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Modern applications are distributed and introduce complex challenges for Developers and IT Operators. Project Pacific, a technology preview, is a new evolution of the vSphere platform that tightly integrates a Kubernetes control plane with vCenter, ESXi (compute), networking, and storage. Project Pacific enables developers to use Kubernetes declarative state syntax and tools to self-service manage data center resources including containers, VMs, storage, and networks. This Kubernetes control plane is managed completely by vCenter, allowing IT operators to use their existing tools and skills to manage modern applications.
Personnel: Jared Rosoff
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Modern applications are distributed and introduce complex challenges for Developers and IT Operators. Project Pacific, a technology preview, is a new evolution of the vSphere platform that tightly integrates a Kubernetes control plane with vCenter, ESXi (compute), networking, and storage. Project Pacific enables developers to use Kubernetes declarative state syntax and tools to self-service manage data center resources including containers, VMs, storage, and networks. This Kubernetes control plane is managed completely by vCenter, allowing IT operators to use their existing tools and skills to manage modern applications.
Personnel: Jared Rosoff
Watch on YouTube
Watch on Vimeo
Modern applications are distributed and introduce complex challenges for Developers and IT Operators. Project Pacific, a technology preview, is a new evolution of the vSphere platform that tightly integrates a Kubernetes control plane with vCenter, ESXi (compute), networking, and storage. Project Pacific enables developers to use Kubernetes declarative state syntax and tools to self-service manage data center resources including containers, VMs, storage, and networks. This Kubernetes control plane is managed completely by vCenter, allowing IT operators to use their existing tools and skills to manage modern applications.
Personnel: Michael West
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With enterprises’ growing adoption of AI, ML, and analytics workloads, GPUs and FPGAs are becoming integral infrastructure parts to provide the timely results required by business-critical apps. For IT admins, this means satisfying a growing demand for elastic and virtual infrastructure to support more apps and users.
Discussion about Bitfusion, vSphere’s recent acquisition, to learn how its software turns GPUs and FPGAs into a shared network-attached virtual GPU and FPGA pool, responding in real time to workload demand.
Personnel: Mazhar Memon
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With enterprises’ growing adoption of AI, ML, and analytics workloads, GPUs and FPGAs are becoming integral infrastructure parts to provide the timely results required by business-critical apps. For IT admins, this means satisfying a growing demand for elastic and virtual infrastructure to support more apps and users.
Discussion about Bitfusion, vSphere’s recent acquisition, to learn how its software turns GPUs and FPGAs into a shared network-attached virtual GPU and FPGA pool, responding in real time to workload demand.
Personnel: Mazhar Memon
Watch on YouTube
Watch on Vimeo
With enterprises’ growing adoption of AI, ML, and analytics workloads, GPUs and FPGAs are becoming integral infrastructure parts to provide the timely results required by business-critical apps. For IT admins, this means satisfying a growing demand for elastic and virtual infrastructure to support more apps and users.
With Bitfusion and vSphere, see how to get the best of both worlds: a robust SDDC with ML/AI workloads in VMs or containers dynamically consuming any amount of GPU (partial, multiple, local, remote) while preserving those workloads’ ability to leverage vSphere vMotion and Distribution Resource Scheduler (DRS).
Personnel: Jim Brogan
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With enterprises’ growing adoption of AI, ML, and analytics workloads, GPUs and FPGAs are becoming integral infrastructure parts to provide the timely results required by business-critical apps. For IT admins, this means satisfying a growing demand for elastic and virtual infrastructure to support more apps and users.
With Bitfusion and vSphere, see how to get the best of both worlds: a robust SDDC with ML/AI workloads in VMs or containers dynamically consuming any amount of GPU (partial, multiple, local, remote) while preserving those workloads’ ability to leverage vSphere vMotion and Distribution Resource Scheduler (DRS).
Personnel: Ziv Kalmanovich
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