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What Is Cloud Migration?

Cloud migrations are complex transitions that frequently lead to budget overruns, security vulnerabilities, and operational downtime if not properly executed. Key challenges include aligning legacy system compatibility, bridging internal skills gaps, and avoiding vendor lock-in with major hyperscalers.

The most critical hurdles organizations face include:

  • Limited visibility into existing infrastructure: Missing asset inventories make migration planning inaccurate.
  • Incomplete application dependency mapping: Hidden dependencies increase the risk of outages during migration.
  • Choosing the wrong migration strategy: A poor migration approach can increase costs and reduce cloud benefits.
  • Unexpected cloud migration costs: Hidden infrastructure, licensing, and data transfer costs strain budgets.
  • Data migration complexity: Large datasets require careful synchronization and validation.
  • Security and privacy risks: Misconfigurations can expose sensitive data during and after migration.
  • Regulatory and compliance requirements: Cloud deployments must meet industry and regional regulations.
  • Application compatibility and modernization issues: Legacy applications may require significant redesign before migration.
  • Performance and latency problems: Cloud architectures can introduce network and application delays.
  • Business disruption and downtime: Poor planning can interrupt critical business operations.
  • Skills gaps and organizational resistance: Limited cloud expertise and resistance to change slow projects.
  • Managing hybrid and multi-cloud environments: Multiple environments increase operational complexity.

Why Cloud Migrations Fail 

Cloud migrations often fail due to inadequate planning and a lack of understanding of the existing IT landscape. Organizations might underestimate the complexity of their legacy systems or overlook hidden application dependencies, resulting in unexpected technical challenges. Insufficient discovery and assessment phases can lead to costly mistakes, such as migrating incompatible applications or missing critical data.

Another common reason for failure is poor stakeholder alignment and change management. If business leaders, IT teams, and end users are not aligned, conflicting priorities and resistance to change can stall migration efforts. Failure to address security, compliance, and performance requirements can further derail projects, leading to budget overruns, operational disruptions, or data breaches that damage trust and reputation.

Related content: Review the top cloud migration risks and how to mitigate them.

12 Common Cloud Migration Challenges 

1. Limited Visibility into Existing Infrastructure

Limited visibility into the current IT environment is a major hurdle for cloud migration. Many organizations lack up-to-date inventories of their hardware, software, and network assets, making it difficult to plan a migration. Without accurate insight, it is easy to overlook legacy systems, shadow IT, or unsupported components that could cause failures or security gaps once workloads are moved.

This lack of visibility also limits the ability to identify which workloads are suitable for migration and which should remain on-premises. It increases the risk of duplicating resources, missing dependencies, or migrating obsolete systems. Comprehensive discovery is necessary to build an accurate baseline, reduce surprises, and support informed decision-making throughout the migration process.

2. Incomplete Application Dependency Mapping

Incomplete mapping of application dependencies can lead to migration failures and unplanned downtime. Applications rarely operate in isolation; they interact with databases, middleware, APIs, and other services. If these dependencies are not fully documented and understood, migrating only part of an application stack can break functionality and disrupt business operations.

Dependency mapping is often complex, especially in environments with a mix of legacy and modern systems. Failure to capture these relationships can result in performance bottlenecks, integration issues, or security vulnerabilities in the cloud. A thorough assessment of data flows, communication paths, and service linkages is required to ensure application performance after migration.

3. Choosing the Wrong Migration Strategy

Selecting an inappropriate migration strategy can compromise project outcomes. Common approaches include lift-and-shift, replatforming, and refactoring, each with distinct trade-offs in cost, complexity, and speed. A one-size-fits-all approach often fails because different workloads have unique requirements and constraints. For example, rehosting a legacy application may not use cloud-native benefits or could introduce compatibility issues.

If the migration strategy does not align with business objectives or technical realities, organizations may encounter performance problems, increased costs, or the need for post-migration remediation. Careful analysis and tailored strategies for each workload are necessary to increase cloud value while minimizing disruption and risk.

4. Unexpected Cloud Migration Costs

Unexpected costs are a frequent challenge in cloud migration projects. Initial estimates often focus on direct infrastructure expenses but overlook ancillary costs such as data transfer, network reconfiguration, or increased licensing fees. These hidden expenses can quickly erode anticipated savings and affect return on investment.

Cost overruns can also result from poor workload sizing, lack of resource optimization, or failure to decommission unused assets after migration. Organizations must implement cost management practices, monitor cloud usage, and regularly review billing to prevent budget surprises. Upfront planning and transparency help keep migration costs under control.

5. Data Migration Complexity

Migrating large volumes of data to the cloud is complex, especially for organizations with legacy databases, distributed storage, or strict data integrity requirements. Data must be validated, transformed, and synchronized across environments to avoid loss, corruption, or inconsistencies. This process is further complicated by the need to maintain business continuity and minimize downtime.

Data migration projects can also be hindered by bandwidth limitations, regulatory constraints, or incompatible formats between source and target systems. Careful planning, testing, and execution are required to ensure that data arrives in the cloud intact and accessible. Automation tools and phased approaches can help manage risk and simplify the migration process.

6. Security and Privacy Risks

Cloud migration introduces new security and privacy risks that must be addressed proactively. Moving data and applications off premises changes the organization’s attack surface and may expose sensitive information to unauthorized access if not properly secured. Cloud environments require new identity management, encryption, and monitoring controls to maintain data confidentiality and integrity.

Failure to account for shared responsibility models, misconfigured cloud services, or lack of visibility into cloud activity can lead to breaches or compliance violations. Security must be integrated into every phase of migration, from planning to execution and ongoing operations. Regular audits and continuous monitoring are necessary to safeguard cloud-hosted assets.

7. Regulatory and Compliance Requirements

Meeting regulatory and compliance requirements is a significant challenge during cloud migration, especially for organizations in regulated industries such as finance or healthcare. Laws and standards like GDPR, HIPAA, or PCI DSS dictate how data must be stored, processed, and protected. Migrating to the cloud may require new controls, documentation, and reporting to remain compliant.

Failure to address these requirements can result in legal penalties, reputational harm, or operational restrictions. Organizations must work with legal and compliance teams to understand obligations and verify that chosen cloud services meet required certifications and safeguards. Compliance should be embedded into the migration plan, not treated as an afterthought.

8. Application Compatibility and Modernization Issues

Many legacy applications are not designed for cloud environments, leading to compatibility and modernization challenges. Some applications rely on hardware-specific features, outdated operating systems, or proprietary middleware that are not supported in the cloud. Attempting to migrate these applications without modification can result in performance issues or failure.

Modernizing applications, such as containerizing, refactoring, or adopting microservices, may be necessary to realize cloud benefits. However, this process can be time-consuming and resource intensive. Organizations must assess which applications are suitable for rehosting versus those requiring significant redevelopment and plan accordingly to minimize disruption.

9. Performance and Latency Problems

Performance and latency issues often arise after cloud migration, especially for applications with real-time or high-throughput requirements. The physical distance between cloud data centers and end users, variable internet connectivity, or suboptimal cloud configurations can degrade user experience and affect business operations.

To mitigate these risks, organizations need to conduct performance testing and optimize workloads for the cloud environment. This may involve using content delivery networks, scaling resources dynamically, or re-architecting applications for distributed architectures. Continuous monitoring and tuning are required to maintain acceptable performance levels after migration.

10. Business Disruption and Downtime

Business disruption and downtime are major concerns during cloud migration. Even brief outages can lead to lost revenue, customer dissatisfaction, and reputational harm. Migrations that require extended cutover windows, complex data synchronization, or manual interventions are particularly prone to errors and delays.

To minimize disruption, organizations must develop migration plans with detailed rollback procedures, backup strategies, and communication protocols. Testing migrations in controlled environments and scheduling cutovers during low-traffic periods can further reduce risk. Planning is necessary to maintain business continuity throughout the migration process.

11. Skills Gaps and Organizational Resistance

Skills gaps within IT teams can slow down or jeopardize cloud migration projects. Cloud platforms require expertise in new tools, architectures, and security models that may not be present in traditional IT organizations. Training and upskilling are necessary to equip teams with the knowledge needed for successful migrations.

Organizational resistance to change is another barrier. Employees may fear job loss, increased workload, or unfamiliar workflows associated with cloud adoption. Effective change management, including communication, training, and stakeholder engagement, is critical to fostering buy-in and supporting a smooth transition.

12. Managing Hybrid and Multi-Cloud Environments

Many organizations adopt hybrid or multi-cloud strategies for flexibility, redundancy, or regulatory reasons, but managing these environments adds complexity to migration efforts. Integrating on-premises infrastructure with multiple cloud providers requires networking, consistent security controls, and unified management tools.

Inconsistent policies, fragmented visibility, and siloed operations can increase risk and operational overhead. Organizations must invest in automation, centralized monitoring, and governance frameworks to manage hybrid and multi-cloud environments. Standardizing processes and using cross-platform tools can help maintain control and simplify ongoing operations.

Related content: Learn how to build and manage hybrid cloud infrastructure.

Lanir Shacham
CEO, Faddom

Lanir specializes in founding new tech companies for Enterprise Software: Assemble and nurture a great team, Early stage funding to growth late stage, One design partner to hundreds of enterprise customers, MVP to Enterprise grade product, Low level kernel engineering to AI/ML and BigData, One advisory board to a long list of shareholders and board members of the worlds largest VCs

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Tips from the Expert

In my experience, here are tips that can help you better manage cloud migration challenges:

  1. Create an application migration scorecard:

    Develop a weighted scoring model for every application based on business value, technical debt, dependency complexity, cloud readiness, supportability, and operational risk. This removes subjectivity from migration decisions and helps justify priorities to stakeholders.

  2. Baseline operational behavior before migration:

    Collect several weeks of production metrics (including CPU, memory, network traffic, storage IOPS, transaction volumes, and seasonal peaks) before moving workloads. Without a baseline, it’s difficult to determine whether post-migration issues are cloud-related or pre-existing.

  3. Map operational ownership, not just technical dependencies:

    In addition to identifying application dependencies, document which teams own each service, database, API, firewall rule, and integration. Many migration delays occur because no one knows who approves or supports a critical component.

  4. Eliminate technical debt before moving it:

    Identify obsolete scheduled tasks, unused databases, dormant services, legacy integrations, and abandoned applications during discovery. Migrating unnecessary components increases cloud costs and operational complexity without delivering business value.

  5. Define cloud operating standards before the first workload moves:

    Standardize naming conventions, tagging policies, network segmentation, backup policies, monitoring, IAM roles, logging, and infrastructure templates early. Consistent standards prevent every migration wave from creating a different operational model.

How to Overcome Cloud Migration Challenges 

Here are some of the ways that organizations can ensure a smooth transition to the target cloud environment.

1. Start with Automated Asset Discovery

Automated asset discovery provides an accurate inventory of IT assets, including servers, applications, databases, and network devices. This visibility is critical for understanding what needs to be migrated, identifying unsupported or redundant systems, and uncovering hidden dependencies. Automated tools reduce manual effort and the risk of oversight, enabling data-driven decisions during the planning phase.

By using automated discovery, teams can detect unauthorized assets, shadow IT, and outdated components that may pose security or compatibility risks. This baseline inventory serves as the foundation for migration planning, helping prioritize workloads, allocate resources, and anticipate potential roadblocks before they affect the migration timeline.

Key actions:

  • Inventory servers, applications, and databases
  • Identify unsupported and obsolete assets
  • Detect shadow IT and unmanaged systems
  • Maintain a continuously updated asset inventory

2. Map Application Dependencies and Data Flows

Understanding how applications communicate with each other is necessary before migrating any workload. Dependency mapping identifies connections between applications, databases, APIs, messaging systems, storage, and external services. It helps teams determine the correct migration sequence, avoid breaking integrations, and ensure that required components are available after cutover.

Automated dependency mapping tools can analyze network traffic, process communications, and service relationships to build an accurate view of the environment. This information supports migration planning, reduces the risk of unexpected outages, and highlights opportunities to consolidate or modernize applications before moving them to the cloud.

Key actions:

  • Discover application and service dependencies
  • Map database and API communication paths
  • Validate migration sequencing before cutover
  • Document critical data flows

3. Classify Workloads by Business Criticality

Not every application should be migrated with the same priority or strategy. Classifying workloads according to business criticality, technical complexity, compliance requirements, and downtime tolerance helps organizations allocate resources and reduce operational risk. Critical systems typically require more extensive testing, rollback planning, and stakeholder involvement.

This classification also helps determine migration order. Low-risk, nonproduction, or less critical applications are good candidates for early migration waves, allowing teams to refine processes before tackling mission-critical workloads. A structured prioritization approach improves confidence and minimizes disruption throughout the project.

Key actions:

  • Rank workloads by business impact
  • Prioritize low-risk applications for early migration
  • Define recovery objectives for critical systems
  • Include compliance requirements in prioritization

4. Select the Right Migration Approach for Each Workload

Migration strategies should be chosen based on the characteristics of each workload rather than applying a single approach across the environment. Some applications are suited for lift-and-shift migrations, while others benefit from replatforming, refactoring, replacing with SaaS solutions, or retiring if they no longer provide business value.

Evaluating application architecture, operational requirements, cost, and long-term business goals helps determine the appropriate approach. Matching the migration strategy to each workload reduces unnecessary modernization efforts, controls costs, and increases the likelihood of achieving expected performance and scalability improvements.

Key actions:

  • Evaluate rehost, replatform, and refactor options
  • Retire obsolete applications where appropriate
  • Align migration strategy with business goals
  • Estimate cost and effort before execution

5. Build a Phased Migration Roadmap

A phased migration roadmap breaks a large project into manageable stages instead of attempting a single large-scale migration. Each phase should define workloads to be migrated, success criteria, timelines, responsible teams, and rollback procedures. This incremental approach reduces operational risk and allows lessons learned from earlier phases to improve subsequent migrations.

Pilot migrations provide an opportunity to validate tools, processes, and cloud configurations before expanding the scope. Regular reviews throughout the roadmap help adjust priorities, resolve issues quickly, and keep the migration aligned with evolving business and technical requirements.

Key actions:

  • Start with pilot migrations
  • Define milestones and rollback plans
  • Validate each migration phase before expanding
  • Adjust plans based on lessons learned

6. Establish Security and Compliance Controls Early

Security and compliance requirements should be incorporated into migration planning from the beginning rather than added after workloads are deployed. Organizations should define identity and access policies, encryption standards, network segmentation, logging, and monitoring before moving production systems. Establishing these controls early reduces the likelihood of misconfigurations that could expose sensitive data.

Compliance requirements should also be validated against the capabilities of the target cloud environment. Documenting security controls, implementing continuous compliance monitoring, and verifying cloud provider certifications help organizations meet regulatory obligations while maintaining a consistent security posture throughout the migration.

Key actions:

  • Configure identity and access management
  • Encrypt data in transit and at rest
  • Enable logging and continuous monitoring
  • Validate compliance before production deployment

7. Test Performance, Availability, and Recovery

Comprehensive testing ensures that migrated workloads perform as expected under real operating conditions. Performance testing should verify response times, resource utilization, scalability, and application behavior under expected and peak workloads. Identifying bottlenecks before production cutover reduces the risk of user-facing issues after migration.

Recovery capabilities should be tested with the same level of rigor. Disaster recovery procedures, backup restoration, failover mechanisms, and high-availability configurations should be validated through practical testing. Regular testing confirms that systems can recover quickly from failures and continue meeting business continuity requirements.

Key actions:

  • Benchmark application performance
  • Test backup and disaster recovery procedures
  • Validate failover and high-availability configurations
  • Simulate production workloads before cutover

8. Continuously Track Infrastructure Changes

IT environments continue to evolve throughout a migration project as new systems are deployed, existing applications are updated, and infrastructure configurations change. Monitoring these changes helps keep migration plans accurate and prevents newly introduced dependencies or assets from being overlooked.

Automated change detection provides current visibility into the environment and allows teams to update migration schedules as needed. Maintaining an accurate inventory throughout the project reduces configuration drift, improves governance, and ensures migration decisions are based on the latest infrastructure state.

Key actions:

  • Monitor configuration and asset changes
  • Update dependency maps continuously
  • Detect configuration drift automatically
  • Keep migration plans synchronized with the environment

9. Validate Migration Success with Technical Evidence

Migration success should be measured using objective technical validation rather than assuming workloads are functioning correctly. Teams should verify application availability, dependency connectivity, data integrity, security configurations, performance metrics, and infrastructure health against predefined acceptance criteria.

Collecting technical evidence through monitoring dashboards, system logs, automated validation scripts, and post-migration reports provides confidence that workloads are operating as intended. This documentation also supports audits, enables troubleshooting, and establishes a reliable baseline for future optimization efforts.

Key actions:

  • Verify application functionality and connectivity
  • Confirm data integrity after migration
  • Review performance against baseline metrics
  • Document validation results for audit and optimization

How Faddom Helps You Overcome Cloud Migration Challenges

Most cloud migration challenges trace back to one root cause: incomplete visibility into how applications and infrastructure actually connect. Faddom is an agentless application dependency mapping platform that gives IT teams a complete, real-time view of their environment before, during, and after migration. Because roughly 80% of migration work is planning, Faddom concentrates on surfacing the visibility gaps, unknown dependencies, outdated documentation, and security exposures that put migration uptime at risk, then uses a wave-based approach to simplify the move, reduce disruptions, and deliver precise insights at every step.

Key capabilities of Faddom:

  • Real-time dependency mapping: Agentless mapping provides complete visibility into applications, servers, and connections before, during, and after migration, exposing the hidden dependencies that otherwise cause costly disruptions and downtime.
  • Wave-based migration planning: Faddom maps application dependencies to plan migration waves accurately, grouping servers and applications that must move together to prevent failures and ensure a smooth, efficient move.
  • Accurate, always-current documentation: Continuous mapping replaces the fragmented or outdated records that make planning and executing a seamless migration difficult.
  • Security and compliance visibility: Faddom surfaces misconfigured firewalls and access controls, helping teams address the vulnerabilities that migrations can introduce.
  • Cost optimization: A built-in cloud calculator helps optimize compute, storage, and network costs to rightsize resources and reduce unnecessary expenses.
  • Rapid, agentless deployment: Faddom maps all on-premises servers, cloud instances, applications, and dependencies in under 60 minutes, with no agents to install.

See every connection, miss nothing, and migrate with confidence. Explore how Faddom supports your cloud migration and start a free 14-day trial.