabilities, compliance issues, and a lack of insight into their cloud environments.

So, what’s standing in the way? Let’s break down the biggest challenges in adopting a cloud operating model—and, more importantly, how to manage them.

Top 6 Challenges in Adopting a Cloud Operating Model

Here are the six major challenges organizations usually face in adopting a cloud operating model, and how can they manage them effectively:

1. Security and Compliance

Maintaining the security of your data while ensuring compliance with industry regulations is one of the major challenges businesses face when moving to the cloud. Unlike traditional on-premise setups where organizations have full control over their infrastructure, cloud environments introduce new risks, such as unauthorized access, misconfigurations, and compliance failures.

If not managed effectively, these security risks can lead to data breaches, legal issues, and a loss of customer trust.

What makes it difficult?

• Limited visibility into data storage locations and access permissions.
• Misconfigurations that expose sensitive information.
• Complex compliance requirements (GDPR, HIPAA, SOC 2).

How to address it:

• Adopt a zero-trust security model—verify every access request instead of assuming trust.
• Encrypt data both at rest and in transit to enhance protection.

2. Cloud Costs

Cloud services offer cost efficiency—but only when managed wisely. Many businesses underestimate their cloud consumption, leading to unexpected bills. Unused resources, over-provisioned instances, and lack of budget controls can turn cost savings into a financial headache.

Why is it tricky?

• Pay-as-you-go pricing sounds great—until unmonitored usage spirals out of control.
• Companies often over-allocate resources "just in case".
• Multi-cloud environments make tracking expenses even harder.

How to control costs:

• Use autoscaling and reserved instances to optimize cloud spending.
• Set up budgets and alerts to track usage in real-time.
• Implement FinOps (Financial Operations) to align cloud costs with business goals.
• Regularly review billing dashboards (AWS Cost Explorer, Azure Cost Management) to cut waste.

3. Legacy Systems

Not every application is designed for the cloud. Many businesses still use legacy systems built decades ago, making migration a major challenge. Trying to force-fit old applications into a modern cloud setup can lead to performance issues and operational inefficiencies.

What’s the problem?

• Legacy apps weren’t built for cloud scalability.
• Migrating without modernization can cause downtime and performance lags.
• Poor integration between cloud and on-prem systems.

How to make it work:

• Use a hybrid cloud approach to transition workloads gradually.
• Containerize applications with Docker or Kubernetes to improve portability.
• Introduce APIs and middleware to bridge cloud and legacy systems.
• Adopt a phased migration strategy rather than a complete lift-and-shift.

4. Skill Gaps

The cloud isn’t just a technology shift—it’s a cultural shift. Traditional IT teams may not be ready for cloud automation, DevOps, or microservices, leading to skill gaps that slow down adoption. Without the right expertise, businesses struggle to manage cloud environments efficiently.

Why does this happen?

• Many IT teams are still used to on-prem infrastructure.
• Cloud-native skills (Kubernetes, Terraform, CI/CD) require specialized training.
• Resistance to change—employees may feel threatened by automation.

How to upskill your team:

• Invest in cloud certifications (AWS, Azure, Google Cloud).
• Implement DevOps practices to encourage automation and collaboration.
• Hire cloud architects and engineers or partner with cloud consulting firms.
• Promote a culture of learning through hands-on training and internal cloud boot camps.

5. Governance and Control

When multiple teams deploy cloud resources, things can quickly spiral into chaos. Without proper governance, businesses risk inconsistent security policies, shadow IT, and compliance violations.

Common issues:

• Lack of centralized control over cloud resources.
• Unclear policies on data access, security, and provisioning.
• Teams spinning up services without IT oversight.

How to maintain governance:

• Define a cloud governance framework with clear security and compliance policies.
• Use cloud management platforms to monitor resources across teams.
• Automate policy enforcement with AWS Organizations, Azure Policy, or Google Cloud Resource Manager.
• Regularly audit who has access to what to prevent security loopholes.

6. Performance & Reliability

Cloud downtime isn’t just a minor setback—it can lead to revenue loss, customer dissatisfaction, and operational disruptions. Ensuring that cloud workloads remain available, responsive, and scalable is crucial.

What makes performance a challenge?

• Latency issues in multi-region setups.
• Unoptimized applications consuming too many resources.
• Lack of real-time monitoring to detect issues before they escalate.

How to ensure reliability:

• Distribute workloads across multiple cloud regions and availability zones.
• Use CDNs (Cloudflare, AWS CloudFront, Azure CDN) to improve response times.
• Implement auto-healing mechanisms to detect and fix issues automatically.
• Continuously monitor performance with AWS CloudWatch, Azure Monitor, or Google Operations Suite.

Real-World Example: How a Financial Services Firm Fixed Their Cloud Adoption Issues

A global financial services company faced challenges in adopting a cloud operating model, including security risks, rising costs, and performance bottlenecks after moving to a multi-cloud environment. Their lack of cost tracking, poor governance, and outdated legacy integrations made cloud adoption difficult.

Here’s what they did to turn things around:

• Security Automation: Used AI-driven threat detection to reduce security incidents by 50%.
• Cost Optimization: Identified and shut down unused cloud resources, cutting cloud bills by 35%.
• Hybrid Cloud Strategy: Gradually modernized legacy applications, avoiding costly re-platforming.

Within a year, their cloud efficiency improved by 40%, and compliance issues dropped significantly.

Conclusion

Adopting a cloud operating model is not just a technological innovation, it is a strategic decision. However, challenges such as security risks, budget overruns, limitations of legacy systems, and skill shortages can make this transition intimidating.

The good news? With the right governance, automation, and optimization strategies, these challenges in adopting a cloud operating model can be tackled better.

For businesses facing difficulty managing these cloud complexities, cloud managed services provide the expertise and support needed to optimize their cloud operations and adopt a cloud operating model, without having to go through the hassle of managing everything inhouse.