What is static overhead memory?

We had a discussion internally on static overhead memory. Coincidentally I spoke with Aashish Parikh from the DRS team on this topic a couple of weeks ago when I was in Palo Alto. Aashish is working on improving the overhead memory estimation calculation so that both HA and DRS can be even more efficient when it comes to placing virtual machines. The question was around what determines the static memory and this is the answer that Aashish provided. I found it very useful hence the reason I asked Aashish if it was okay to share it with the world. I added some bits and pieces where I felt additional details were needed though.

First of all, what is static overhead and what is dynamic overhead:

  • When a VM is powered-off, the amount of overhead memory required to power it on is called static overhead memory.
  • Once a VM is powered-on, the amount of overhead memory required to keep it running is called dynamic or runtime overhead memory.

Static overhead memory of a VM depends upon various factors:

  1. Several virtual machine configuration parameters like the number vCPUs, amount of vRAM, number of devices, etc
  2. The enabling/disabling of various VMware features (FT, CBRC; etc)
  3. ESXi Build Number

Note that static overhead memory estimation is calculated fairly conservative and we take a worst-case-scenario in to account. This is the reason why engineering is exploring ways of improving it. One of the areas that can be improved is for instance including host configuration parameters. These parameters are things like CPU model, family & stepping, various CPUID bits, etc. This means that as a result, two similar VMs residing on different hosts would have different overhead values.

But what about Dynamic? Dynamic overhead seems to be more accurate today right? Well there is a good reason for it, with dynamic overhead it is “known” where the host is running and the cost of running the VM on that host can easily be calculated. It is not a matter of estimating it any longer, but a matter of doing the math. That is the big difference: Dynamic = VM is running and we know where versus Static = VM is powered off and we don’t know where it might be powered!

Same applies for instance to vMotion scenarios. Although the platform knows what the target destination will be; it still doesn’t know how the target will treat that virtual machine. As such the vMotion process aims to be conservative and uses static overhead memory instead of dynamic. One of the things or instance that changes the amount of overhead memory needed is the “monitor mode” used (BT, HV or HWMMU).

So what is being explored to improve it? First of all including the additional host side parameters as mentioned above. But secondly, but equally important, based on the vm -> “target host” combination the overhead memory should be calculated. Or as engineering calls it calculating “Static overhead of VM v on Host h”.

Now why is this important? When is static overhead memory used? Static overhead memory is used by both HA and DRS. HA for instance uses it with Admission Control when doing the calculations around how many VMs can be powered on before unreserved resources are depleted. When you power-on a virtual machine the host side “admission control” will validate if it has sufficient unreserved resource available for the “static memory overhead” to be guaranteed… But also DRS and vMotion use the static memory overhead metric, for instance to ensure a virtual machine can be placed on a target host during a vMotion process as the static memory overhead needs to be guaranteed.

As you can see, a fairly lengthy chunk of info on just a single simple metric in vCenter / ESXTOP… but very nice to know!

Guaranteeing availability through admission control, chip in!

I have been having these discussions with our engineering teams for the last year around guaranteed restarts of virtual machines in a cluster. In the current shape / form we use Admission Control to guarantee virtual machines are restarted. Today Admission Control is all about guaranteeing virtual machine restarts by keeping track of Memory and CPU resource reservations, but you can imagine that in the Software Defined Datacenter this could be expanded with for instance storage or networking reservation.

Now why am I having these discussions, what is the problem with Admission Control today? Well first of all it is the perception that many appear to have of Admission Control. Many believe the Admission Control algorithm uses “used” resources. Reality however is that Admission Control is not that flexible, it uses resource reservations and as you know this is static. So what is the result of using reservations?

By using reservations for “admission control” vSphere HA has a simple way of guaranteeing a restart is possible at all times. Simply because it checks if sufficient “unreserved resources” are available and if so it allows the virtual machine to be powered-on. If not, then it won’t allow the power-on just to ensure that all virtual machines can be restarted in case of a failure. But what is the problem? Although we guarantee a restart we do not guarantee any type of performance after the restart! Unless, unless of course you are setting your reservations equal to what you provisioned… but I don’t know anyone doing this as it eliminates any form of overcommitment and will result in an increase of cost and a decrease in flexibility.

So that is the problem. Question is – what should we do about it? We (the engineering teams and I) would like to hear from YOU.

  • What would you like admission control to be?
  • What guarantees do you want HA to provide?
  • After a failure, what criteria should HA apply in deciding which VMs to restart?

One idea we have been discussing is to have Admission Control use something like “used” resources… or for instance an “average of resources used” per virtual machine. What if you could say: I want to ensure that my virtual machines always get at least 80% of what they use on average? If so, what should HA do when there are not enough resources to meet the 80% demand of all VMs? Power on some of the VMs? Power on all with reduced share values?

Also, something we have discussed is having vCenter show how many resources are used on average taking your high availability N-X setup in to account, which should at least provide an insight around how your VMs (and applications) will perform after a fail-over. Is that something you see value in?

What do you think? Be open and honest, tell us what you think… don’t be scared, we won’t be bite, we are open for all suggestions.

What is: Current Memory Failover Capacity?

I have had this question many times by now, what is “Current Memory Failover Capacity” that is shown in the cluster summary when you have selected the “Percentage Based Admission Control Policy”? What is that percentage? 99% of what? And will it go down to 0%? Or will it go down to the percentage that you reserved? Well I figured it was time to put things to the test and no longer be guessing.

As shown in the screenshot above, I have selected 33% of memory to be reserved and currently have 99% of memory failover capacity. Lets power-on a bunch of virtual machines and see what happens. Below is the result shown in a screenshot, “current memory failover capacity” went down from 99% to 94%.

Also when I increase the reservation in a virtual machine I can see “Current Memory Failover Capacity” drop down even further. So it is not about “used” but about “unreserved / reserved” memory resources (including memory overhead), let that be absolutely clear! When will vCenter Server shout “Insufficient resources to satisfy configured failover level for vSphere HA”?

It shouldn’t be too difficult to figure that one out, just power-on new VMs until it says “stop it”. As you can see in the screenshot below. This happens when you reach the percentage you specified to reserve as “memory failover capacity”. In other words in my case I reserved 33%, when “Current Memory Failover Capacity” reaches 33% it doesn’t allow the VM to be powered on as this would violate the selected admission control policy.

I agree, this is kind of confusing…  But I guess when you run out of resources it will become pretty clear very quickly ;-)

 

Using das.vmmemoryminmb with Percentage Based admission control

I had question today about using the advanced settings to set a minimal amount of resources that HA would use to do the admission control math with. Many of us have used these advanced settings das.vmMemoryMinMB and das.vmCpuMinMHz to dictate the slot size when no reservations were set in an environment where the “host failures” admission control policy was used. However what many don’t appear to realize is that this will also work for the Percentage Based admission control policy.

If you want to avoid extreme overcommitment and want to specify a minimal amount of resources that HA should use to do the math with then even with the Percentage Based admission control policy you can use these settings. In the case where your VM reservation does not exceed the value specified, the value is used to do the math with. In other words if you set “das.vmMemoryMinMB” to 2048, it will use 2048 to do the math with unless the reservation set on the VM is higher.

I did a quick experiment in my test lab which I had just rebuilt. Without das.vmMemoryMinMB and two VMs running (with no reservation) I had 99% Mem Failover Capacity as shown in the screenshot below:

With das.vmMemoryMinMB set to 20480, and two VMs running, I had 78% Mem Failover Capacity as shown in the screenshot below:

I guess that proves that you can use das.vmMemoryMinMB and das.vmCpuMinMHz to influence Percentage Based admission control.

Why the world needs Software Defined Storage

Yesterday I was at a Software Defined Datacenter event organized by IBM and VMware. The famous Cormac Hogan presented on Software Defined Storage and I very much enjoyed hearing about the VMware vision and of course Cormac’s take on this. Coincidentally, last week I read this article by long-time community guru Jason Boche on VAAI and number of VMs, and after a discussion with a customer yesterday (at the event) about their operational procedures for provisioning new workloads I figured it was time to write down my thoughts.

I have seen many different definitions so far for Software Defined Storage and I guess there is a source of truth in all of them. Before I explain what it means to me, let me describe commonly faced challenges people have today.

In a lot of environments managing storage and associated workloads is a tedious task. It is not uncommon to see large spreadsheets with a long list of LUNs, IDs, Capabilities, Groupings and whatever more is relevant to them and their workloads. These spreadsheets are typically used to decide where to place a virtual machine or virtual disk. Based on the requirements of the application a specific destination will be selected. On top of that, a selection will need to be made based on currently available disk space of a datastore and of course the current IO load. You do not want to randomly place your virtual machine and find out two days later that you are running out of disk space… Well, that is if you have a relatively mature provisioning process. Of course it is also not uncommon to just pick a random datastore and hope for the best.

To be honest, I can understand many people randomly provision virtual machines. Keeping track of virtual disks, datastores, performance, disk space and other characteristics… it is simply too much and boring. Didn’t we invent computer systems to do these repeatable boring tasks for us? That leads us to the question where and how Software Defined Storage should help you?

A common theme recurring in many “Software Defined” solutions presented by VMware is:

Abstract, Pool, Automate.

This also applies to Software Defined Storage in my opinion. These are three basic requirements that a Software Defined Storage solution should meet. But what does this mean and how does it help you? Let me try to make some sense out of that nice three word marketing slogan:

Software Defined Storage should enable you to provision workloads to a pool of virtualized physical resources based on service level agreements (defined in a policy) in an automated fashion.

I understand that is a mouth full, so lets elaborate a bit more. Think about the challenges I described above… or what Jason described with regards to “VMs per Volume” and how there are various different components that can impact your service level. A Software Defined Storage (SDS) solution should be able to intelligently place virtual disks (virtual machines / vApps) based on selected policy for the object (virtual disk / machine / appliance). These policies typically contain characteristics of the provided service level. On top of that a Software Defined Storage solution should take risks / constraints in to account. Meaning that you don’t want your workload to be deployed to a volume which is running out of disk space for instance.

What about those characteristics, what are those? Characteristics could be anything, just two simple examples to make it a bit more obvious:

  • Does your application require recover-ability after a disaster? –> SDS selects destination which is replicated, or instructs storage system to create replicated object for the VM
  • Does your application require a certain level of performance? –> SDS selects destination that can provide this performance, or instructs storage system to reserve storage resources for the VM

Now this all sounds a bit vague, but I am purposely trying to avoid using product or feature names. Software Defined Storage is not about a particular feature, product or storage system. Although I dropped the word policy, note that enabling Profile Driven Storage within vCenter Server does not provide you a Software Defined Storage solution. It shouldn’t matter either (to a certain extent) if you are using EMC, NetApp, Nimbus, a VMware software solution or any of the other thousands of different storage systems out there. Any of those systems, or even a combination of them, should work in the software defined world. To be clear, in my opinion (today) there isn’t such a thing as a Software Defined Storage product, it is a strategy. It is a way of operating that particular part of your datacenter.

To be fair, there is a huge difference between various solutions. There are products and features out there that will enable you to build a solution like this and transform the way you manage your storage and provision new workloads. Products and features that will allow you to create a flexible offering. VMware has been and is working hard to be a part of this space, vSphere Replication / Storage DRS / Storage IO Control / Virsto / Profile Driven Storage are part of the “now”, but just the beginning… Virtual Volumes, Virtual Flash and Distributed Storage have all been previewed at VMworld and are potentially what is next. Who knows what else is in the pipeline or what other vendors are working on.

If you ask me, there are exciting times ahead. Software Defined Storage is a big part of the Software Defined Data Center story and you can bet this will change datacenter architecture and operations.

** There are two excellent articles on this topic the first by Bill Earl, and the second by Christos Karamanolis, make sure to read their perspective. **