The News
Google Cloud and Nutanix announced the general availability of Nutanix Cloud Clusters (NC2) on Google Cloud, enabling enterprises to run Nutanix Hybrid Cloud environments natively on Google Compute Engine. Organizations can migrate and modernize regulated, mission-critical, and specialized workloads without refactoring, while gaining access to Google Cloud’s AI, data, and workload-optimized compute capabilities.
Analysis
Hybrid Cloud Enters Its AI-Ready Phase
The availability of NC2 on Google Cloud marks a meaningful shift in how enterprises can approach modernization. Instead of forcing a binary choice between staying on-premises or adopting cloud-native architectures, organizations now gain a pathway that preserves operational consistency while unlocking cloud elasticity and AI integration. This hybrid continuity (same hypervisor, same networking constructs, same operational workflows) may reduce the friction that typically slows cloud adoption.
ECI Research data shows that many enterprises remain in hybrid models by necessity, not preference. More than half operate across mixed environments, and complexity, risk, and migration effort continue to delay modernization initiatives. NC2 on Google Cloud aims to target this tension by allowing workloads to move without architectural redesign. At the same time, tight integration with Google Cloud’s AI stack responds to a major market gap: while organizations are eager to adopt GenAI, legacy systems often keep their most valuable data locked behind infrastructure that is difficult to transform.
A Unified Operational Model with Direct Paths to AI and Analytics
At the core of this announcement is a simple value proposition: enterprises can extend Nutanix environments into Google Cloud while maintaining the same management plane, security posture, and automation workflows they already depend on. Running NC2 directly on Google’s new C4 and Z3 bare metal families provides high-density compute and NVMe-rich storage, potentially enabling performance-sensitive enterprise workloads to migrate without degradation.
From an application development and AI perspective, the significance lies in proximity. Applications running on NC2 can now connect with low latency to services like BigQuery, Vertex AI, Gemini Enterprise, and Dialogflow. This co-location effect could give organizations the ability to integrate AI models with transactional workloads, logs, and operational datasets without introducing brittle pipelines or heavyweight re-architecting. AppDev teams may gain opportunities to layer AI-driven capabilities on top of stable, trusted systems that historically existed outside the reach of cloud-native analytics.
Market Challenges and Insights
Enterprises continue to grapple with the operational cost of maintaining separate on-prem and cloud stacks. Fragmented security controls, divergent tooling, and inconsistent skill coverage all contribute to the friction that has slowed hybrid modernization for years. Our findings reinforce this reality; operational complexity, integration challenges, and governance gaps remain top inhibitors to scaling cloud-native and AI initiatives. NC2 on Google Cloud offers a pragmatic response by collapsing these operational divides rather than forcing a full architectural rewrite.
The announcement also highlights an increasing enterprise expectation for AI-accessible infrastructure. As AI becomes more deeply embedded into modernization strategies, organizations require hybrid platforms that bring compute performance, data governance, and AI proximity together. NC2’s integration with Google Cloud may advance this shift by making traditional workloads visible and usable to modern AI systems.
The Developer Approach
Developers working within hybrid environments may see NC2 on Google Cloud as a bridge that allows gradual modernization instead of disruptive rewrites. Being able to run unchanged workloads on Nutanix while tapping directly into BigQuery or Vertex AI may encourage teams to build AI-enhanced extensions rather than full migrations. This could lead to expanded use of conversational interfaces, predictive analytics, and real-time insights layered on top of legacy enterprise systems.
Over time, teams may also gravitate toward hybrid architectures that allow cloud elasticity, such as capacity bursting or DR orchestration, without losing the deterministic performance and governance properties of their on-prem estates. For many developers and platform teams, this offers a more manageable and lower-risk approach to modernization than immediate cloud-native conversion.
Looking Ahead
A Convergence Point for Hybrid Infrastructure and AI Modernization
With NC2 now generally available across 17 Google Cloud regions, the platform creates a clearer runway for organizations seeking to modernize with AI while preserving operational continuity. As Google continues expanding AI and bare-metal capabilities and as Nutanix pushes deeper into hybrid orchestration, the convergence of data, compute, and AI across a unified operational model is likely to accelerate.
What This Means for Nutanix and Google Cloud
This partnership positions Nutanix as a central layer in hybrid AI modernization strategies and strengthens Google Cloud’s appeal to organizations with specialized or tightly regulated workloads. Future developments may include deeper AI-native integrations, more automated migration tooling, and broader multi-cloud extensions as enterprises demand platforms that support modernization at their own pace.
Akuity Expands GitOps Beyond Kubernetes
Nutanix NC2 Becomes Generally Available on Google Cloud
Axonis Exits Stealth with Federated AI Architecture
Google Extends MCP Across Cloud Services
Databricks Advances Agentic AI with Agent Bricks and Unity Catalog Governance
