Caylent’s new AI-driven migration package lands squarely in the crossfire of a reshaped virtualization market, promising an output-based, pay-only-for-success model designed to pull VMware, Azure and GCP workloads into AWS while leaning on Amazon Bedrock and AWS migration services to speed discovery, dependency mapping and cutover validation.
The enterprise virtualization and cloud market has been in flux since Broadcom’s acquisition of VMware and the subsequent licensing and go‑to‑market changes that followed. That upheaval — including Broadcom’s decision that VMware Cloud on AWS would be sold directly by Broadcom rather than resold through AWS and its partners — has prompted a wave of partner and customer activity as organizations re-evaluate long-term hosting, licensing and migration strategies. This change in channel dynamics is well documented across multiple industry outlets.
At the same time, hyperscalers keep iterating on migration automation: AWS has continued to enhance its Application Migration Service (MGN) and associated connectors to automate agent deployment and streamline lift‑and‑shift migrations, while cloud vendors pursue differentiated approaches to hybrid and migration tooling. Enterprises now face a choice between preserving VMware operational models in cloud-hosted VMware offerings (for example Azure VMware Solution or other vendor-managed stacks) or undergoing replatforming and modernization to cloud-native services. The consequence is a rich market for migration specialists and consultancies to capture workloads that move either to native public cloud stacks or hosted VMware stacks.
Caylent — an AWS Premier Tier Services Partner that won multiple AWS Partner Awards in 2024 (including Migration Consulting Partner of the Year and GenAI Industry Solution Partner of the Year) — has positioned itself to capture this moment by formalizing a productized migration offering it calls Accelerate for Cloud Migration. The company’s credentials in migrations and generative AI are public and verifiable through its announcements and AWS recognition.
This model also reallocates some risk back to the vendor: Caylent must accurately plan, automate, test, and validate migrations or absorb the cost of failed attempts. That shifts incentives in a way customers often prefer, but it requires airtight scoping and rigorous acceptance criteria to avoid disputes about what constitutes a “successfully migrated and validated” workload.
However, the offering is not a universal remedy. Customers must carefully validate vendor-supplied market numbers, define unambiguous acceptance criteria for “successful” migrations, and prepare for edge‑case remediation where automation falls short. Generative AI can accelerate discovery and planning, but it cannot replace subject‑matter validation for mission-critical or nonstandard workloads. Where Caylent’s model truly wins is in shifting commercial risk and speeding up decision-making — but that only helps when customers demand clarity and procedural rigor up front.
For CIOs and IT leaders, the practical path forward is a disciplined pilot: test the output‑based model on a meaningful but non-critical workload, validate the Terraform and operational handover, and then scale if the pilot’s technical and contractual assumptions hold. The migration market has entered a second phase: automation and commercial innovation. Caylent’s announcement is a concrete example of that phase, and it will matter most to organizations that do the careful work of scoping, testing and governing the migration outcomes.
Source: CRN Magazine AWS Partner Caylent Targets VMware, GCP And Azure Clients With New Cloud Migration Offering
Background
The enterprise virtualization and cloud market has been in flux since Broadcom’s acquisition of VMware and the subsequent licensing and go‑to‑market changes that followed. That upheaval — including Broadcom’s decision that VMware Cloud on AWS would be sold directly by Broadcom rather than resold through AWS and its partners — has prompted a wave of partner and customer activity as organizations re-evaluate long-term hosting, licensing and migration strategies. This change in channel dynamics is well documented across multiple industry outlets. At the same time, hyperscalers keep iterating on migration automation: AWS has continued to enhance its Application Migration Service (MGN) and associated connectors to automate agent deployment and streamline lift‑and‑shift migrations, while cloud vendors pursue differentiated approaches to hybrid and migration tooling. Enterprises now face a choice between preserving VMware operational models in cloud-hosted VMware offerings (for example Azure VMware Solution or other vendor-managed stacks) or undergoing replatforming and modernization to cloud-native services. The consequence is a rich market for migration specialists and consultancies to capture workloads that move either to native public cloud stacks or hosted VMware stacks.
Caylent — an AWS Premier Tier Services Partner that won multiple AWS Partner Awards in 2024 (including Migration Consulting Partner of the Year and GenAI Industry Solution Partner of the Year) — has positioned itself to capture this moment by formalizing a productized migration offering it calls Accelerate for Cloud Migration. The company’s credentials in migrations and generative AI are public and verifiable through its announcements and AWS recognition.
What Caylent announced — the product in plain terms
Caylent’s Accelerate for Cloud Migration is framed as a combined offering of:- AI‑enabled discovery and planning, powered by Amazon Bedrock for dependency mapping, inventory validation and migration path recommendations.
- Automated use of AWS migration tooling, particularly AWS Application Migration Service (MGN), with automated enablement, configuration and conversion of VM metadata into optimized AWS launch templates.
- Infrastructure-as-code generation, where migrations produce Terraform artifacts to “future-proof” the environment and standardize deployments.
- An output-based commercial model, where customers pay only for workloads that are successfully migrated and validated in AWS — not for time spent or failed attempts.
- Built-in post‑migration validation and cost optimization, including automated health checks, rightsizing recommendations and guidance on AWS Savings Plans.
Why Caylent’s timing makes strategic sense
- Broadcom’s licensing and channel moves have changed commercial calculus for VMware customers. Broadcom’s decision to centralize sales of VMware Cloud on AWS has been interpreted as increasing friction and cost for organizations seeking cloud alternatives, which in turn has created opportunity for AWS partners to present migration-to-AWS pathways. This shift in reseller dynamics is a direct market driver for migration programs.
- Enterprises sitting on large on‑prem VMware estates face rising renewal and license costs, and some are actively looking for alternatives. Caylent publicly frames the opportunity as enormous — referencing an 85 million VM on‑premises figure and a >$51 billion total addressable market — and says more than 70% of VMware customers are exploring alternatives. Those specific numbers appear in Caylent’s press coverage, but they derive from company statements and market extrapolations; independent confirmation of the exact figures is not readily found in public third‑party reports, so readers should treat the raw numbers as vendor‑supplied market sizing.
- The rise of generative AI tooling and Bedrock-style model orchestration has made it practical to accelerate repetitive, discovery-heavy phases of migration projects — dependency mapping, code snippet translation, and automated playbook generation — which historically have been labor‑intensive and error‑prone. Caylent leverages Amazon Bedrock, an AWS-managed service for foundation model inference and customization, to power those stages. Amazon Bedrock is explicitly designed for private, controlled model customization and integration in enterprise workflows, which makes it a reasonable underpinning for an AI-enabled migration product.
Technical anatomy — how Caylent claims the flow works
1. Assessment and discovery (AI‑assisted)
- Automated inventory validation: AI compares and reconciles application and server inventories to identify mismatches and stale records.
- Dependency mapping: Automated graphing of application interdependencies so migrations can be planned by application wave rather than by host, reducing cascade failures.
- Complexity classification: GenAI classifies database objects, middleware, and application assets by migration complexity for realistic planning windows.
2. Automated enablement and migration
- AWS Application Migration Service (MGN) automation: Caylent’s platform provisions and configures replication agents, validates prerequisites and orchestrates test cutovers.
- Metadata translation: VM metadata is translated into optimized AWS launch templates to ensure instances run with appropriate networking, IAM roles, and storage configurations.
- IaC generation: Terraform artifacts are emitted automatically so the post‑migration environment is codified and auditable.
3. Validation and optimization (post‑migration)
- Automated health checks verify service availability and dependency integrity.
- Rightsizing analysis compares migrated instance performance against AWS instance families and recommends Savings Plans and reservation strategies.
- Disaster recovery planning is included and aligned to customer RTO/RPO targets.
Commercial model — output-based pricing and risk allocation
Caylent’s most headline-grabbing commercial move is the promise that customers only pay for workloads that are successfully migrated and validated in AWS. That changes a common professional‑services model from time-and-materials or fixed-fee engagements into an outcome-driven structure. For customers, this can reduce the financial risk of a large migration program: you don’t pay for failed waves or extended discovery overruns if the provider’s tooling — and execution — fail to deliver.This model also reallocates some risk back to the vendor: Caylent must accurately plan, automate, test, and validate migrations or absorb the cost of failed attempts. That shifts incentives in a way customers often prefer, but it requires airtight scoping and rigorous acceptance criteria to avoid disputes about what constitutes a “successfully migrated and validated” workload.
Cross‑checks and verification of key claims
- Caylent’s awards and AWS partner status are independently verifiable through the company’s announcements and AWS Partner Awards listings; the company publicly details its Migration Consulting Partner of the Year and GenAI award wins for 2024.
- Caylent’s use of Amazon Bedrock and AWS Application Migration Service as core pieces of the technical architecture is corroborated by the company’s product pages and press statements, and those AWS services’ technical capabilities are documented on AWS sites. This provides two independent threads of verification: Caylent’s claim and AWS’s published product capabilities.
- Broadcom’s change to VMware Cloud on AWS reseller arrangements is confirmed by multiple outlets and Broadcom’s own public statements; AWS confirmed it would no longer resell the product. That market change underlies much of Caylent’s go‑to‑market rationale.
- The specific market sizing figures cited in Caylent and in press coverage (for example, “more than 85 million VMs on‑premises” and “a $51 billion-plus market opportunity,” plus the claim that “more than 70 percent” of VMware customers are exploring alternatives) appear in Caylent commentary as reported by trade press. Those claims are reasonable as vendor market estimates, but they are not matched to a clearly attributable third‑party market research report in the public domain (at least from accessible public sources). As such, these specific numeric claims should be treated as company-supplied estimates rather than independently verified market facts.
Strengths and practical benefits (what Caylent brings that matters)
- Output-based pricing aligns incentives: Customers who dislike vendor billing surprises will appreciate paying only for validated migrations. When tightly defined, this model can accelerate decisions and free up budgets for modernization work post‑migration.
- AI speeds discovery and planning: Manual dependency mapping is expensive. Using Amazon Bedrock to automate pattern recognition, catalog reconciliation and code classification can materially shorten the critical early phases of a migration program.
- Integrated IaC and Terraform generation: Delivering migrations with infrastructure-as-code artifacts reduces technical debt after cutover and accelerates future operations, patching and-scale workflows.
- Built-in cost optimization: Rightsizing and Savings Plan guidance reduces the chance that customers simply lift and shift and then pay too much on cloud bills — a common post-migration failure mode.
- AWS-native stack: For shops committed to AWS services, moving directly into AWS-native artifacts (EC2, RDS/Aurora, S3, IAM) can simplify future modernization projects that rewrite for cloud-native services. Caylent’s AWS Partner status and awards lend credibility to delivery capabilities.
Risks and caveats (what customers must watch)
- Vendor-supplied market claims need scrutiny: The headline numbers — 85 million VMs and $51B TAM — are useful framing, but customers should demand transparent methodology when vendors use such figures to justify urgency or pricing. Independent market research should be requested in RFPs or procurement deep dives.
- Output-based disputes are possible: Success criteria must be contractually explicit. Define exactly what “validated in AWS” means: uptime windows, performance baselines, functional acceptance tests, data consistency checks, and rollback triggers. Otherwise, customers risk long legal or billing debates after cutover.
- AI is only as good as the data: GenAI and model-based inference accelerate tasks but are prone to hallucination or misclassification when inventory data is stale or when edge-case configurations exist. Organizations must ensure discovery data is as accurate as possible and budget for manual validation of mission-critical systems. This is a standard migration risk: automated discovery tools surface many problems, but they don’t replace subject-matter-owner validation.
- Data gravity and latency constraints: Not all workloads are good candidates for a simple lift‑and‑shift. High I/O databases, tightly coupled multi‑component systems, and workloads with regulatory data residency constraints may require re-architecture or hybrid deployments rather than pure migration. Migration vendors must present clear patterns for these exceptions.
- Licensing and compatibility edge cases: Some on‑prem configurations — specialized hardware pass‑through, vendor-specific network appliances, or legacy drivers — do not translate cleanly to EC2 instances and require remediation that is expensive or time‑consuming.
- Operational lock‑in tradeoffs: Moving into AWS‑native services delivers many benefits but makes cross‑cloud mobility harder over time. Customers should weigh the operational and business cost of greater AWS dependency against simplified operations and service richness.
How to evaluate Caylent’s offering (a practical checklist for IT decision makers)
- Require a detailed migration acceptance test (MAT) definition with explicit performance and functional checks.
- Demand transparency on the AI models and prompts used for discovery — what data sources are consumed and how results are validated.
- Ask for a phased pilot: pick a non‑critical application and execute a full end‑to‑end migration under the output-based pricing to validate commercial and technical claims.
- Require delivered IaC artifacts and runbooks for verification — ensure Terraform output is modular, commented, and adheres to your security baselines.
- Confirm DR strategy: the offering claims inclusion of DR aligned to RTO/RPO; ensure these are quantifiable and have a tested runbook.
- Insist on a post‑migration FinOps baseline and governance handover that includes rightsizing steps and cost‑optimization checklists.
Competitive landscape — where this fits versus Azure, GCP and other migration options
- Microsoft and Google have their own migration accelerators and hosted VMware propositions designed to retain customers in their clouds. Microsoft’s Azure VMware Solution and migration tooling emphasize a lift‑and‑shift approach that keeps VMware operational familiarity while integrating with Azure management. Microsoft is actively investing in partner incentives to attract VMware workloads to Azure.
- Google’s stance emphasizes Kubernetes and Anthos for portability, and GCP offers migration tooling aimed at containerization and modernization. Many enterprises view Google as the Kubernetes-native option for portability but less of a direct drop-in for traditional VMware workloads.
- Specialist migration consultancies and system integrators often blend tooling: some sell hosted VMware on other clouds, others push replatforming to cloud‑native services. Caylent’s approach is a targeted play: combine AI-enabled automation, AWS MGN integration, and an outcome-based commercial model to accelerate migration specifically into AWS. That focus helps Caylent differentiate versus generalist consultancies, but it naturally aligns the outcome with AWS’s service model.
Operational playbook — a pragmatic sequence for customers considering the offering
- Inventory & Discovery: Run Caylent’s AI‑driven inventory probe and reconcile with CMDBs, app catalogs, and business owners.
- Pilot Wave: Choose a single application stack with clearly defined success metrics and run a full automated migration into a sandbox AWS account.
- Validate & Adjust: Run production‑equivalent tests, validate performance and security posture, and review Terraform outputs for compliance.
- Wave Execution: Migrate in prioritized waves, using discovered dependencies to minimize cross‑wave coupling and downtime windows.
- Post‑Migration Stabilization: Execute automated health checks, rightsizing, Savings Plan enrollment, and handover to ops teams with runbooks and IaC.
- Modernization Sprint: After lift‑and‑shift, schedule replatforming or refactoring sprints for strategic workloads to realize cloud-native benefits.
Strategic implications for enterprise technology strategy
- For organizations under VMware renewal pressure, the existence of packaged, outcome-driven migration products reduces the friction to evaluate cloud alternatives — not every migration will be simple, but the commercial model reduces the upfront procurement risk.
- For cloud strategy, the decision remains strategic: a wholesale move to AWS can accelerate access to AWS-native data, analytics, and AI services, but it also tightens vendor dependency. A hybrid approach — migrating suitable workloads while retaining regulated systems or latency‑sensitive components on-premises or on hosted VMware offerings — may remain optimal for many enterprises.
- For partners and channels, Caylent’s play demonstrates how AWS partners are increasingly productizing services (combining IP, automation and outcome-based pricing) to win migrations. Expect more competitors to mirror this model, and expect hyperscalers to respond with incentive programs, packaged migration credits, or enhanced managed VMware offers.
Final assessment — opportunity, but not a silver bullet
Caylent’s Accelerate for Cloud Migration is a timely, pragmatic product that matches a clearly signaled market opportunity: VMware licensing and channel disruption combined with widespread interest in cost reduction and modernization. Its use of Amazon Bedrock, AWS MGN and automated IaC generation makes technical sense and benefits from being anchored to AWS-native tooling; Caylent’s AWS partner pedigree supports execution credibility.However, the offering is not a universal remedy. Customers must carefully validate vendor-supplied market numbers, define unambiguous acceptance criteria for “successful” migrations, and prepare for edge‑case remediation where automation falls short. Generative AI can accelerate discovery and planning, but it cannot replace subject‑matter validation for mission-critical or nonstandard workloads. Where Caylent’s model truly wins is in shifting commercial risk and speeding up decision-making — but that only helps when customers demand clarity and procedural rigor up front.
For CIOs and IT leaders, the practical path forward is a disciplined pilot: test the output‑based model on a meaningful but non-critical workload, validate the Terraform and operational handover, and then scale if the pilot’s technical and contractual assumptions hold. The migration market has entered a second phase: automation and commercial innovation. Caylent’s announcement is a concrete example of that phase, and it will matter most to organizations that do the careful work of scoping, testing and governing the migration outcomes.
Source: CRN Magazine AWS Partner Caylent Targets VMware, GCP And Azure Clients With New Cloud Migration Offering
