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NIX United helped a US-based industrial IoT software provider migrate VMware to AWS using an AI-enabled engineering approach. The project reduced migration time to approximately 2 days instead of an estimated 10–12 weeks, while minimizing downtime and building a scalable AWS foundation.
Internet Services and Computer Software
AWS, Data Engineering, Cloud Services, Cloud Migration
AWS Transform, AWS MGN, Amazon EC2
Our client is a US-based provider of industrial IoT software used by manufacturers to monitor connected equipment and analyze real-time operational data. Rapid growth in their customer base created a critical need for scalable infrastructure and lower operational costs. However, their existing VMware environment had become too expensive to maintain and too rigid to support modern demands.
The company needed to migrate VMware to AWS quickly, while curbing risks, reducing cutover time, and lowering long-term expenses without impacting service availability. They selected NIX United for our deep AWS expertise and unique ability to combine solid engineering practices with AI-enabled automation that accelerates the migration timeline.
Our key objectives included:
Outdated infrastructure documentation and complex application dependencies made the VMware migration a high-risk project. We needed full visibility into thousands of interconnected workloads, applications, and network connections while working against a tight deadline. Our AI-enabled engineering approach helped eliminate blind spots, prevent costly errors, and optimize the target environment for efficient cloud operations—all within the established timeframe.
To bypass the slow planning and heavy manual labor of traditional lift-and-shift, NIX United combined expert cloud engineering with AI-driven automation via AWS Transform. This way, we managed to streamline VMware replication to AWS and accelerate the overall migration process without compromising security, reliability, or production readiness.
NIX engineers used AWS Transform to automatically analyze the client’s VMware environment, discovering workloads, infrastructure configurations, and application dependencies. By letting AI handle the heavy data processing, our team eliminated days of manual inventory reviews and focused on refining the overall strategy.
Our architects validated all AI-generated insights, identified edge cases, and grouped workloads into logical, prioritized execution phases based on business urgency and technical complexity—reducing uncertainty before execution.
This approach enabled us to:
With the migration strategy in place, the NIX team moved 60 VMware virtual machines to Amazon EC2 using AWS Transform together with AWS Application Migration Service (MGN).
We automated infrastructure discovery, workload replication, and migration orchestration while carefully executing staged cutovers to minimize business disruption. Throughout the project, our engineers monitored replication progress, validated migrated workloads, and performed post-migration testing to ensure the application runs as expected.
Recreating the client’s networking environment in AWS was one of the most critical migration stages. Using AWS Transform, we automatically translated VMware networking and security configurations into AWS-native infrastructure, including VPCs, Security Groups, and Route Tables.
We didn’t rely solely on AI automation: our cloud engineers meticulously reviewed, refined, and validated every generated configuration. This way, we could guarantee perfect alignment with the client’s strict security, connectivity, and operational standards.
As a result, we were able to:
We focused on optimizing the target environment right from the start, using actual workload behavior. AWS Transform analyzed historical CPU, memory, and workload utilization to recommend perfectly sized Amazon EC2 instances, eliminating unnecessary overprovisioning.
Our cloud architects then evaluated every recommendation and adjusted resource allocation to ensure each workload matched real business requirements, leaving behind legacy infrastructure inefficiencies.
This approach allowed the client to:
Beyond migrating workloads, our team established a scalable AWS-native foundation designed to support long-term growth and innovation.
The migration eliminated the company’s dependence on VMware licensing and removed vendor lock-in while enabling seamless adoption of AWS-native services. The client can now take advantage of the advanced AWS ecosystem—including managed database, monitoring, security, and AI services—to accelerate future innovation while reducing operational overhead.
The new platform provides:
The NIX team guided the client through a complex migration of VMware workloads to AWS much faster than traditional manual approaches would have allowed. While AI accelerated data analysis, configuration mapping, and planning, our cloud architects maintained full control over technical validation and execution.
By using AI-enabled automation under strict expert oversight, we helped the company reduce operational costs, eliminate VMware vendor lock-in, and establish a scalable AWS foundation for future innovation.
60
VMware virtual machines successfully migrated to AWS
~2
days to complete the migration
< 10
minutes of downtime across migrated workloads
~60%
lower infrastructure costs
30–40%
estimated annual infrastructure savings
99.5%
infrastructure availability with AWS managed services
5 Experts (Cloud Solution Architect, 2 DevOps Engineers, Data Engineer, Project Manager)
Migration and Automation: AWS Transform (AI-enabled discovery and orchestration), AWS Application Migration Service (MGN)
Compute and Infrastructure: Amazon EC2, VMware vSphere
Infrastructure as Code (IaC): AWS CloudFormation
Networking and Security: AWS VPC, AWS Security Groups, Route Tables
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