I attended VMware PEX a couple of weeks back and during some of the sessions and discussions I had after the sessions I realized that many customers out there still design using legacy concepts. Funny thing is that this mainly applies to server virtualization projects and to a certain extend to cloud environments.It appears that designing in building blocks is something that EUC side of this world has embraced a long time ago.
I want to use this post to get feedback about your environments. How you scale up / scale out. I discussed a concept with one of the PEX attendees which I want to share. (This is no rocket science or something revolutionary, let that be clear.) This attendee worked for one of our partners, a service provider in the US, and was responsible for creating a scalable architecture for an Infrastructure as a Service (IaaS) offering.
The original plan they had was to build an environment that would allow for 10.000 virtual machines. Storage, networking and compute sizing and scaling was all done with these 10k VMs in mind. However it was expected that in the first 12 months only 1000 virtual machines would be deployed. You can imagine that internally there was a lot of debate around the upfront investment. Especially the storage and compute platform was a huge discussion. What if the projections where incorrect, what if 10k virtual machines was not realistic in three years. What if the estimated compute and IOps requirements where incorrect? This could lead to substantial underutilization of the environment, especially in IaaS where it is difficult to predict how the workload will behave this could lead to a significant loss. On top of that, they were already floor space constraint… which made it impossible to scale / size for 10k virtual machines straight from the start,
During the discussion I threw the building block (pod, stack, block… all the same) method on the table, as mentioned not unlike what the VDI/EUC folks have been doing for years and not unlike some of you have been preaching. Kris Boyd mentioned this in his session at Partner Exchange and let me quote him on this as I fully agree with his statemenet “If you know what works well on a certain scale, why not just repeat that?!” The advantage to that would be that the costs are predictive, but even more important for the customers and ops team the result of the implementation would be predictive. So what was discussed and what will be the approach for this particular environment, or at least will be the proposed as a possible architecture?
First of all a management cluster would be created. This is the mothership of the environment. It will host all vCenter virtual machines, vCloud Director, Chargeback, Databases etc. This environment does not have high IOps requirements or high compute requirements. It would be implemented on a small storage device, NFS based storage that is. The reason it was decided to use NFS is because of the fact that the vCloud Director cells require NFS to transport files. Chris Colotti wrote an article about when this NFS share is used, might be useful to read for those interested in it. This “management cluster” approach is discussed in-depth in the vCloud Architecture Toolkit.
For the vCloud Director resource the following was discussed. The expectation was a 1000 VMs in the first 12 months. The architecture would need to cater for this. It was decided to use averages to calculate the requirements for this environment as the workload was unknown and could literally be anything. How did they come up with a formula in this case? Well what I suggested was looking at their current “hosted environment” and simply averaging things out. Do a dump of all data and try to come up with some common numbers. This is what it resulted in:
- 1000 VMs (4:1 core / VM, average of 6GB memory per VM)
- Required cores = 250 (for example 21 x dual socket 6 core host)
- Required memory = 6TB (for example 24 x 256GB host)
This did not take any savings due to TPS in to account and the current hardware platform used wasn’t as powerful as the new one. In my opinion it is safe to say that 24 hosts would cater for these 1000 VMs and that would include N+2. Even if it did not, they agreed that this would be their starting point and max cluster size. They wanted to avoid any risks and did not like to push the boundaries too much with regards to cluster sizes. Although I believe 32 hosts is no problem at all in a cluster I can understand where they were coming from.
The storage part is where it got more interesting. They had a huge debate around upfront costs and did not want to invest at this point in a huge enterprise level storage solution. As I said they wanted to make sure the environment would scale, but also wanted to make sure the costs made sense. On average in their current environment the disk size was 60GB. Multiply that by a 1000 and you know you will need at least 60TB of storage. This is a lot of spindles. Datacenter floor space was definitely a constraint, so this would be huge challenge… unless you use techniques like deduplication / compression and you have a proper amount of SSD to maintain a certain service level / guarantee performance.
During the discussion it was mentioned several times that they would be looking at the upcoming storage vendors like Tintri, Nimble and Pure Storage. There were the three specifically mentioned by this partner, but I realize there are many others out there. I have to agree that the solutions offered by these vendors are really compelling and each of them have something unique. It is difficult to compare them on paper though as Tintri does NFS, Nimble iSCSI and Pure Storage HC (and iSCSI soon) but is also SSD only. Especially Pure Storage intrigued them due to the power/cooling/rackspace savings. Also the great thing about all of these solutions is again that they are predictable from a cost / performance perspective and it allows for an easy repeatable architecture. They haven’t made a decision yet and are planning on doing an eval with each of the solutions to see how it integrates, scales, performs and most importantly what the operational impact is.
Something we did not discuss unfortunately was networking. These guys, being a traditional networking provider, did not have much control over what would be deployed as their network department was in charge of this. In order to keep things simple they were aiming for a 10Gbit infrastructure, the cost of networking ports was significant and they wanted to reduce the amount of cables coming out of the rack for simplicity reasons.
All in all it was a great discussion which I thought was worth sharing, although the post is anonymized I did ask their permission before I wrote this up :-). I realize that this is by far a complete picture but I hope it does give an idea of the approach, if I can find the time I will expand on this with some more examples. I hope that those working on similar architectures are willing to share their stories.