Identifying & Resolving Excessive CPU Overcommitment (vCPU:pCore ratios)

Help! My performance is terrible and my consultant/vendor says it’s due to high/excessive CPU overcommitment! What do I do next?

Question: “How much CPU overcommitment is ok?”.

The answer is of course “It depends” and there are many factors including but not limited to, workload type, physical CPUs and how complimentary the workloads (other VMs) are.

Other common questions include:

“How much overcommitment do I have now?”

&

“How do I know if overcommitment is causing a performance problem?”.

Let’s start with “How much overcommitment do I have now?”.

With Nutanix this is very easy to work out, first goto the Hardware page in PRISM and click Diagram, then select one of your nodes as shown below.

PRISMHWDiagram

Once you’ve done that you will see below in the “Summary” section the CPU Model, No. of CPU Cores and No. of Sockets as shown below.

HostDetailsPRISMCPUHW

In this case we have 2 sockets and 20 cores total for a total of 10 physical cores per socket.

If you have multiple node types in your cluster, repeat this step for each different node type in your cluster. Then simply add up the total number of physical cores in the cluster.

In my example, I have three nodes, each with 20 cores for a total of 60 physical cores.

Next we need to find out how many vCPUs we’ve provisioned in the cluster. This can be found on the “VMs” page in PRISM as shown below.

ProvisionedvCPUsPRISM

So we have our 3 node cluster with 60 physical cores (pCores) and we have provisioned 130 vCPUs.

Now we can input the details into my vSphere Cluster Sizing Calculator and work out the overcommitment including our desired availability level (in my case, N+1) and we get the following:

ClusterSizingCalc2

The calculator is designed to be conservative and show information assuming the resources (CPU/RAM) required for the configured availability level are removed from the calculation. Put simply, the vCPU:pCore ratio assumes the N+1 host is not in the cluster which is how I personally size environments, especially for business critical applications.

The calculator shows us we have a 3.25:1 vCPU:pCore ratio.

For business critical applications like SQL, Exchange, Oracle, SAP etc, I always recommend sizing without CPU overcommitment (so <= 1:1) and ensuring the VMs are right sized to avoid poor performance and wasted resources.

Now that we know our overcommitment ratio, what’s next?

We need to find out if our overcommitment level is consistent with our original design and assess how the Virtual Machines are performing in the current state. A good design should call out the application requirements and critical performance factors such as CPU overcommitment and VM placement (e.g.: DRS Rules).

“How do I know if overcommitment is causing a performance problem?”.

One of the best ways to measure if a VM has CPU scheduling contention is by looking at “CPU Ready” or “Stolen time” in the AHV (or KVM) world.

CPU ready is basically the delay between time when the VM requests to be scheduled onto CPU cores and the time when it’s actually scheduled. One of the easiest way’s to present this is in a percentage of total time that the VM is waiting to be scheduled.

How Much CPU Ready is OK? My rule of thumb is:

<2.5% CPU Ready
Generally No Problem.

2.5%-5% CPU Ready
Minimal contention that should be monitored during peak times

5%-10% CPU Ready
Significant Contention that should be investigated & addressed

>10% CPU Ready
Serious Contention to be investigated & addressed ASAP!

With that said, the impact of CPU Ready will vary depending on your application so even 1% should not be ignored especially for business critical applications.

As CPU Ready is a critical performance metric, Nutanix decided to display this in PRISM on a per VM basis so customers can easily identify CPU scheduling contention.

Below we see the summary of a VMs performance which can be found on the VM’s page in PRISM after highlighting a VM. At the bottom of the page we see a graph showing CPU Ready.

VMPerformanceNTNXPRISM

CPU Ready of <2.5% is unlikely to be causing major issues for the majority of VMs, but in some latency sensitive applications like databases or video/voice, 2.5% could be causing noticeable issues so never disregard looking into CPU ready in your troubleshooting.

I recommend looking at a VM and if it’s showing even minimal CPU ready is say >1% and it’s a business critical application, follow the troubleshooting steps in this article until CPU Ready is <0.5% and measure the performance difference.

Key Point: If you have applications like SQL Always on availability groups, Oracle RAC or Exchange DAGs, one VM suffering CPU Ready will likely be having a flow on impact to the other VMs trying to communicate (or replicate) to it. So ensure all “dependancies” for your VM/app are not suffering CPU Ready before looking into other areas.

In short, Server A with no CPU Ready can be impacted when trying to communicate to Server B and being delayed because Server B has High CPU Ready.

The reason I bring this up is because it’s important not to get tunnel vision when looking at performance problems.

Now to the fun part, Troubleshooting/Resolutions to CPU Ready!

  1. Right size your VMs

Do NOT ignore this step! Your CPU overcommitment ratio is irrelevant, Right Sizing will always improve the efficiency and performance of your VMs. There is an increasing overhead at the hypervisor layer for scheduling more vCPUs, even with no overcommitment so ensure VMs are not oversized.

A common misconception is that 90% CPU utilisation is a bottleneck, in fact this can be a sign of a right sized VM. We need to ensure vCPUs are sized for peaks but unless a VM is pinned at 100% CPU for long periods of time, a short spike to 100% is not necessarily a problem.

Here is an example of the benefits of VM right sizing.

Once you have right sized your VMs, move onto step 2.

2. Size or place VMs within NUMA boundaries

First what is a NUMA boundary? It’s pretty simple, take the number of cores and divide by the number of sockets and that’s the NUMA boundary and also the maximum number of vCPUs a VM can be if you wish to benefit from maximum memory performance and optimal CPU scheduling.

The total host RAM is also a factor so divide the total RAM by the number of sockets and that’s the maximum RAM a VM can be assigned without breaching the NUMA boundary and paying an approx 30% performance penalty on memory performance.

Example: I had a customer who had MS Exchange running with 12vCPU / 96GB VMs on Nutanix nodes with 12 cores per socket. Exchange was running poorly (in the end due to a MS bug) but they insisted the problem was insufficient CPU. So they forced the customer to increase the VM to 18 vCPUs.

This did not solve the performance problem AND in fact made performance worse as the VM now suffered from very higher CPU Ready as VMs larger than a NUMA boundary can experience much higher CPU ready especially on hosts running other workloads. Moving back to 12 vCPUs relieved the CPU Ready and then Microsoft ultimately resolved the case with a patch.

3. Migrate other VMs off the host running the most critical VM

This is a really easy step to alleviate CPU scheduling contention and allows you to monitor the performance benefit of not having CPU overcommitment.

If the virtual machines performance improves you’ve likely found at least one of the causes of the performance problem. Now comes the harder part. Unless you can afford to have a single VM per host, you now need to identify complimentary workloads to migrate back onto the host.

What’s a complimentary workload? 

I’m glad you asked! Let me give you an example.

Let’s say we have a 10vCPU / 128GB RAM SQL Server VM which is right sized (of course) and our host is the NX-8035-G4 with 2 sockets of 10 cores per socket (20 cores total) and 256GB RAM. Being SQL we’ll also assume it has high IO requirements as it’s the backend for a business critical application.

Being Nutanix we also have a Controller VM using some resources (say 8vCPUs and 32GB RAM). For those who are interested see: Cost vs Reward for the Nutanix Controller VM (CVM)

A complimentary workload would have one or more of the following qualities:

a) Less than 96GB RAM (Host RAM 256GB, minus SQL VM 128GB, minus CVM 32GB = 96GB remaining)

b) vCPU requirements <= 2 (This would mean a 1:1 vCPU:pCore ratio)

c) Low vCPU requirements and/or utilization

d) Low IO requirements

e) Low capacity requirements (this would maximise the amount of SQL data which would remain local to the node for maximum read performance with data locality).

f) A workload which uses CPU/Storage at a different time of the day to the SQL workload.

e.g.: SQL might be busy 8am to 6pm, but workload may drop significantly outside those hours. A VM with high CPU/Storage IO requirements that runs from 7pm to midnight would potentially be a very complimentary workload as it would allow higher overcommitment and with minimal/no performance impact due to the hours of operation of the VMs not overlapping.

4. Migrate the VM onto a node with more physical cores

This might be an obvious one but a node with more physical cores has more CPU scheduling flexibility which can help reduce CPU Ready. Even without increasing the vCPUs on the VM, the VM has a better chance of getting time on the physical cores and therefore should perform better.

5. Migrate the VM onto a node with a higher CPU clock-rate

Another somewhat obvious one but it’s very common for vendors and customers to quote the number of vCPUs as a requirement when a “vCPU” is not a unit of measurement. A vCPU at best with no overcommitment is equal to one physical core and it goes downhill for there. Physical cores also vary in clock-rate (duh!) so a faster clock rate can have a huge impact on performance especially for those pesky single threaded applications.

Note: CPUs with higher clock rates typically have fewer cores, so don’t make the mistake of moving a VM to a node where it exceeds the NUMA boundary!

6. Turn OFF advanced power management on the physical server & use “High Performance” as your policy (in ESXi)

Advanced Power Management settings can save power and in some cases have minimal impact on performance, but when troubleshooting performance problems, especially around business critical applications, I recommend eliminating Power Management as a potential cause and once the performance problem is resolved, test re-enabling it if you desire.

7. Enable Hyperthreading (HT)

Hyperthreads can provide significant CPU scheduling advantages and in many cases improve performance despite a hyperthreading providing generally fairly low overall performance (typically 10%-30%) in CPU benchmarks.

Long story short, a VM in a Ready state is doing NOTHING, so enabling HT can allow it to be doing SOMETHING, which is better than NOTHING!

Also hypervisors are pretty smart, they preferentially schedule vCPUs to pCores so the busy VMs will more often than not be on pCores while the VMs with low vCPU requirements can be scheduled to hyperthreads. Win/Win.

Note: Some vendors recommend turning HT off, such as Microsoft for Exchange. But, this recommendation is really only applicable to Exchange running on physical servers. For virtualization always, always leave HT enabled and size workloads like Exchange with 1:1 vCPU to pCore ratios, then you will achieve consistent, high performance.

For anyone struggling with a vendor (like Microsoft) who is insisting on disabling HT when running business critical apps, here is an Example Architectural Decision on Hyperthreading which may help you.

Example Architectural Decision – Hyperthreading with Business Critical Applications (Exchange 2013)

8. Add additional nodes to the cluster

If you have right sized, migrated VMs to nodes with complimentary workloads, ensured optimal NUMA configurations, ensured critical VMs are running on the highest clock-rate CPUs etc and you’re still having performance problems, it may be time to bite the bullet and add one or more nodes to the cluster.

Additional nodes provide more CPU cores and therefore more CPU scheduling opportunities.

A common question I get is “Why can’t I just use CPU reservations on my critical VMs to guarantee them 100% of their CPU?”

In short, using CPU reservations does not solve CPU ready, I have also written an article on this topic – Common Mistake – Using CPU reservations to solve CPU ready

Wildcard: Add storage only nodes

Wait, what? Why would adding storage only nodes help with CPU contention?

It’s actually pretty simple, lower latency for read/write IO means less CPU WAIT which is the time the CPU is “waiting” for an IO to complete.

e.g.: If an I/O takes 1ms on Nutanix but 5ms on a traditional SAN, then moving the VM to Nutanix will mean 4ms less CPU WAIT for the VM, which means the VM can use it’s assigned vCPUs more efficiently.

Adding storage only nodes (even where the additional capacity is not required) will improve the average read/write latency in the cluster allowing VMs to be scheduled onto a physical core, get the work done, and release the pCore for another VM or to perform other work.

Note: Storage only nodes and the way data is distributed throughput the cluster is a unique capability for Nutanix. See the following article for an example on how performance is improved with storage only nodes with NO modification required to the VMs/Apps.

Scale out performance testing with Nutanix Storage Only Nodes

Summary:

There are a lost of things we can do to address CPU Ready issues, including thinking outside the box and enhancing the underlying storage with things like storage only nodes.

Other articles on CPU Ready

1. VM Right Sizing – An Example of the benefits

2. How Much CPU Ready is OK?

3. Common Mistake – Using CPU Reservations to solve CPU Ready

4. High CPU Ready with Low CPU Utilization

Nutanix AOS 5.5 delivers 1M IOPS from a single VM, but what happens when you vMotion?

For many years Nutanix has been delivering excellent performance across multiple hypervisors as well as hardware platforms including the native NX series, OEMs (Dell XC & Lenovo HX) and more recently software only options with Cisco and HPE.

Recently I tweeted (below) showing how a single virtual machine can achieve 1 million 8k random read IOPS and >8GBps throughput on AHV, the next generation hypervisor.

While most of the response to this was positive, the usual negativity came from some competitors who tried to spread fear, uncertainty and doubt (FUD) about the performance including claims it was not sustainable during/after a live migration (vMotion) and that is does not demonstrate the performance of the IO path.

Let’s quickly cover of the IO path discussion of in-kernel vs a controller VM.

To test the IO path, in the case of Nutanix, via the Controller VM, you want to eliminate as many variables and bottlenecks as possible. This means a read/write test is not valid as writes are dependant on factors such as the network. As this was one a node using NVMe, the bottleneck would quickly become the network and not the path between the user VM and controller VM.

I’ve previously tweeted (below) showing an example of the throughput capabilities of SATA SSD, NVMe and 3DxPoint which clearly shows the network is the bottleneck with next generation flash.

I’ve also responded to 3rd party FUD about Nutanix Data locality with a post which goes in depth about Nutanix original & unique implementation of Data Locality which is how Nutanix minimises its dependancy on the network to deliver excellent performance.

So we are left with read IO to actually test and possibly stress the IO path between a User VM and software defined storage, be that in-kernel or in user space which is where the Nutanix CVM runs.

The tweet showing >1 million 8k random read IOPS and >8GBps throughput shows that the IO path of Nutanix is efficient enough to achieve this at just 110 micro (not milli) seconds.

The next question from those who try to discredit Nutanix and HCI in general is what happens after a vMotion?

Let me start by saying this is a valid question, but even if performance dropped during/after a vMotion is it even a major issue?

For business critical applications, it is common for vendors to recommend DRS should/must rules to prevent vMotion exception for in the event of maintenance or failure regardless of the infrastructure being traditional/legacy NAS/SAN or HCI.

With a NAS/SAN, the best case scenario is 100% remote IO where as with Nutanix this is the worse cast scenario. Let’s assume business as usual on Nutanix is 1M IOPS and during a vMotion and for a few mins after that performance dropped by 20%.

That would still be 800k IOPS which is higher than what most NAS/SAN solutions can delivery anyway.

But the fact is, Nutanix can sustain excellent performance during and after a vMotion as demonstrated by the video below which was recorded in real time. Hint: Watch the values in the putty session as these show the performance as measured at the guest level which is what ultimately matters.

Credit for the video goes to my friend and colleague Michael “Webscale” Webster (VCDX#66 & NPX#007).

The IO dropped below 1 million IOPS for approx 3 seconds during the vMotion with the lowest value recorded at 956k IOPS. I’d say an approx 10% drop for 3 seconds is pretty reasonable as the performance drop is caused by the migration stunning the VM and not by the underlying storage.

Over to our “friends” at the legacy storage vendors to repeat the same test on their biggest/baddest arrays.

Not impressed? Let’s see what 70/30 read/write workload performs!

Nutanix X-Ray Benchmarking tool – Extended Node Failure Scenario

In the first part of this series, I introduced Nutanix X-Ray benchmarking tool which has been designed very differently to traditional benchmarking tools as the performance of the app is the control and the variable is the platform,not the other way around.

In the second part, I showed how Nutanix AHV & AOS could maintain the performance while utilising snapshots to achieve the type of recovery point objective (RPO) that is expected in production environments, especially with business critical workloads whereas a leading hypervisor and SDS platform could not.

In this part, I will cover the Extended Node Failure Scenario in X-Ray and again compare Nutanix AOS/AHV and a leading hypervisor and SDS platform in another real world scenario.

Let’s start by reviewing what the description of the X-ray Extended node failure scenario.

XrayExtendedNodeFailureScenario

I really like that X-ray has a scenario which shows a simulated node failure as this is bound to happen regardless of the platform you choose, and with hyperconverged platforms the impact of a node failure is arguably higher than traditional 3-tier as the nodes contain some data which needs to be recovered.

As such, it is critical before choosing a HCI platform to understand how it behaves in a failure scenario which is exactly what this scenario demonstrates.

XrayNodeFailureComparison

Here we can see the impact on the performance of the surviving VMs following the power being disconnected via the out of band management interface.

The Nutanix AOS/AHV platform continues to run at a very steady rate, virtually without impact to the VMs. On the other hand we see that after 1 hour the other platform has a high impact with significant degradation.

This clearly shows the Acropolis Distributed Storage Fabric (ADSF) to be a superior platform from a resiliency perspective, which should be a primary consideration when choosing a platform for any production environment.

Back in 2014, I highlighted the Problems with RAID and Object Based Storage for data protection and in a follow up post I discussed how Nutanix Acropolis Distributed Storage Fabric (ADSF) compares with traditional SAN/NAS RAID and hyper-converged solutions using Object storage for data protection.

The above results clearly demonstrate the problems I discussed back in 2014 are still applicable to even the most recent versions of a leading hypervisor and SDS platform. This is because the problem is the underlying architecture and bolting on new features is at best masking the constraints of the original architectural decision which has proven to be significantly flawed.

This scenario clearly demonstrates the criticality of looking beyond peak performance numbers and conducting a thorough evaluation of a platform prior to purchase as well as comprehensive operational verification prior to moving any platform into production.

Related Articles:

Nutanix X-Ray Benchmarking tool Part 1 – Introduction

Nutanix X-Ray Benchmarking tool Part 2 -Snapshot Impact Scenario