Using Agentic AI to Modernize VMware Environments on AWS

Cloud migration is a strategic lever for modernization, agility and scale, but it can demand more time and attention from your teams than it should. Manual analysis, repetitive configuration tasks and complex coordination across teams often stretch timelines and divert skilled engineers away from higher-value work.

That friction isn’t inevitable, and migration shouldn’t consume the capacity you need to keep your business moving forward. By combining agentic AI with experienced cloud migration consultants, solutions architects and DevOps engineers, we’re structuring our migration processes so that AI agents can take on data-intensive analysis and repeatable tasks, while human experts provide architectural judgment, business context and oversight.

The challenge with traditional cloud migration

Traditional cloud migrations tend to follow a predictable pattern. Readiness assessments, application portfolio analysis and business case development require teams to process large volumes of data gathered from workshops, discovery tools and technical documentation. Before execution begins, significant effort is spent organizing inputs, validating assumptions and aligning stakeholders on next steps.

As migration planning moves closer to execution, teams shift their focus to highly repeatable but time-intensive activities — creating runbooks, analysing firewall rules, validating configurations and documenting application states. These tasks are essential to a successful migration, but they demand sustained attention and careful coordination, particularly when timelines are compressed.

Over time, this work can absorb the capacity of architects and engineers who are best positioned to guide architectural decisions, modernization priorities and risk management. The challenge isn’t a lack of expertise — it’s that too much of that expertise is applied to migration mechanics rather than higher-value planning and execution.

Finding that balance depends on where AI is applied, how decisions are governed and how modernization progresses without disrupting proven operating models.

This is where agentic AI changes the equation.

How agentic AI transforms cloud migration and modernization

Rackspace approaches cloud migration not as a one-time event, but as a modernization journey. By structuring migration processes around agentic AI capabilities, we’re able to apply automation where it delivers the most impact while keeping architectural judgment, governance and business decisions firmly in human hands.

For organizations running VMware environments, this model supports modernization on AWS without forcing immediate architectural change. VMware services on AWS provide continuity and operational familiarity, while agentic AI accelerates the analysis, planning and execution required to move forward with confidence.

Rather than replacing expertise, agentic AI is designed to amplify it. AI agents can support modernization across the migration lifecycle by taking on data-intensive analysis and repeatable tasks, while we remain accountable for strategy, sequencing and risk management across four phases:

• Assess
• Mobilize
• Migrate and modernize
• Day two operations

Assessment often accounts for a meaningful portion of overall migration timelines, particularly in complex or VMware-based environments. As you move into this phase, discovery workshops and portfolio analysis generate large volumes of technical and operational data that must be reviewed and interpreted before planning can move forward.

In this phase, Rackspace migration consultants lead structured discovery workshops, including the Migration Readiness Assessment (MRA) and Migration Portfolio Assessment (MPA), to gather input across applications, infrastructure and business priorities.

Once discovery is complete, AI agents analyze workshop outputs and supporting documentation to surface patterns, risks and readiness gaps that would take human teams significantly longer to identify. These findings span both business and technical considerations, including organizational readiness issues and end-of-support operating systems that may influence migration and modernization decisions.

With portfolio data analyzed, AI agents can:

• Categorize applications and servers by complexity
• Propose migration approaches and wave sequencing
• Highlight candidates for modernization versus rehosting

Migration consultants review and refine these recommendations, applying business context and customer-specific requirements before plans are finalized.

AI agents can also use Model Context Protocol (MCP) servers to generate estimated cloud costs and total cost of ownership. Solutions architects validate assumptions, confirm estimates and support business case development and funding approvals.

Throughout the assessment phase, Rackspace experts remain directly engaged in workshops and planning discussions, helping your team understand the options available and the decisions that shape the path forward.

Mobilizing for migration at scale

Mobilization translates planning into executable work. This phase depends on a deliberate division of responsibility between human expertise and agentic AI so that your preparation moves quickly without sacrificing control or clarity.

Solutions architects lead activities that require architectural judgment and business insight, including documenting current and target states for each application and defining sequencing, standards and governance requirements.

AI agents then support mobilization by:

• Analyzing release plans and cross-checking dependencies
• Validating technical feasibility and sequencing
• Generating runbooks and deployment artefacts
• Deploying discovery agents and validating replication workflows
• Creating pre- and post-migration checks

All agent outputs are reviewed and validated by migration consultants before execution begins, maintaining quality control as preparation scales.

AI agents can also validate existing or greenfield landing zones against AWS security best practices and Well-Architected Framework principles. Migration governance, organizational alignment and stakeholder engagement remain human-led throughout.

Migrate and modernize at scale

Execution is where agentic AI helps scale migration and modernization activities while maintaining continuity and control, particularly for VMware environments.

For VMware-based workloads, Rackspace uses agent-driven automation alongside VMware HCX to support lift-and-shift migrations with minimal manual effort. By referencing previously captured application and infrastructure data, workloads can be moved individually or in batches using live vMotion while maintaining uptime.

For workloads modernizing toward native Amazon EC2, AWS Transform supports agent-assisted conversions. AI agents validate preparation steps, analyze collected data and document outcomes, while human oversight ensures business-critical workloads are sequenced appropriately and receive focused attention.

Modernization extends beyond infrastructure. For platform modernization scenarios, consultants lead the work while AI agents validate firewall rules, configurations and application-specific infrastructure builds. When deeper transformation is required, AI coding assistants such as Kiro and Amazon Q Developer support refactoring for cloud-native architectures, with human architects guiding design decisions and quality standards.

CloudOps for day two operations and beyond

Migration is not the end of the journey. Once workloads are running on AWS, Rackspace supports ongoing operations through AIOps designed to improve stability, responsiveness and operational efficiency.

AIOps agents can help reduce mean time to recovery by detecting failures, supporting incident response and initiating predefined recovery actions with limited manual intervention. These agents use retrieval-augmented generation (RAG) with runbooks stored in knowledge bases, providing the contextual understanding needed to respond in line with established operational practices.

This model supports a more proactive approach to operations, maintaining reliability and consistency across environments, while allowing your teams to focus on optimization, modernization and ongoing improvement rather than routine firefighting.

A technology foundation built on AWS best practices

To support this model in practice, we rely on a set of AWS services that are designed for secure, governed and scalable agent deployment. These services give you the ability to apply agentic AI across migration, modernization and operations while maintaining the security controls, observability and integration points your environment requires.

At a foundational level, this approach is built on:

• Amazon Bedrock AgentCore, which provides a secure execution environment for AI agents with IAM- and OAuth-based authentication, along with access to Model Context Protocol (MCP) servers through the AgentCore Gateway
• Amazon Strands Agents, which supply prebuilt tools for common migration and operations tasks, supporting consistent behavior and reducing the overhead required to design and manage agent workflows
• Amazon Bedrock Knowledge Bases, which store runbooks, best practices and operational knowledge in vector databases, enabling agents to use retrieval-augmented generation (RAG) for context-aware analysis and response

Together, these services allow agentic AI to operate within defined security boundaries while remaining flexible enough to support migration, modernization and day two operations at scale.

Expertise and automation working together

Across migration and modernization, agentic AI is applied alongside experienced delivery teams to support complex enterprise environments, including VMware estates running on AWS. Automation contributes consistency and scale, while architectural decisions, governance and execution remain guided by experienced practitioners throughout the journey.

As an AWS Premier Tier Services Partner, we ready to help eligible customers navigate AWS migration funding programs that can offset a portion of modernization costs. This support allows technical execution and business planning to move forward in parallel, without slowing momentum or sacrificing oversight.

If you’re planning a migration, there’s a more efficient path forward. Rackspace can help you move faster while maintaining the quality, control and oversight your organization requires. Learn more today.