In my architecture I have two blades in a cluster, let's say with a CPU of 32 cores.
All the blades have several VMs managed by vCenter.
I want to install a VM for a software that require at least 40 cores of CPU to run without problems.
Are the resources of the two blades shared and so I can install the VM forgetting of the individual blade hw details?
You won't be able to create a VM with more CPUs than the underlying hardware has logical processors.
Related
We are running 4 different micro-services on 4 different ec2 autoscaling groups:
service-1 - vcpu:4, RAM:32 GB, VM count:8
service-2 - vcpu:4, RAM:32 GB, VM count:8
service-3 - vcpu:4, RAM:32 GB, VM count:8
service-4 - vcpu:4, RAM:32 GB, VM count:16
We are planning to migrate this workload on EKS (in containers)
We need help in deciding the right node configuration (in EKS) to start with.
We can start with a small machine vcpu:4, RAM:32 GB, but will not get any cost saving as each container will need a separate vm.
We can use a large machine vcpu:16, RAM: 128 GB, but when these machines scale out, scaled out machine will be large and thus can be underutiliized.
Or we can go with a Medium machine like vcpu: 8, RAM:64 GB.
Other than this recommendation, we were also evaluating the cost saving of moving to containers.
As per our understanding, every VM machine comes with following overhead
Overhead of running hypervisor/virtualisation
Overhead of running separate Operating system
Note: One large VM vs many small VMs cost the same on public cloud as cost is based on number of vCPUs + RAM.
Hypervisor/virtualization cost is only valid if we are running on-prem, so no need to consider this.
On the 2nd point, how much resources a typical linux machine can take to run a OS? If we provision a small machine (vcpu:2, RAM:4GB), an approximate cpu usage is 0.2% and memory consumption (other than user space is 500Mb).
So, running large instances (count:5 instances in comparison to small instances count:40) can save 35 times of this cpu and RAM, which does not seem significant.
You are unlikely to see any cost savings in resources when you move to containers in EKS from applications running directly on VM's.
A Linux Container is just an isolated Linux process with specified resource limits, it is no different from a normal process when it comes to resource consumption. EKS still uses virtual machines to provide compute to the cluster, so you will still be running processes on a VM, regardless of containerization or not and from a resource point of view it will be equal. (See this answer for a more detailed comparison of VM's and containers)
When you add Kubernetes to the mix you are actually adding more overhead compared to running directly on VM's. The Kubernetes control plane runs on a set of dedicated VM's. In EKS those are fully managed in a PaaS, but Amazon charges a small hourly fee for each cluster.
In addition to the dedicated control plane nodes, each worker node in the cluster need a set of programs (system pods) to function properly (kube-proxy, kubelet etc.) and you may also define containers that must run on each node (daemon sets), like log collectors and security agents.
When it comes to sizing the nodes you need to find a balance between scaling and cost optimization.
The larger the worker node is the smaller the relative overhead of system pods and daemon sets become. In theory a worker node large enough to accommodate all your containers would maximize resources consumed by your applications compared to supporting applications on the node.
The smaller the worker nodes are the smaller the horizontal scaling steps can be, which is likely to reduce waste when scaling. It also provides better resilience as a node failure will impact fewer containers.
I tend to prefer nodes that are small so that scaling can be handled efficiently. They should be slightly larger than what is required from the largest containers, so that system pods and daemon sets also can fit.
I was wondering if it was possible to force Kubernetes to allocate the cores from the same CPU while spinning up a POD. What I would like Kubernetes to do is, as new PODs are created, the cores allocated to them should come from -let's say- CPU1 as long as there are cores still available on it. CPU2's, CPU3's, etc. cores should not be used in the newly initiated pod. I would like my PODs to have cores allocated from a single CPU as long as it is possible.
Is there a way to achieve this?
Also, is there a way to see from which physical CPUs the cores(cpu) of a POD is coming from?
Thanks a lot.
Edit: Let me explain why I want to do this.
We are running a Spark cluster on Kubernetes. The lead of system/linux administration team warned us about the concept of NUMA. He told us that we could improve the performance of our executor pods if we were to allocate the cores from the same physical CPU. That is why I started digging into this.
I found this Kubernetes CPU Manager. The documentation says:
CPU Manager allocates CPUs in a topological order on a best-effort
basis. If a whole socket is free, the CPU Manager will exclusively
allocate the CPUs from the free socket to the workload. This boosts
the performance of the workload by avoiding any cross-socket traffic.
Also on the same page:
Allocate all the logical CPUs (hyperthreads) from the same physical
CPU core if available and the container requests an entire core worth
of CPUs.
So now I am starting to think maybe what I need is to enable the static policy for the CPU manager to get what I want.
i have question about KVM i could not find any satisfying answer in the net about.
Lets say i want to create 3 virtual machines on a host with 2 CPUs. I am assigning 1 cpu to 1 virtual machines. The other 2 virtual machines should be sharing 1 cpu. If it is possible i want to give 1 vm 30 % and the other one 70% of the cpu.
I know this does not make much sense but i am curious and want to test is :-)
I know that hypervisors like onapp can do that. But how do they do it?
KVM represents each virtual CPU as a thread in the host Linux system, actually as a thread in the QEMU process. So scheduling of guest VCPUs is controlled by the Linux scheduler.
On Linux, you can use taskset to force specific threads onto specific CPUs. So that will let you assign one VCPU to one physical CPU and two VCPUs to another. See, for example, https://groups.google.com/forum/#!topic/linuxkernelnewbies/qs5IiIA4xnw.
As far as controlling what percent of the CPU each VM gets, Linux has several scheduling policies available, but I'm not familiar with them. Any information you can find on how to control scheduling of Linux processes will apply to KVM.
The answers to this question may help: https://serverfault.com/questions/313333/kvm-and-virtual-to-physical-cpu-mapping. (Also that forum may be a better place for this question, since this one is intended for programming questions.)
If you search for "KVM virtual CPU scheduling" and "Linux CPU scheduling" (without the quotes), you should find plenty of additional information.
I was looking for an answear but didn't find one.
I'm trying to create a new VM to develop a web application. What would be the optimal processor settings?
I have i7 (6th gen) with hyperthreading.
Host OS: Windows 10. Guest OS: CentOS.
Off topic: RAM that should I give to VM should be 50% of my memory? Would it be ok? (I have 16GB RAM)
Thanks!
This is referred to as 'right-sizing' a vm, and it is dependent on the application workload that will run inside it. Ideally, you want to provide the VM with the minimum amount of resources the app requires to run correctly. "Correctly" is subjective based upon your expectations.
Inside your VM (CentOS) you can run top to see how much memory and cpu % is being used. You can also install htop which you may find friendlier than top.
RAM
If you see a low % of RAM being used, you can probably reduce what you're giving the VM. If you are seeing any swap memory used (paging to disk), you may want to increase the RAM. Start with 2GB and see how the app behaves.
CPU
You'll may want to start with no more than 2vCPUs, checkout top to see how utilized the application is under load, and then make an assessment for more/less vCPUs.
The way a hosted hypervisor (VMware Workstation) handles guest CPU usage is through a CPU scheduler. When you give a vm x number of vCPUs, the VM will need to wait till that many cores are free on the CPU to do 'work'. The more vCPUs you give it, the more difficult (slower) it will be to schedule. It's more complicated than this, but I'm trying to keep it high level. CPU scheduling deep dive.
So we have around 8 VMs running on a 32 GB RAM and 8 Physical core server. Six of them run a mail server each(Zimbra), two of them run multiple web applications. The load on the servers are very high primarily because of heavy load on each VMs.
We recently came across Docker. It seems to be a cool idea to create containers of applications. Do you think it's a viable idea to run applications of each of these VMs inside 8 Docker Containers. Currently the server is heavily utilized because multiple VMs have serious I/O issues.
Or can docker be utilized in cases where we are only running web applications, and not email or any other infra apps. Do advise...
Docker will certainly alleviate your server's CPU load, removing the overhead from the hypervisor's with that aspect.
Regarding I/O, my tests revealed that Docker has its own overhead on I/O, due to how AUFS (or lately device mapper) works. In that front you will still gain some benefits over the hypervisor's I/O overhead, but not bare-metal performance on I/O. My observations, for my own needs, pointed that Docker was not "bare-metal performance like" when dealing with intense I/O services.
Have you thought about adding more RAM. 64GB or more? For a large zimbra deployment 4GB per VM may not be enough. Zimbra like all messaging and collaboration systems, is an IO bound application.
Having zmdiaglog (/opt/zimbra/libexec/zmdiaglog) data to see if you are allocating memory correctly would help. as per here;
http://wiki.zimbra.com/wiki/Performance_Tuning_Guidelines_for_Large_Deployments#Memory_Allocation