Google Cloud VMware Engine Simulator
Model Google Cloud VMware Engine scenarios in seconds
Google’s release of Google Cloud VMware Engine (GCVE) brings about a new era in cloud migration. With GCVE, customers can migrate VMware workloads to a native VMware environment running in Google Cloud, benefiting from Google Cloud strengths, including Google’s secure and scalable global infrastructure and leading data analytics, AI, and ML capabilities. With GCVE, users will have access to the full VMware Cloud Foundation stack including ESXi, vCenter, vSAN, NSX-T and HCX.
CloudPhysics accelerates your migration by finding and simulating the ideal infrastructure size and providing a wide array of storage and fault recovery options. Using the CloudPhysics simulator, customers can quickly find the ideal cluster size for any grouping of VMs in their current data centers modeled against the Google Cloud options. CloudPhysics allows customers to model unique Failures to Tolerate scenarios for vSAN storage as well as allowing customers to account for data redundancy and oversubscription scenarios. Combined with cloud storage options, customers can quickly model and simulate their current environment on the host shapes and geographies provide by Google
Leverage the CloudPhysics Google Cloud VMware Engine Simulator to model and plan the placements of workloads in the Cloud. With limitations on total storage per vSAN and the number of hosts in a cluster, CloudPhysics can calculate the number of clusters and VPC’s required to accommodate your GCVE environment.
- Determine the cost of your environment dynamically and in real-time based on selected VMs and resources. Export these cost models for runbooks or cost comparison offline.
- Model workloads in GCVE based on Failures to Tolerate, capacity growth, deduplication and compression estimates, and over subscription ratios.
- Incorporate VMware Horizon planning to allow for capacity planning of Windows Desktops.
- Scale cluster size and cost based on Failures to Tolerate (FTT) and Raid options.
- Rightsize clusters for future growth by incorporating additional headroom for vCPUs, vRAM, and vSAN storage.
- Include secondary storage for large data volumes and high-performance applications on partner cloud storge solutions by the TB.
- Calculate commitment costs for On-Demand usage in weeks or commitments in 1- and 3-year terms.
- Get itemized placement data sheets on where each workload ideally fits in initial deployments across multiple clusters and VPCs.
CloudPhysics Google Cloud VMware Engine benefits include
- Calculate host counts and cost of hosting workload in GCVE
- Host packing engine to determine the ideal number of servers required for current workloads.
- Ability to scale up CPU, RAM, and storge to accommodate future growth
- Visibility into how differing Failures To Tolerate (FTT) storage models within vSAN will impact host count and cost
- Gain historical visibility into performance and capacity changes to determine peak usage of all resources. Use this data to find constraints on-premsies and avoid bottlenecks in the cloud
- SaaS based analytics require no compute or storage on premises
- Collaborative tools allow monitoring by customers and partners to ensure both parties are planning a cloud migration together