Optimizing VMware migration workflows with Agent AI

by SkillAiNest

For years, many chief information officers (CIOs) viewed VMware-to-cloud migration with cautious pragmatism. Manually mapping dependencies and rewriting legacy apps was not an attractive, low-lift proposition for mid-flight enterprise IT teams.

But the calculus for such decisions has changed dramatically in a short time. After recent VMware licensing changes, organizations are seeing more uncertainty about the future of the platform. At the same time, cloud-native innovation is accelerating. According to CNCF’s 2024 Annual Surveyfor , for , for , . 89% of organizations have already adopted at least some cloud-native techniques, and the share of companies reporting nearly all development and deployments as cloud-native has grown rapidly from 2023 to 2024 (20% to 24%). and market research firms IDC reports They have become top strategic partners for cloud provider productivity AI initiatives.

All this is happening amid increasing pressure to innovate faster and more cost-effectively to meet the demands of an AI-first future. As enterprises prepare for this inevitability, they are facing compute demands that are difficult, if not prohibitively expensive, to maintain exclusively on premises.

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This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by the editorial staff of MIT Technology Review.

This content was researched, designed and created by human authors, editors, analysts, and writers. This includes writing the survey and collecting data for the survey. The AI ​​tools that have been used were limited to secondary production processes that passed full human review.

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