VMware and Google Cloud: building the hybrid cloud together with vRealize Orchestrator

Many of our customers with hybrid cloud environments rely on VMware software on-premises. They want to simplify provisioning and enable end-user self service. At the same time, they also want to make sure they’re complying with IT policies and following IT best practices. As a result, many use VMware vRealize Automation, a platform for automated self-service provisioning and lifecycle management of IT infrastructure, and are looking for ways to leverage it in the cloud.

Today, we’re announcing the preview of our plug-in for VMware vRealize Orchestrator and support for Google Cloud Platform (GCP) resources in vRealize Automation. With these resources, you can now deploy and manage GCP resources from within your vRealize Automation environment.

The GCP plug-in for VMware vRealize Orchestrator provides a consistent management and governance experience across on-premises and GCP-based IT environments. For example, you can use Google-provided blueprints or build your own blueprints for Google Compute Engine resources and publish to the vRealize service catalog. This means you can select and launch resources in a predictable manner that is similar to how you launch VMs in your on-premises VMware environment, using a tool you’re already familiar with.

This preview release allows you to: 

• Create vRealize Automation “blueprints” for Compute Engine VM Instances
• Request and self-provision resources in GCP using vRA’s catalog feature
• Gain visibility and reclaim resources in GCP to reduce operational costs
• Enforce access and resource quota policies for resources in GCP
• Initiate Day 2 operations (start, stop, delete, etc.) on Compute Engine VM Instances, Instance Groups and Disks

1. Reach new regions to address global business needs. (Hello Finland, Mumbai and Singapore.)
2. Define large-scale applications using vRA and deploy to Compute Engine to leverage GCP’s worldwide load balancing and automatic scaling.
3. Save money by deploying VMs as Compute Engine Preemptible VM Instances and using Custom Machine Types to tailor the VM configuration to application needs.
4. Accelerate the time it takes to train a machine learning model by using Compute Engine with NVIDIA® Tesla® P100 GPUs.
5. Replicate your on premises-based applications to the cloud and scale up or down as your business dictates.

In the meantime, to join the preview program, please submit a request using the preview intake form.