By Lyubomir Lyubenov, Cloud Service Architect, VMware
One of the busiest areas at VMworld 2017 in Las Vegas is the Hands-on Lab (HOL), which gives our customers special access to test VMware technologies without needing to purchase equipment, software, or licenses.
Our requirements for the HOL infrastructure included the following:
- High performance and very scalable infrastructure
- Highly resilient, high available operations
- Capacity consumable by the VMware Learning Platform
- Ability to leverage existing private cloud monitoring tools
In 2017, we used a new VMWare public cloud offering, VMware Cloud on AWS, to run part of our workload. VMware Cloud on AWS is an on-demand service that integrates vSphere, vSAN, NSX, and VMware vCenter management and runs on dedicated, elastic, bare-metal AWS infrastructure and is powered by VMware Cloud Foundation.
VMC is a perfect choice for a public burst use case like HOL because it gives us the ability to add large amounts of capacity on-demand when we need it. We can literally scale up or down within hours. This blog explores how we architected our HOL to use VMware Cloud on AWS as part of the VMworld labs.
We used VMC along with private cloud and other public cloud resources during VMworld, then scaled it back down. Just prior to VMworld, we increased from one to five clusters with just a few clicks. We were able to scale up the environment and add more capacity one day, test it the next day, and run it as production on the third day.
The HOL team consumed the cloud infrastructure through the VMware Learning Platform. The whole event was served from our private cloud, cloud capacity from our partners and VMware Cloud on AWS.
Our architecture was focused on performance and resiliency. We deployed multiple SDDCs within VMC, so that if there was a failure, the impact was confined to and managed within the particular SDDC. Each VMC SDDC was scaled up to eight hosts. And because each SDDC was designed and deployed exactly the same way, we could easily plan our capacity consumption model and have it scale as expected. This also guaranteed predictable performance.
Since every SDDC has its own dedicated vCenter, we could push a lot more concurrent tasks against that environment, which significantly improved our content provisioning times as well.
A star-like VPN network topology was adopted to connect the first, or main SDDC, to the remaining VMC SDDCs. We used VPN tunnels to communicate among SDDCs. Each SDDC also had a second VPN tunnel connected directly back to VMware for centralized management and monitoring. The cloud management platform components were deployed in the main SDDC and all VMware Cloud on AWS SDDCs were managed through it.
VMware Cloud on AWS performed extremely well as part of our HOL environment, with no surprises. In fact, it performed better than the other environments. For example, a single VMware Cloud on AWS cluster could produce around 235K IOPS during our storage performance testing, while a similar size cluster in our on-premises infrastructure produced around 150K IOPS. This was a significant storage performance boost for VMware Cloud on AWS that we didn’t expect.
We experienced firsthand how quickly and easily we could scale capacity on demand and be confident that it would work as expected. When VMworld was over, we immediately decommissioned the extra capacity with a few clicks and avoided having potentially idle infrastructure. Another benefit was that we didn’t need to worry about doing maintenance and software upgrades in VMware Cloud on AWS; those were handled by the VMware support team. This saved us a significant amount of time and effort.
It took time to build up confidence that this service would work as expected. Given our experience so far, we expect VMware Cloud on AWS to play a major role in our HOL environment for VMworld and other events in 2018. We look forward to sharing more about our experiences with this service in future blogs.
To learn more, read these VMware Cloud on AWS blogs:
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