A structured handoff for cloud architects, AI builders, and data leaders. Direct workspace planning with infrastructure specialists.
WHAT YOU’LL GET
- Architecture path
- Assumptions to validate
- Next best action
Connect with an AI specialist
Let's outline your scale, pipeline, and hybrid target.
Zero commitment. Clean data privacy standards guaranteed.
Talk to an architect
AI workloads expose the gap between data location and compute demand
AI infrastructureleaders
Teams aligning high-throughput storage pipelines with raw GPU processing demands.
Cloudarchitects
Architects mapping native public cloud endpoints to primary physical storage fabrics.
Dataleaders
Managers architecting compliance, snapshot rhythms, and enterprise file protection layers.
Storagearchitects
Engineers migrating workloads or tuning hybrid infrastructure topologies.
WHAT YOU GET
Let’s focus on ranges, keeping sensitive data out of the conversation
We do not need exact file paths or private structures. Approximate ranges of your workload size, data frequency, and cloud targets are more than enough to draft a concrete, actionable blueprint.
Helpful inputs
General workload type (AI training, virtualization, backup)
Approximate active data scale (TB/PB ranges)
Current GPU estate or public cloud compute goals
Existing network throughput limits or hurdles
Customer proof
Customer success stories
Modernization is essential. To support AI in design, production, and delivery, we needed a data foundation that's intelligent and future-ready.
Attribution: Jagdish Joshi, Principal of Technology Infrastructure, Mahindra
NetApp’s strategic partnership with Kyndryl enables joint delivery of critical data infrastructure services that will accelerate future innovation and business impact for customers and fast track cloud adoption.
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