GITNUXSOFTWARE REVIEW
Digital Transformation In IndustryTop 10 Best Migration to Cloud Services of 2026
Compare migration to cloud options and where they fit, with an editorial list for teams planning provider selection, including Infosys and EPAM.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page. This does not influence our reviews. Editorial policy
Infosys is the best pick for enterprises that need migration factory execution plus governance checkpoints across many workloads because its runbook-led cutovers and rollback planning are orchestrated in wave delivery. Choose Cognizant instead for large portfolios where dependency mapping and coordinated build, test, cutover, and rollback mechanics must stay tightly repeatable.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Infosys
Migration wave execution with runbook-led cutover and rollback governance tied to a factory-style delivery workflow.
Best for: Fits when enterprises need migration factory execution plus governance checkpoints across many workloads.
Cognizant
Editor pickMigration execution governance that ties cutover and rollback planning to migration wave operations.
Best for: Fits when enterprises need repeatable migration factory execution across many dependencies and teams.
EPAM Systems
Editor pickEnd-to-end migration delivery combining dependency mapping outputs with cutover and rollback engineering runbooks for release waves.
Best for: Fits when enterprises need engineering-led migration waves across complex integrations and multiple stacks.
Comparison Table
Infosys
enterprise_vendorIndian IT services major offering cloud migration through its Infosys Cobalt portfolio of services and solutions.
Migration wave execution with runbook-led cutover and rollback governance tied to a factory-style delivery workflow.
Infosys is a fit when cloud migration is treated as a program with repeated waves, dependency mapping, and controlled cutover and rollback mechanics. Delivery teams typically build a landing-zone oriented foundation and then execute workload migration with documented procedures for provisioning, validation, and operational handoff. The engagement model supports both VM and application layer moves, plus database migration planning and execution patterns suitable for hybrid cloud and multicloud schedules.
A tradeoff is that Infosys migration work usually assumes enterprise alignment on target architecture, security guardrails, and operational ownership to prevent rework in later waves. Infosys is most effective when an IT org needs a migration factory style workflow with clear throughput expectations and governance checkpoints, not when it only needs quick proof-of-concept deployments.
- +Program delivery cadence for migration waves and controlled cutovers
- +Governance guardrails across environments with repeatable policies
- +Migration execution support spanning rehost through refactor choices
- +Clear operational handoff artifacts for ongoing cloud run
- –Requires strong client alignment on target architecture and security controls
- –Automation depth depends on chosen toolchain and integration scope
- –Central coordination can slow changes late in the migration waves
CIO office and IT program teams
Multi-wave cloud migration factory rollout
Reduced cutover incidents
Enterprise architecture teams
Target-state architecture and dependency-driven migration
Fewer dependency-driven delays
Show 2 more scenarios
Security and compliance leaders
Landing-zone guardrails and audit evidence
More consistent audit readiness
Access controls and audit evidence processes are aligned to migration environments to reduce compliance gaps.
Application modernization teams
Refactor selection and controlled modernization
More stable application releases
Teams apply modernization decisions to high-value services with validation gates before switching traffic.
Best for: Fits when enterprises need migration factory execution plus governance checkpoints across many workloads.
Cognizant
enterprise_vendorTechnology services firm offering cloud migration, application refactoring, and cloud managed services.
Migration execution governance that ties cutover and rollback planning to migration wave operations.
Cognizant supports end-to-end migration execution with discovery and dependency analysis, migration wave planning, and workload classification to create sequenced tracks for rehost, replatform, and refactor decisions. Delivery work commonly includes landing-zone setup with guardrails, followed by application migration factory operations that coordinate build, test, cutover, and rollback. Cognizant also incorporates operational readiness, including environment management patterns that reduce drift when migrating across hybrid or multicloud estates.
A key tradeoff is reliance on Cognizant-led delivery and tooling patterns, which can limit flexibility if internal teams require full control over every pipeline step. A strong usage situation is a large application portfolio where dependency mapping and cutover planning drive migration waves, and multiple teams need consistent governance and execution reporting.
Cognizant is less suitable when migration scope is narrow and internal engineering already runs a mature factory with established landing-zone automation and reusable cutover runbooks.
- +Migration factory execution with coordinated build, test, cutover, rollback mechanics
- +Strong dependency mapping and wave planning for large application portfolios
- +Landing-zone guardrails paired with infrastructure as code delivery
- +Enterprise governance coverage that aligns security and operations with migrations
- –Delivery model can constrain teams that want full pipeline ownership
- –Integration timelines can extend when estates need extensive discovery cleanup
- –Cutover runbooks depend on agreed operational roles and acceptance criteria
- –Refactor-heavy programs require tighter scope definition to avoid churn
CIO office and architecture teams
Multi-quarter migration with governance controls
Lower cutover risk
Platform engineering leads
Landing zone rollout with guardrails
Faster environment provisioning
Show 2 more scenarios
Application migration factory managers
Coordinated rehost and replatform work
More predictable migration throughput
Execution tracks build, testing, and rollback steps to keep throughput consistent across batches.
Security and risk owners
Operational readiness for cloud transition
Audit-ready operational handoff
Cognizant aligns security expectations and runbook readiness with migration execution governance.
Best for: Fits when enterprises need repeatable migration factory execution across many dependencies and teams.
EPAM Systems
enterprise_vendorDigital platform engineering firm providing cloud migration, architecture redesign, and cloud-native development.
End-to-end migration delivery combining dependency mapping outputs with cutover and rollback engineering runbooks for release waves.
EPAM Systems differentiates itself as a large-scale engineering and cloud services firm that couples migration program delivery with implementation-level expertise across rehost, replatform, and refactor work. Its migration execution model typically includes discovery and dependency analysis, application portfolio assessment outputs, and factory-style delivery that targets repeatable wave plans.
EPAM also supports governance needs through practical landing-zone guardrails execution, plus automation via infrastructure-as-code and CI/CD integration for workload cutover and rollback readiness. Delivery quality is strongest when systems span multiple stacks and require coordinated engineering across application, data, and integration surfaces.
- +Migration factory delivery model with wave planning and engineering execution
- +Strong application and integration refactoring support beyond lift-and-shift
- +Infrastructure-as-code adoption for repeatable provisioning and environment parity
- +Practices for landing-zone guardrails implementation tied to rollout workflows
- –Requires clear governance buy-in to manage rollout guardrails consistently
- –Automated tooling depth can vary by application type and target architecture
- –Longer lead times than boutique teams during early dependency mapping cycles
- –Cutover and rollback plans depend on client availability for production ownership
Enterprise digital experience teams
Migrate customer and partner portals to cloud
Managed portal experience rollout
Enterprise AI engineering teams
Deploy retrieval-enabled LLM applications to cloud
Production LLM deployment readiness
Show 2 more scenarios
Enterprise integration architects
Modernize API and event flows across systems
Controlled cross-system processes
Connects business systems using APIs, middleware, and validated event flows during migration to cloud.
Large software engineering organizations
Standardize repositories and release workflows
More consistent delivery practices
Designs branching, testing, and release workflow practices that support repeatable migration waves to cloud.
Best for: Fits when enterprises need engineering-led migration waves across complex integrations and multiple stacks.
Wipro
enterprise_vendorIT services company providing cloud migration through its Wipro FullStride Cloud Services practice.
Factory-style orchestration that ties discovery outputs to multi-wave execution with structured cutover and rollback planning.
Wipro’s migration delivery emphasizes repeatable factory execution, which aligns with large application portfolios that need workload classification and staged cutover planning. Service teams typically start with migration readiness assessment and dependency mapping to drive sequencing across infrastructure, integration points, and data flows. For governance, Wipro focuses on landing-zone guardrails and operational controls needed for hybrid cloud and multicloud scenarios.
- +Migration factory execution for coordinated wave and cutover planning
- +Engineering-led migration paths from rehost to refactor
- +Governed landing-zone enablement aligned to operations
- +Automation artifacts for repeatable provisioning across environments
- –Success depends on timely customer approvals and access for validation
- –Change-heavy refactor requires stronger customer product ownership
- –Factory coordination adds overhead for small portfolios
- –Automation coverage may require environment-by-environment pattern tuning
CIO and program governance teams
Multi-wave migration factory orchestration
Fewer cutover failures
Enterprise application engineering leaders
Rehost and selective replatform waves
Predictable modernization progress
Show 2 more scenarios
Data platform and integration owners
Managed data migration and replication
Reduced data drift risk
Supports migration planning for data flows that require coordinated validation and cutover.
Security and cloud governance teams
Landing-zone guardrails implementation
Tighter governance controls
Establishes policy-aligned environments to control provisioning, networking, and operations.
Best for: Fits when enterprise programs need guided migration factories and governed landing-zone delivery across many applications.
Accenture
enterprise_vendorGlobal professional services firm offering end-to-end cloud migration consulting across all major hyperscaler platforms.
Accenture’s migration factory approach coordinates dependency-aware migration waves with runbook-based automation and operational handoff.
Accenture delivers end-to-end cloud migration services that combine migration factory execution with deep enterprise integration across legacy apps, infrastructure, and data flows. Its core strength is coordinating discovery outputs into migration waves with dependency mapping, cutover planning, and governance guardrails that teams can operate during ongoing rollouts.
- +Migration factory delivery model for consistent wave planning and execution control
- +Dependency mapping and cutover planning support multi-application portfolio moves
- +API-centric orchestration for repeatable provisioning and environment setup workflows
- +Governance guardrails for landing-zone operations across hybrid and multicloud programs
- –Service engagement models can slow changes for teams that expect self-serve tooling
- –Heavy dependency on client-provided access and architecture inputs for accurate readiness results
- –Tooling fit varies by cloud vendor landscape and may require additional platform engineering
- –Execution quality depends on strong internal governance participation during rollout
Digital and enterprise architecture teams
Modernize portals with governed access
Governed access controls
Telecommunications innovation teams
Plan emerging technology pilots for cloud readiness
Feasibility to operations path
Show 2 more scenarios
Technology operations teams
Improve reliability practices during migrations
Stabilized reliability practices
Uses investigation, observability, and managed change processes to address recurring failures during migration to cloud.
Supply chain technology teams
Modernize B2B EDI and partner integrations
Standardized partner connectivity
Designs mappings, canonical models, partner onboarding, and API connectivity for migration to cloud.
Best for: Fits when large enterprises need guided cloud migration waves with orchestration, governance, and cross-team dependency control.
IBM Consulting
enterprise_vendorHybrid cloud and AI consultancy offering migration services leveraging IBM Garage methodology and cloud platforms.
A migration factory delivery approach that ties dependency mapping to wave plans and cutover and rollback artifacts.
IBM Consulting runs cloud migration programs that combine application portfolio assessment with migration factory execution across rehost, replatform, refactor, and data cutover. It delivers detailed dependency mapping, landing-zone guardrails, and migration wave planning that support hybrid and multicloud delivery.
- +Migration programs with factory-style wave planning and repeatable delivery workflows
- +Strong dependency mapping outputs that feed sequencing, cutover, and rollback design
- +Governance guardrails designed for landing-zone controls and audit-ready operations
- +API and automation integration for orchestrating migrations and compliance checks
- –Requires active client collaboration for readiness inputs and acceptance gates
- –Less suitable for teams seeking a purely self-serve migration tooling layer
- –Factory execution depth can increase coordination overhead across stakeholders
- –Advanced automation coverage depends on the agreed delivery toolchain
Enterprise architecture teams
Align hybrid security and target architecture
Governed target architecture
Enterprise transformation leaders
Refactor legacy applications in waves
Implemented application changes
Show 2 more scenarios
Digital commerce operations leaders
Migrate storefront and back-office operations
Connected commerce operating model
Coordinates storefront, fulfillment, and returns changes with integrated platform work during migration to cloud.
AI and operations teams
Operationalize AI workflows with integration
Integration-ready AI workflows
Moves AI and natural language use cases from experimentation into operational workflows for migration to cloud.
Best for: Fits when enterprises need managed migration factory execution with governance, sequencing, and operational cutover rigor.
Capgemini
enterprise_vendorEuropean IT services leader specializing in cloud migration, application modernization, and infrastructure transformation.
Migration wave planning with governance artifacts and cutover and rollback runbooks built into the delivery workflow.
Capgemini is a cloud migration services provider with enterprise delivery centers that emphasize structured migration waves and governance artifacts alongside implementation. The firm typically supports application portfolio assessment, dependency mapping, workload classification, and end-to-end execution across rehost, replatform, and refactor plans.
- +Disciplined migration factory approach for repeatable wave delivery
- +Strong dependency mapping support for complex application portfolios
- +Landing-zone and governance artifacts built into migration execution
- +Practical automation using infrastructure as code patterns for cutovers
- –More delivery heavy than product-led tooling for day-to-day engineers
- –API depth varies by target platform and migration approach
- –Requires clear governance ownership to keep landing-zone guardrails effective
- –Refactor and database modernization scopes can extend timelines
Cloud and infrastructure leaders
Run a governed migration program with operations support
Governed cloud environment
Enterprise integration and partner teams
Transform EDI with managed transaction flows
More consistent partner connectivity
Show 2 more scenarios
Enterprise bid and proposal teams
Coordinate tender responses tied to migration scope
Clearer ownership and fewer misses
Manages compliance review, stakeholder inputs, and document production across tender cycles supporting migration to cloud.
Retail planning and partner teams
Connect trade promotion planning to cloud platforms
Structured promotion planning
Models promotional scenarios and links trade calendars to partner collaboration during migration to cloud planning.
Best for: Fits when enterprise IT teams need end-to-end migration delivery with governance and wave planning across hybrid estates.
HCLTech
enterprise_vendorGlobal technology company delivering cloud migration through its Cloud Native and infrastructure modernization services.
Wave-based migration factory execution that couples dependency-aware planning with operational cutover and rollback runbooks.
HCLTech is an IT services and migration execution provider with delivery capacity across enterprise apps, data platforms, and infrastructure modernization. The migration approach centers on end-to-end discovery, workload conversion planning, and controlled wave execution with documented cutover and rollback support.
- +Migration factory-style wave planning for coordinated large portfolio throughput
- +Cutover and rollback planning aligned to operational readiness workflows
- +Governance artifacts integrated into delivery workstreams and change control
- +Deep integration with client environments for dependency-aware application conversion
- –Delivery depends on established enterprise intake and governance processes
- –Automation and API surface depth varies by migration tooling and engagement scope
- –Complex hybrid estates can increase orchestration overhead across teams
- –Documentation quality can vary across workstreams without strict standards
Product engineering teams
Migrate connected device ingestion and operations
Integrated device-to-cloud delivery
Enterprise application owners
Modernize applications during controlled rollout
Coordinated modernization rollout
Show 2 more scenarios
Retail commerce merchandising teams
Migrate search and recommendations into retail systems
Retail capabilities aligned
Aligns commerce capabilities with product data and operational workflows while migrating to cloud.
Enterprise process owners
Redesign cross-application workflows to cloud
Governed redesigned workflows
Assesses and improves end-to-end processes across applications with implementation and governance support during migration to cloud.
Best for: Fits when enterprise migration programs need execution depth, controlled cutovers, and governance-integrated wave delivery.
PwC
enterprise_vendorBig Four firm providing cloud migration strategy, implementation, and operational transformation services.
Migration wave planning deliverables tied to governance guardrails for repeatable execution across application cohorts.
PwC is distinct in migration to cloud services because it delivers cloud advisory and large-program implementation support across regulated and enterprise environments. Migration readiness assessment, application portfolio assessment, and dependency mapping are core inputs to its cloud migration strategy work.
- +End-to-end migration readiness to wave planning artifacts for large portfolios
- +Strong dependency mapping focus for complex application and data flows
- +Governance guardrails for landing-zone design and operational controls
- +Program delivery model suited to hybrid cloud and multicloud transitions
- –Automation and API surface are not a product focus compared with cloud-native vendors
- –Delivery scales best with enterprise governance and stakeholder bandwidth
- –Tooling specifics for data replication workflows depend on chosen partner stack
CISOs and cloud risk leaders
Assess identity and security controls for cloud migration
Prioritized security improvements
Broadcast program governance teams
Plan migration across complex vendor programs
Aligned scope and controls
Show 2 more scenarios
Operations and transformation leaders
Standardize cross-unit processes with KPIs
Consistent workflows and ownership
Redesigns processes and connects findings to controls, KPIs, and operating procedures for migration to cloud.
Deal teams and technology executives
Perform technical due diligence for cloud decisions
Documented risk findings
Reviews architecture and delivery risks and frames them into documented findings and remediation roadmaps for migration to cloud.
Best for: Fits when enterprise programs need advisory-to-delivery continuity across governance, waves, and cutover planning.
Tata Consultancy Services
enterprise_vendorGlobal IT services provider offering cloud migration through its Enterprise Cloud unit and migration factory approach.
Factory-style migration delivery that couples dependency mapping and wave orchestration with landing-zone guardrail enforcement during execution.
Tata Consultancy Services differentiates itself through end-to-end cloud migration delivery that blends strategy work with hands-on engineering and operations. Its migration approach is built around portfolio and dependency discovery, migration wave planning, and governance controls delivered alongside platform build.
- +Strong delivery model for multi-wave migrations with explicit dependency handling
- +Governance guardrails are built into landing zone setup and enforced during migration
- +Automation support connects migration workflows to CI/CD and infrastructure as code
- +Experienced teams cover rehost through refactor style paths for mixed portfolios
- –Requires clear governance decisions early to avoid late rework during waves
- –Automation depth can depend on the client’s target tooling and existing pipelines
- –Operational handover quality varies based on chosen run model and training scope
- –Transformation-heavy programs can add planning overhead for application teams
Enterprise application and cloud teams
Modernize applications across cloud workstreams
Migration plan with delivery
Enterprise finance and operations teams
Migrate ERP with integration and validation
Coordinated ERP implementation
Show 2 more scenarios
Cloud operations and reliability teams
Set monitoring and incident workflows
Clear alert ownership
Builds monitoring practices that connect telemetry, alert rules, escalation, and incident response for migration to cloud.
Data platform and database teams
Design and modernize database schemas
Coordinated schema migration
Develops data models and implementation artifacts that connect database design with platform changes for migration to cloud.
Best for: Fits when large enterprises need migration-factory execution plus governance and engineering, not only advisory work.
Conclusion
After evaluating 10 migration to cloud, Infosys stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Frequently Asked Questions About Migration to Cloud
What should a migration readiness assessment cover before execution begins?
How do migration factories coordinate build, test, cutover, and rollback across multiple waves?
Which providers offer API-driven orchestration for provisioning and operational workflows?
When is a landing zone approach sufficient, and when does an operating model design become necessary?
How should enterprises handle data migration so it matches application cutover timing?
What breaks if dependency mapping is incomplete before wave planning starts?
How do providers manage security controls across identity access and administration during migration?
Which provider model fits organizations that need engineering depth across rehost to refactor with complex integrations?
What tradeoff occurs when internal teams must gain full control over the migration pipeline steps?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
How to Choose the Right Migration to Cloud
We see the biggest differences in migration to cloud come from how well each tool drives your plan through discovery and cutover, then how it keeps control during waves of change. When choosing, compare Migration wave planning, Cutover and rollback automation, and Audit trail coverage to avoid surprises halfway through.
Migration wave planning and scheduling
Why it matters
Migration wave planning and scheduling matters because cloud moves often happen in batches. If the tool can’t express dependencies and sequencing, teams lose time during cutover and rework after failures.
How to check
Ask for a demo that uses multiple waves and shows dependency ordering between workloads. Then show whether the plan exports as a checklist with owners and dates, and whether changes propagate to dependent items.
Cutover and rollback automation support
Why it matters
Cutover and rollback automation reduces downtime risk during migration to cloud. If rollback is only described in text, you’ll still need manual heroics under time pressure.
How to check
Request a sample workflow that performs a cutover for a test workload and then simulates a failure to trigger rollback steps. Confirm it records what changed and what should revert, not just a static runbook link.
Audit trail and change tracking
Why it matters
Audit trail and change tracking matters when multiple teams touch migration artifacts across waves. Without clear history, it’s hard to answer what was altered, by whom, and when.
How to check
In the interface, create a small migration item, change its target, and review the audit log entries. Verify you can filter by actor, timestamp, and migration item and export the log for evidence.
Dependency impact visibility for apps
Why it matters
Migration to cloud fails most often through hidden coupling. Dependency impact visibility helps you see what breaks when you move one workload and route validation work to the right owners.
How to check
Ask the tool to ingest a dependency view from an environment scan or import, then show how it marks impact paths when you select a workload for migration. Check whether it highlights downstream systems and produces a validation checklist.
Data migration consistency controls
Why it matters
Data migration consistency controls protect correctness during migration to cloud. Without defined behavior for data change and validation, you may “finish” the move but ship inconsistent state.
How to check
Request a demo using a database or data workload scenario and show how it handles ongoing writes during the final sync stage. Confirm it supports consistency checks and a clear “data validated” status you can gate on.
Red flags
- Wave plans can’t show dependencies or owners
- Rollback steps can’t be executed or recorded automatically
- Audit logs don’t capture who changed what
Fit by situation
- If your migration program runs in batches with many teams, prioritize Migration wave planning and scheduling.
- If you worry about downtime and failed cutovers, prioritize Cutover and rollback automation support.
- If data correctness is the gating risk, prioritize Data migration consistency controls.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
- Service review · 2026 · Digital Transformation In IndustryCloud Migration
- Service review · 2026 · Digital Transformation In IndustryCloud Migration Engineering
- Service review · 2026 · Digital Transformation In IndustryCloud Migration Advisory
- Review · 2026 · Digital Transformation In IndustryMigration Software
- Review · 2026 · Technology Digital MediaCloud Migration Software
Keep exploring
Comparing two specific tools?
Software Alternatives
See head-to-head software comparisons with feature breakdowns, pricing, and our recommendation for each use case.
Explore software alternatives→In this category
Digital Transformation In Industry alternatives
See side-by-side comparisons of digital transformation in industry tools and pick the right one for your stack.
Compare digital transformation in industry tools→