Cloud migration challenges affect 50% of organizations, with projects either failing or stalling completely. Though moving data and applications to cloud infrastructure offers significant benefits, 44% of CIOs approach this transition with insufficient planning. Organizations that successfully migrate at least 60% of their IT systems to the cloud can increase profits by up to 11.2% year over year. In this article, we'll explore the five major technical challenges in cloud migration and provide practical solutions to overcome them.

Challenge 1: Data Security and Compliance Risks

Data security represents one of the most significant cloud migration challenges faced by organizations today. The number of data breaches nearly tripled between 2020 and 2023 in the United States, making security concerns more pressing than ever. Furthermore, according to IBM's Cost of a Data Breach Report 2023, the financial impact of data breaches has been rising steadily, including a 15% increase in the last three years. Let's examine why security risks intensify during cloud migration and how to address them effectively.

Why cloud migration increases security exposure

Moving to the cloud fundamentally changes your security landscape. The cloud operates on a shared responsibility model, meaning while providers maintain security certifications, many security responsibilities still fall on your team. Essentially, cloud providers secure the infrastructure, but you remain responsible for protecting your data.

During migration, your digital assets become particularly vulnerable. By its nature, cloud migration involves transferring data, services, databases, and applications either wholly or partially to distributed servers accessed over the internet. This transfer process inherently increases risk exposure as your data becomes accessible remotely.

One critical vulnerability comes from storage misconfiguration. Recently, an Amazon S3 bucket containing 3TB of data, including airport employee records across Colombia and Peru, was left unprotected and exposed over one million files online. Such incidents highlight how easy it is for sensitive information to become compromised during transition periods.

Additionally, the management interfaces used to control cloud resources become attractive targets for attackers. These interfaces, like all software, may contain vulnerabilities including remote access and browser weaknesses. Consequently, without proper security protocols, these entry points provide opportunities for unauthorized access.

Internal threats also increase during migration periods. According to a Verizon Data Breach Investigations Report, "20 percent of all cybersecurity incidents and nearly 15 percent of all data breaches" involved insider and privilege misuse patterns. A Fortinet study found that 56 percent of respondents believe that the "shift to cloud computing is making the detection of insider attacks more difficult".

Common compliance pitfalls (GDPR, HIPAA)

Regulatory compliance becomes more complex in cloud environments, creating additional challenges during migration. Organizations often confront unfamiliar sets of regulatory requirements, yet receive no grace period to settle into their new IT ecosystem.

For GDPR compliance, organizations that store and process EU residents' personal data must adhere to specific protocols regardless of where the organization is based:

• Obtain explicit consent from users to collect and process their data
• Implement robust data protection standards
• Ensure data portability and deletion capabilities
• Report any data breaches within 72 hours

Similarly, HIPAA compliance requires healthcare organizations to implement specific safeguards:

• Establish strict access controls to prevent unauthorized data access
• Conduct regular risk assessments
• Maintain comprehensive logging for audit trails
• Properly dispose of electronic protected health information (ePHI)

The penalties for non-compliance are severe. In 2021, the Luxembourg National Commission for Data Protection fined Amazon $887 million for data privacy failures. Similarly, when Equifax failed to patch a vulnerability in 2017, exposing information of 150,000 individuals, they were fined $575 million by the Federal Trade Commission.

Another often overlooked compliance challenge involves jurisdiction and data sovereignty. When information is stored in cloud data centers, it becomes subject to the privacy laws and data disclosure regulations of those jurisdictions. Moreover, should a cloud provider be subpoenaed for a client's data, multiple cloud users can be affected, especially if hardware is part of the subpoena.

How to secure data in transit and at rest

Protecting data during cloud migration requires comprehensive security strategies for both data in transit (moving between systems) and at rest (stored in the cloud).

For data in transit:

Encryption serves as your first line of defense. When data moves between on-premises systems and cloud environments, it becomes vulnerable to interception by malicious actors. Implement end-to-end encryption using industry-standard algorithms like AES-256 to make your data unreadable even if intercepted.

Secure transfer methods are equally important. The most preferred approach is using an encrypted tunnel, which ensures data protection during transit and prevents interception. Additionally, employing SSL/TLS encryption for all communications provides an essential security layer.

For organizations using AWS, services like AWS PrivateLink create secure and private network connections between Amazon Virtual Private Cloud (Amazon VPC) or on-premises locations to hosted services. This approach eliminates the need for internet gateways or NAT configurations while maintaining compliance with industry-specific regulations such as HIPAA.

Google Cloud similarly encrypts customer data in transit within its networks. Their approach includes authenticating all traffic between VMs using security tokens to prevent compromised hosts from spoofing packets on the network.

For data at rest:

Once your data resides in the cloud, continued protection is essential. Many cloud providers offer encryption options for data at rest, but consider managing your own encryption keys for enhanced control over data security. Implement strong encryption of data at rest in the cloud and store trade secrets and other company IP locally to mitigate unauthorized disclosure risks.

Access controls represent another critical component of your security strategy. Implement role-based access controls (RBAC) and two-factor authentication for added protection. These measures help prevent unauthorized access and limit exposure if credentials are compromised.

Regular security audits and continuous monitoring should be standard practice. Deploy data loss prevention (DLP) solutions to safeguard sensitive information, monitoring and preventing unauthorized data exfiltration attempts. These tools can detect and block unauthorized cloud storage uploads of confidential data.

Prior to migration, conducting a comprehensive inventory of your digital assets is crucial. Map out dependencies to recognize potential security threats and classify data sensitivity levels to determine appropriate security controls. This assessment should inform which workloads require enhanced protection or might need to remain on-premises for regulatory reasons.

Disabling firewalls during data transit creates major vulnerabilities, even if only temporarily. Instead, use network security controls and encrypted network protocols that prevent third-party interception of sensitive data.

The cloud migration process presents significant security challenges, but with proper planning and implementation of robust security measures, organizations can safely transition their operations while maintaining data integrity and compliance.

Challenge 2: Cost Overruns and Budgeting Issues

Cost management represents a formidable challenge in cloud migration journeys. A staggering 70% of companies have incurred cloud costs significantly higher than initially anticipated. In fact, cloud spending challenges have now surpassed security as the foremost cloud challenge for the first time. Let's examine the financial pitfalls that organizations face during migration and how to effectively manage them.

Hidden costs in cloud migration

Many organizations experience dramatic budget overruns when moving to the cloud. A recent study found that 38% of projects involving data migration to the cloud fail completely. Meanwhile, 40% of companies fail to keep their cloud costs under control, with 33% finding their cloud budget overrun by 40%.

Several factors contribute to these unexpected expenses:

• Inefficient planning: Without thorough cost analysis and control strategies, organizations often underestimate the complexity of migration.
• Technical challenges: Incompatibility between legacy systems and cloud environments can slow down migration, thereby increasing costs.
• Skill gaps: Approximately 95% of IT leaders report being adversely impacted by cloud skills gaps, forcing companies to either hire expensive technical resources or invest in upskilling existing staff.
• Overlapping services: During migration, organizations typically run services both in the cloud and on-premises simultaneously. This "double-dipping" can persist for weeks or months until the cutover is complete, creating significant duplicate expenses.
• Data transfer costs: Hyperscalers charge networking fees for moving data across the public internet. Depending on the amount of data being transferred, this can become both expensive and time-consuming.
• Transformation costs: These include expenses related to reskilling existing teams, raising salaries to match market levels for cloud roles, changing organizational structure, and adopting agile DevOps practices.

First, migration methods impact costs substantially. Organizations typically choose between two approaches: The "Big Bang" approach involves extracting and processing data from the source system and loading it into the target system all at once. Although fast, this method often results in extended downtime periods, increasing migration costs. Conversely, the "Trickle" approach migrates data incrementally, eliminating downtime but extending the overall migration timeline and potentially raising costs.

Beyond technical expenses, McKinsey predicts that organizations will lose over USD 100 billion in wasted spending over the next three years due to inefficient cloud migration. In the same period, shareholder value could be reduced by USD 500 billion due to costs associated with moving workloads to the cloud.

How to estimate total cost of ownership

Calculating the total cost of ownership (TCO) for cloud migration requires a comprehensive approach that goes beyond simple hardware comparisons. Unfortunately, many organizations make the mistake of performing only an apples-to-apples comparison of on-premises versus cloud costs, which fails to capture hidden expenses and intangible benefits.

To accurately calculate cloud TCO, consider these essential factors:

Current infrastructure assessment: Begin by determining what you're actually paying for your current IT infrastructure. This includes hardware and infrastructure costs, datacenter expenses (cooling, power, space), software licensing, personnel, disaster recovery systems, maintenance, upgrades, and security. For instance, companies often fail to account for indirect costs such as downtime and decreased productivity.

Cloud infrastructure costs: Next, estimate the expenses associated with your future cloud environment. According to AWS, the total platform cost includes container registry costs, container orchestration costs, compute costs (with storage), and tools costs. Remember that cloud pricing typically follows a pay-as-you-go model, making budgeting more predictable but requiring vigilant monitoring.

Migration expenses: These costs vary based on your chosen migration approach. Gartner identifies five migration methods: rehosting (lift-and-shift), refactoring, revising (modifying code), rebuilding (rearchitecting), and replacing with SaaS. Each method carries different cost implications that should be factored into your TCO calculation.

Transformation and residual costs: Often overlooked, these include reskilling costs, organizational changes, and adapting to new operational procedures. Residual costs encompass losses in productivity from vacated facilities and hardware, unused software licenses, and the expense of running duplicate systems during migration.

TCO calculation methods vary depending on available data and the time you're willing to invest in analysis. For public sector organizations, AWS offers the Government Workload Assessment (GWA), which helps plan cloud transformation based on year-over-year workload forecasts and expert recommendations.

Notably, a lift-and-shift strategy without proper planning will likely increase your TCO, defeating one of the main reasons for migrating—cost savings. Before migration, conducting a thorough rightsizing assessment is crucial. As AWS points out, many customers have seen up to 36% in cost savings through proper rightsizing and automation.

Tools for real-time cost monitoring

Effective cost management platforms are essential for controlling expenses during and after migration. Gartner predicts that through 2024, 60% of infrastructure and operations leaders will encounter public cloud cost overruns that negatively impact their on-premises budgets. Therefore, implementing robust monitoring solutions is critical.

Several powerful tools can help manage and optimize cloud spending:

CloudZero: This cost intelligence platform provides real-time visibility into cloud spending during migration. It helps prevent overspending by tracking every dollar and showing how costs relate to business outcomes. The platform identifies costly inefficiencies, suggests resource adjustments for better value, and predicts future costs based on current data.

AWS Cost Explorer: This tool visualizes spending patterns and shows how funds are allocated across services. It tracks expenses by service and region, highlighting trends and potential savings. Organizations can create custom reports to identify cost drivers and project future expenses. Moreover, Cost Explorer forecasts costs, allowing for proactive strategy adjustments.

Flexera One: This comprehensive solution offers detailed cost modeling across multiple cloud platforms, including AWS and Google Cloud. It provides precise cost insights during migration to help manage budgets and prevent overruns. After migration, Flexera One continues to monitor and manage costs, ensuring efficient cloud spending by proactively avoiding unnecessary expenses.

OpenCost: This vendor-neutral open source project measures and allocates cloud infrastructure and container costs in real-time. It offers flexible, customizable cost allocation and cloud resource monitoring for accurate showback and chargeback. The platform provides real-time cost allocation broken down to the container level and supports dynamic asset pricing through integrations with AWS, Azure, and GCP billing APIs.

Azure Cost Management: This native tool helps track costs across business units, applications, and teams. It offers easy-to-implement savings recommendations, forecasting and budgeting insights, tagging and metadata capabilities for accurate cost allocation, and anomaly detection using AI/ML-powered algorithms.

For companies seeking to optimize their cloud investment, these monitoring practices are highly recommended:

• Set clear, measurable goals for cloud monitoring
• Choose appropriate cloud monitoring tools for actionable insights
• Implement FinOps practices to manage and optimize cloud costs
• Configure automated alerts for deviations from cost baselines
• Perform regular audits to identify and eliminate unused resources

Without proper cost monitoring, ongoing cloud expenses may increase unexpectedly. Continuous tracking allows organizations to identify areas where costs could be reduced or budget adjustments might be necessary. As cloud adoption continues to accelerate, with Gartner predicting end-user spending on public cloud services to increase from USD 595.70 billion in 2024 to USD 723.40 billion in 2025, effective cost management becomes even more critical to avoid contributing to the estimated 35% of cloud spending lost to waste.

Challenge 3: Legacy System Compatibility

Legacy systems represent one of the most complex technical hurdles in cloud migration, with many organizations finding their decades-old applications fundamentally incompatible with modern cloud architectures. This incompatibility creates significant roadblocks that can derail migration projects entirely if not properly addressed.

Why legacy systems struggle in cloud environments

Legacy applications often rely on outdated technologies and programming languages that simply don't align with cloud-native environments. The absence of standardized protocols and interfaces creates substantial integration challenges when attempting to connect these systems with modern cloud platforms. These older systems typically feature rigid, monolithic architectures with deeply entangled dependencies that weren't designed to function outside their original environments.

Beyond technical limitations, legacy systems frequently suffer from knowledge gaps that complicate migration efforts. As data engineers typically transition to new roles every two years, organizations often face situations where critical knowledge has left with former employees. Picture opening an existing report with thousands of lines of poorly designed code, no documentation, and no access to the original developer – a nightmare scenario for migration teams.

The maintenance burden grows increasingly severe as systems age. Many organizations still depend on legacy platforms to perform essential functions, yet face mounting challenges including:

• High maintenance costs for systems requiring niche expertise
• Limited flexibility when attempting to implement new features
• Growing security vulnerabilities from outdated platforms lacking modern encryption
• Innovation bottlenecks caused by data trapped in inflexible systems

These technical constraints extend beyond mere inconvenience – they directly impact business performance. Without enough governance, self-service analytics often results in hundreds of inconsistent reports throughout an organization. Furthermore, communication between technical teams and stakeholders frequently suffers, creating misalignment between business needs and technical capabilities.

Refactoring vs replatforming: which to choose?

When migrating legacy systems to the cloud, organizations typically choose between two primary modernization strategies: refactoring and replatforming. Each approach offers distinct advantages depending on your specific circumstances.

Refactoring involves restructuring existing application code without changing its external behavior. This approach is ideal when:

• Your legacy mainframe application no longer addresses business demands due to limitations or excessive maintenance costs
• You have a monolithic application hindering quick product delivery or customer response
• The application has poor test coverage affecting quality and feature delivery
• You need to reduce technical debt while preserving core functionality

Refactoring enhances code readability and maintainability by restructuring the codebase, making it easier for developers to understand and modify. This approach helps reduce technical debt as inefficiencies are addressed, decreasing the risk of encountering costly issues later. However, refactoring presents challenges – it can be time-consuming, might introduce new bugs despite careful planning, and potentially diverts resources from other critical tasks.

Replatforming, alternatively, moves an application to a new platform while preserving its essential features. This strategy works best when:

• You want to save time and reduce costs by moving to fully managed or serverless services
• You need to improve security and compliance by upgrading your operating system
• Cost reduction is possible through switching to different processors or operating systems

Replatforming allows businesses to upgrade to more modern, robust platforms, thereby improving application performance and security. By moving to scalable cloud infrastructure, applications can accommodate growth more seamlessly. Nevertheless, this approach requires significant research and careful planning to ensure the investment justifies the short-term disruption.

The decision between these approaches should align with your business drivers and specific circumstances. If your primary goal is reducing technical debt or optimizing code, refactoring makes sense. For organizations seeking to minimize infrastructure management while improving scalability with minimal code changes, replatforming offers a compelling alternative.

Using middleware to bridge compatibility gaps

Middleware provides an elegant solution for organizations that cannot completely replace their legacy systems yet need cloud integration. It serves as a communication layer that facilitates interaction between different applications, systems, and services.

Originally developed in response to distributed computing in the 1980s, middleware use increased as a way to link newer applications to traditional legacy systems. Today, middleware has evolved to play an essential role in modern cloud-native application development, enabling developers to build applications without creating custom integrations whenever they need to connect to services, data sources, or devices.

There are several effective middleware approaches for legacy integration:

1. API Wrappers - Build REST APIs on top of legacy systems to expose key data and logic to modern applications
2. Enterprise Service Bus (ESB) - Create a communication hub that routes data between systems in real-time or batches
3. Enterprise Application Integration - Establish a standardized way to connect applications, processes, and data sources throughout the enterprise

The benefits of middleware implementation are substantial. A large financial institution struggling with a COBOL-based mainframe discovered they couldn't feasibly migrate away from it, yet needed real-time access via Salesforce and analytics tools. By implementing middleware, they created secure REST APIs over mainframe records, integrated directly into Salesforce, and connected real-time data to dashboards. The result was a 40% reduction in customer onboarding time with zero disruption to the mainframe.

For organizations with legacy compatibility challenges, middleware delivers multiple advantages:

• Minimal disruption - No need for complete system replacement
• Faster integrations - Modern systems connect via APIs
• Lower costs - Avoids large-scale redevelopment
• Extended system lifespan - Keeps legacy platforms functional and future-ready

To implement middleware effectively, standardize interfaces and protocols to facilitate communication between legacy and cloud systems. This reduces compatibility issues and simplifies the integration process. Additionally, utilize middleware solutions specifically designed to bridge legacy systems and cloud environments, enabling data transformation and protocol conversion for smooth communication.

By encapsulating key functionalities through APIs or intermediary services, legacy systems can communicate with hybrid cloud environments without complete restructuring. Applying strategies like modular refactoring or virtualizing the execution environment further helps isolate problematic components, facilitating progressive integration.

Challenge 4: Skill Gaps in IT Teams

The human element often proves to be the most persistent obstacle in cloud migration, with skill gaps creating significant roadblocks for organizations. According to a recent survey, over 85% of IT decision-makers reported that the lack of cloud expertise has negatively impacted their ability to achieve business goals. This technical talent shortage ranks among the top priorities for tech CEOs, with Gartner reporting that attracting and retaining talent is their foremost concern.

Why internal teams may lack cloud expertise

Several factors contribute to the widespread shortage of cloud skills within internal IT teams. Firstly, the rapid evolution of cloud technologies continuously introduces new tools, platforms, and best practices. What was cutting-edge knowledge last year may already be outdated, creating a constant demand for professionals with current expertise.

Cloud environments require specialized skills that many traditional IT professionals simply don't possess. These include proficiency in:

• Cloud platform architecture and configuration
• Infrastructure management and automation
• Cloud security and compliance
• DevOps practices and containerization

Without these specialized skills, organizations face significant consequences. Inexperienced teams can delay migration timelines or make choices that introduce unnecessary costs and security vulnerabilities. In fact, a staggering 95% of IT decision-makers reported that skill gaps negatively impact their teams.

The responsibilities of IT staff change dramatically after cloud transition. As applications move to the cloud, operational responsibilities of application teams increase substantially. Without proper training, this shift leads to operational instability, increased costs, and potential security breaches.

Upskilling vs outsourcing: pros and cons

When facing talent shortages, organizations typically choose between two primary strategies: upskilling existing employees or outsourcing to external experts.

Upskilling involves training current employees to develop new cloud skills. This approach strengthens internal teams rather than replacing them with new talent. Benefits include:

• Knowledge continuity and retention of institutional memory
• Increased employee engagement and loyalty
• Long-term cost effectiveness
• Alignment with existing company culture

To succeed with upskilling, organizations should implement formal training mechanisms with standardized curriculums for different roles. Many companies use frameworks like the Skills Framework for the Information Age (SFIA) to assess current skill sets, identify gaps, and plan targeted development initiatives.

Outsourcing, in contrast, involves hiring external experts or agencies to handle specific cloud tasks. Rather than training in-house staff, companies contract specialists to quickly fill skill gaps. Advantages include:

• Immediate access to specialized expertise
• Flexibility to scale resources as needed
• No long-term commitment to specialized positions
• Focus on core business objectives while experts handle technical challenges

Certainly, both approaches have limitations. Upskilling works best as a long-term strategy rather than a quick solution, requiring careful assessment of workforce potential before committing. Outsourcing can introduce communication challenges and potential knowledge transfer issues when contracts end.

In practice, many organizations find that a hybrid approach works best. This balanced strategy allows businesses to upskill for commonly needed capabilities while outsourcing highly specialized or temporary requirements. Technical accelerator programs can provide outside cloud engineers and migration specialists who help application teams during migration while simultaneously transferring knowledge.

The decision between upskilling and outsourcing should align with project urgency, budget constraints, and long-term business goals. Time-sensitive migrations may benefit from immediate external expertise, whereas organizations focused on building sustainable internal capabilities might prioritize upskilling despite the longer timeline.

Regardless of approach, addressing the cloud skills gap is essential. Companies that maintain current cloud capabilities consistently outperform those with outdated skills and achieve better business outcomes. Without addressing this challenge, organizations risk falling behind in the race to effectively leverage cloud technologies.

Challenge 5: Downtime and Business Disruption

Downtime represents a substantial financial risk in cloud migration, with businesses losing up to USD 5600.00 per minute when systems are unavailable. This often-overlooked challenge can transform what should be a strategic advantage into a operational nightmare, particularly when migration planning fails to account for service continuity.

How downtime affects operations and customer trust

Service interruptions during cloud migration directly impact both internal operations and external relationships. With average downtime costs ranging from USD 140,000 to USD 540,000 per hour, the financial implications are immediate and severe. Beyond monetary losses, extended outages disrupt critical business functions, decrease productivity, and potentially cause permanent data loss.

The damage extends beyond internal operations. As one industry expert notes, "downtime can quickly become a hindrance rather than a help" when customers lose access to services they depend on. Subsequently, even brief interruptions can lead to immediate revenue loss and eroded user trust. This trust, once damaged, requires significant effort to rebuild, making downtime prevention a critical priority for any migration project.

Strategies to minimize service interruptions

To reduce migration-related downtime, several proven approaches stand out:

• Blue-green deployment: Maintain parallel environments simultaneously, working through issues in the new environment while keeping the original as a backup. This approach virtually eliminates the risk of service disruptions during transition.
• Phased migration: Break your migration into manageable stages to reduce overall impact. For instance, migrating attachments weeks before project data significantly reduces the time window for the remaining migration.
• Read-only mode: Prior to migration, restrict user permissions to prevent changes that would require re-migration. In Confluence, remove all permissions except read access; for Jira, create permission schemes allowing only browse capabilities.

Above all, migration methods should be chosen based on each workload's downtime tolerance. As Microsoft recommends, "Choose downtime migration for workloads that tolerate planned outages... Choose near-zero downtime migration for critical workloads".

Importance of rollback plans and testing

A comprehensive rollback plan provides the ability to quickly reverse changes when deployment issues arise. This safety mechanism minimizes downtime, limits business impact, and maintains system reliability. To create an effective rollback strategy:

First, clearly define what constitutes a failed deployment in collaboration with stakeholders. Include specific conditions that trigger rollbacks, such as CPU usage limits or response time thresholds to make decisions consistent during incidents.

Second, automate rollback steps in CI/CD pipelines using tools like Azure Pipelines or GitHub Actions. This automation enables rapid execution with minimal manual intervention.

Third, rigorously test your rollback procedures by simulating deployment failures in preproduction environments. This validates their effectiveness and helps identify gaps in your processes.

As one database expert emphasizes, "The only way to check is to restore it. Some places automatically rebuild test environment from a backup of production every week". Through this disciplined approach, organizations can ensure that even when problems occur, business continuity remains protected.

Conclusion

Cloud migration presents significant challenges, yet organizations can overcome these obstacles through careful planning and strategic implementation. Throughout this article, we've explored five major hurdles that commonly derail migration projects.

Security and compliance issues demand robust encryption strategies and clear understanding of regulatory requirements. Cost overruns, arguably the most common pitfall, require thorough TCO analysis and real-time monitoring tools to prevent budget disasters. Legacy system compatibility calls for thoughtful decisions between refactoring and replatforming, with middleware solutions bridging critical gaps when necessary. Skill shortages necessitate balanced approaches to talent acquisition, whether through upskilling internal teams or strategic outsourcing. Finally, downtime risks can be mitigated through blue-green deployments, phased transitions, and comprehensive rollback plans.

Companies that successfully navigate these challenges position themselves for substantial rewards. After all, organizations migrating at least 60% of their IT systems to the cloud experience profit increases up to 11.2% year over year.

The cloud journey may seem daunting, but with proper preparation and awareness of these potential roadblocks, your organization can join the ranks of those reaping cloud computing's transformative benefits rather than becoming another migration statistic.