does open shift actively monitor cpu for all the running processes or just the first process that was run.
i am running a service that is configured to use horizontal auto scaling capabilities.
i have hawkuler metrics and heapster setup and working as expected
i have set my resource limits and target cpu utilization at 50%.
once the pod hits cpu >50 i can see it scale up to 3 pods which is the max that i have in my configuration.
my question is does it monitor all the 3 pods at this point ?
also, is there a way to scale up in steps, like bring up one more pod and if the cpu is above 50% then bring up another on and so on or the maximum number of pods configured will be brought up immediatley once the cpu utlization on the 1st pod hits >50%
My understanding is that it's by pod.
Ex. Pod 1 goes over your CPU limit, so Pod 2 is deployed. 5 minutes later, Pod 2 goes over your CPU limit, and Pod3 is deployed.
Related
I have some science jobs to run where the instance is has a mounted network drive to a server that is always. Since the cost of always on VMs cost double, I wanted to run pre-emptible VMs but restart them hourly if they have stopped. I want the jobs to finish, but I also don't want to blow the budget on always on instances when I can have a little down time pay half the hourly rate.
Per this document, Compute Engine always terminates preemptible instances after they run for 24 hours. If you start or shut down the instance via the click “start” or “stop” button in the Google Cloud Console instance page, these actions will reset the 24-hour counter for preemptible instances.
If your science jobs always run longer than 24 hours, and you want to avoid jobs being interrupted, or if you want restart your preemptible instance hourly, you can use Cloud scheduler to start or stop your instance at a fixed time.
I'm setting up an OKD Cluster in a VM via oc cluster up. My VM has 6 GB of RAM and 2 CPUs. Interactions with the internal image registry are very, very slow (multiple minutes to pull or push an image, e.g. when building an application via S2I). At the same time, htop shows me a CPU utilization of 100% for both CPUs within the VM. Is there any way to avoid this issue?
How does OpenShift scale when using EBS for persistent storage? How does OpenShift map users to EBS volumes? Because its infeasible to allocate 1 ebs volume to each user, how does openshift handle this in the backend using kubernetes?
EBS volumes can only be mounted on a single node in a cluster at a time. This means you cannot scale an application that uses one beyond 1 replica. Further, an application using an EBS volume cannot use 'Rolling' deployment strategy as that would require there to be 2 replicas when the new deployment is occurring. The deployment strategy therefore needs to be set to 'Recreate'.
Subject to those restrictions on your deployed application which has claimed a volume of type EBS, there is no problems with using EBS volumes as an underlying storage type. Kubernetes will quite happily map the volume into the pod for your application. If that pod dies and gets started on a different node, Kubernetes will then mount the volume in the pod on the new node instead, such that your storage follows the application.
If you give up a volume claim, its contents are wiped and it is returned to the pool of available volumes. A subsequent claim by you or a different user can then get that volume and it would be applied to the pod for the new application.
This is all handled and works no problems. It is a bit hard to understand what you are asking, but hopefully this gives you a better picture.
I set up a 1 node cluster on google container engine which I just intend to use for testing, so I want to be able keep it shutdown while I am not using it to keep my costs low. I can not however figure out why the VM continually restarts after I shut it down through the console. I have set the "Automatic Restarts" option to false on the VM.
The VM is a n1-standard-2 (2 vCPUs, 7.5 GB memory) with 2 standard persistent disks attached.
Has anyone else faced this issue, or have experience with how to set up GCE so that you can keep it offline while not in use? Thanks in advance for any help.
The VMs in GKE clusters are managed by what's called a Managed Instance Group, which ensures that there's always the expected number of nodes in your cluster. I'd guess that it's seeing that there isn't a VM running in your project and assuming that something's gone wrong, so it recreates it.
You could stop it from doing so by explicitly resizing the instance group down to 0. You can change the number of nodes in the cluster either via the Container Engine UI or by running gcloud container clusters resize $CLUSTERNAME --size=0.
For a research project I am trying to boot as many VM's as possible, using python libvirt bindings, in KVM under Ubuntu server 12.04. All the VM's are set to idle after boot, and to use a minimum amount of memory. At the most I was able to boot 1000 VM's on a single host, at which point the kernel (Linux 3x) became unresponsive, even if both CPU- and memory usage is nowhere near the limits (48 cores AMD, 128GB mem.) Before this, the booting process became successively slower, after a couple of hundred VM's.
I assume this must be related to the KVM/Qemu driver, as the linux kernel itself should have no problem handling this few processes. However, I did read that the Qemu driver was now multi-threaded. Any ideas of what the cause of this slowness may be - or at least where I should start looking?
You are booting all the VMs using qemu-kvm right, and after 100s of VM you feel it's becoming successively slow. So when you feels it stop using kvm, just boot using qemu, I expect you see the same slowliness. My guess is that after those many VMs, KVM (hardware support) exhausts. Because KVM is nothing but software layer for few added hardware registers. So KVM might be the culprit here.
Also what is the purpose of this experiment ?
The following virtual hardware limits for guests have been tested. We ensure host and VMs install and work successfully, even when reaching the limits and there are no major performance regressions (CPU, memory, disk, network) since the last release (SUSE Linux Enterprise Server 11 SP1).
Max. Guest RAM Size --- 512 GB
Max. Virtual CPUs per Guest --- 64
Max. Virtual Network Devices per Guest --- 8
Max. Block Devices per Guest --- 4 emulated (IDE), 20 para-virtual (using virtio-blk)
Max. Number of VM Guests per VM Host Server --- Limit is defined as the total number of virtual CPUs in all guests being no greater than 8 times the number of CPU cores in the host
for more limitations of KVm please refer this document link