by Duncan Epping
I just cloned PhotonOS a few times for running “Folding at Home” in our lab, and I noticed every VM was getting the same IP address every time. It appears that this is caused by the fact that when you clone the VM they all have the same machine identifier. You can get around this by running the following command within the PhotonOS console:
echo -n > /etc/machine-id
I hope that helps those planning on running PhotonOS at home, lab, or in production as well.
There was a great article by Cormac talking about vSAN File Services published last week. I had some articles planned, but hadn’t started yet, so when I saw the article I figured I would do something different. No point in rehashing what Cormac has already shared right. I figured I would shoot another demo, and do a brief write-up so people know what vSAN File Services is all about. In vSAN/vSphere 7.0 there’s now a new feature, and this is vSAN File Service. vSAN File Services can simply be enabled on a cluster level and provides you NFS 3 and 4.1 capabilities. The great thing about the solution is that you can create file shares and associate policies with the file shares. In other words, you can have a file share with RAID-1, RAID-5, or maybe even striping or stretched across locations when that is supported.
When you enable File Service, vSAN will deploy a number of “agent VMs” and these VMs/appliances are fully managed by vSAN. These agent VMs run Photon OS and have the file service capabilities enabled through docker/container technology. After these File Service Agent VMs have been deployed, the docker container instances have been instantiated and configured, vSAN File Service will be up and running and available for use. Next, you could simply create a file share and start consuming it. But before I reveal everything, let’s just head over to the demo below. I hope you enjoy it!
I wrote a post and recorded a short demo that explained this cool new feature called Scalable Shares, part of vSphere 7 / DRS, last week. I didn’t want to go too deep in the post, but now that I am getting more questions about how this actually works, I figured I would provide some examples to explain it. As mentioned in my previous post, Scalable Shares solves a problem many have been facing over the last decade or so, which is that DRS does not take the number of VMs in the pool into account when it comes to allocating resources. So as an example:
Just imagine you have a resource pool called “Test”, it is a resource pool with “normal” shares and has 4 VMs. Let’s say this resource pool has 4000 shares.
Now compare that resource pool to the “Production” pool, which has shares set to “high” but has 24 VMs. Let’s say this resource pool has 8000 shares.
This is a very extreme example, but it shows you immediately what the problem is. On a per VM basis, the VMs in the production resource pool, would receive far less resources when there’s contention as DRS would simply divvy up the resources based on the assignment of the shares of the resource pool. Test would receive 1/3 of the resource (4000 of 12000 total shares), and production would receive 2/3 of the resources (8000 of 12000 total shares). If you would divide that by the number of VMs in each pool, it is obvious that the VMs in Test are in a better situation than the VMs in Production.
So how would this work if you Scalable Shares enabled? Well, let’s list some facts first:
The calculation would be as following:
Resource Pool Shares = (4 vCPU * Shares of Pool )* (Total number of shares of all vCPUs in resource pool)
So as an example, in the case I have Test with normal shares and 4 VMs, and Production with high shares and 24 VMs, and all VMs have a single vCPU with normal priority the calculation for those two resource pools would be:
Test = (4 * 1000) * (4 * 1000) = 16,000,000 shares
Production = (4 * 2000) * (24 * 1000) = 192,000,000 shares
In other words, Production has 12 times more the number of shares as Test has when Scalable Shares is enabled. I hope that clears things up!
Early 2015 Frank Denneman and I had a discussion during a flight to San Francisco. We came up with this concept for Resource Pools where the number of shares would be determined by the number of VMs and the priority of the pool. In other words, we wanted to avoid the dilution of shares in an environment with resource pools and basically solve the resource pool pie paradox problem described here. We worked with the DRS team on describing the concept, we filed a patent for it and got the patent granted in 2019. Today I am happy to share that the feature made it into a release and will be part of vSphere 7.0.
Scalable Shares is a feature that is part of DRS. You either enable it on the Cluster or you enable it on the Resource Pool. Personally I would always enable it on the Resource Pool level. So how does it work? Well normally when you create a resource pool with High Priority and one with Normal Priority, the RP with Priority High will have 8000 shares and the RP with Priority Normal will get 4000 shares. In other words, a 2:1 ratio between High and Normal. Now if you have 8 VMs in High and 1 in Normal, you can imagine that this single VM in Normal will get more resources than the 8 in High when there is contention simply as the 8 share the resources of the pool while the single VM doesn’t share the resources.
When Scalable Shares is enabled, DRS does a calculation using the ratio (4:2:1 – High:Normal:Low) and the number of VMs. In other words, 8 VMs with a 1000 shares in High would be *4, and 1 VM with a 1000 shares in Normal would be *2. The result being:
I hope that makes a bit sense? It took me a while to fully grasp. If you are wondering what this looks like in the product, and what the impact could/would be when you switch from “traditional” to “scalable shares”, I created a demo that shows this below.
Today is the last day of my Take 3 with the Project VXR team. Ridiculous how fast these 3 months went. It seems like only yesterday that I posted I was going to start this journey of learning more about the world of Spatial Computing and Remote Rendering of VR in particular. If I say so myself, I feel that over the past 3 months I managed to accomplish quite a lot. The last three months I spend figuring out how to virtualize a Virtual Reality application and how to stream the application to a head-mounted display. I tested different solutions in this space, some of which I discussed on my blog in the past months, and I was surprised how smooth it worked, to be honest. If you are interested in this space, my recommendation would be to look into NVIDIA CloudXR in combination with vSphere 6.7 U3 and NVIDIA vGPU technology.
I can’t share all the details just yet, I wrote a white paper, which now needs to go through reviews and copy editing, and hopefully, it will be published soon. I will, however, discuss some of my findings and my experience during some of the upcoming VMUGs I will be presenting at. Hopefully, people will enjoy it and appreciate it.
One thing I would like to do is thank a few people who helped me tremendously in the past few months. First of all, of course, the folks on the Project VXR team, they gave me all the pointers/hints/tips I needed and shared a wealth of knowledge on the topic of spatial computing. I also like to thank Grid Factory, Ben in particular, for the many discussions, emails etc that we had. Of course also NVIDIA for the discussions and help around the lab equipment. Last but not least, I want to thank the VMware OCTO team focussing on Dell Technologies for providing me with a Dell Precision Workstation, and shipping it out literally within a day or two. Much appreciated everyone!
Now it is time to get back to reality.
