Vector cuts cloud migration time by 34% using AWS Transform for VMware

Serving over 628,000 residential and commercial customers, Vector Limited is the country’s largest distributor of electricity and gas. Since 2020, the company has pursued a cloud-first strategy, modernizing its technology environment while retaining certain on-premises workloads to meet industry regulations.

As part of this journey, Vector adopted VMware Cloud (VMC) on AWS to support key systems and provide a stable environment during its digital transformation. With a long-term goal of moving to native AWS services to support agility, automation, and cost optimization, Vector viewed VMC as a practical step in its modernization roadmap. As the renewal of its VMC licensing approached, the company recognized an opportunity to advance its roadmap and fully transition to AWS. Jerry Li, general manager of digital technology at Vector, says, “VMC was always part of our strategy—it gave us a flexible environment to operate in while we avoided large hardware reinvestments. It helped us focus on modernization at our own pace before moving to native AWS services.”

With time constraints increasing, and based on its experience with previous VMware migrations, the company sought a more efficient, automated approach that would reduce manual effort and risk.

To accelerate this transition, Vector turned to AWS Partner Slalom, a long-standing collaborator with a deep understanding of the company’s infrastructure and cloud strategy. During early planning discussions, Slalom proposed using AWS Transform for VMware, an agentic AI–powered service designed to automate and streamline VMware-to-AWS migrations.

Although AWS Transform for VMware was still in public preview, Vector was able to move quickly thanks to its close collaboration with Slalom. As an AWS Premier Partner under a global Strategic Collaboration Agreement, Slalom had early access to the service and was well positioned to lead its implementation. Maria Sokolova, director of cloud capability at Slalom, says, “These are the moments when selected AWS Partners with deep strategic alignment have an advantage—we gain early access to the latest AWS services, enabling our customers to start deploying and realizing value much sooner.”

AWS Transform for VMware had an immediate impact on the migration process. Traditionally, migrations have relied heavily on manual work, including document reviews, inventory collection, and application mapping. However, with AWS Transform for VMware, the AI agents automate these tasks and more, such as network conversion and right-sizing Amazon Elastic Compute Cloud (Amazon EC2) instances for each migrated workload. The solution also handled wave planning—the process of grouping virtual machines into migration batches based on application dependencies and technical requirements. This helped Vector coordinate a phased migration approach aligned with system readiness and business continuity.  

Powered by an agentic AI–based approach and AWS Transform for VMware, the migration was completed 34 percent faster than previous VMC efforts and delivered 35 percent cost savings over a five-year TCO. It also freed internal teams to focus on higher-value initiatives.

Wave planning saw one of the biggest gains. A task that once took days or weeks now finishes in minutes with agentic AI, which automated about 60 percent of the work. The team only needed to add business-critical details like outage windows and test schedules. This automation enabled a faster migration timeline.

Vector has also built a foundation for a more flexible and automated technology environment by scaling infrastructure-as-code, refining DevOps pipelines, and expanding serverless compute adoption. These changes streamlined operations, cut overhead, and boosted infrastructure team effectiveness by 30 percent, freeing up 17 percent more time for higher-value work in planning, orchestration, architecture, and innovation.

“Automation is a priority for us,” says Li. “It eliminates burdensome tasks for employees and lowers the cost of experimenting, fostering a culture of innovation.” With enhanced observability and system-level visibility, the team can resolve issues faster, reduce long-term technical debt, and explore generative AI tools to strengthen its peer programming model with automated test creation and intelligent code assistance.

The migration has also unlocked new opportunities for optimization. “By optimizing our cloud infrastructure, we have the opportunity to deliver even greater impact back to the business. With AWS, we gain near-real-time visibility and the agility to continually refine and improve—turning technology into a true enabler of growth and innovation,” concludes Li.