Tag: openshift

  • openshift-install-power – quick notes

    FYI: openshift-install-power – this is a small recipe for deploying the latest code with the UPI from master branch @ my repo

    git clone https://github.com/ocp-power-automation/openshift-install-power.git
    chmod +x openshift-install-powervs
    export IBMCLOUD_API_KEY="<<redacted>>"
    export RELEASE_VER=latest
    export ARTIFACTS_VERSION="master"
    export ARTIFACTS_REPO="<<MY REPO>>"
    ./openshift-install-powervs setup
    ./openshift-install-powervs create -var-file mon01-20220930.tfvars -flavor small -trace
    

    This also recover from errors in ocp4-upi-powervs/terraform

  • Topology Manager and OpenShift/Kubernetes

    I recently had to work with the Kubernetes Topology Manager and OpenShift. Here is a braindump on Topology Manager:

    If the Topology ManagerFeature Gate is enabled, then any active HintProviders are registered to the TopologyManager.

    If the CPU Manager and feature gate are enabled, then the CPU Manager can be used to help workloads which are sensitive to CPU throttling, context switches, cache misses, require hyperthreads on same physical CPU core, low latency, and benefit from shared processor resources. The manager has two policies none and static which registers a NOP provider or statically locks the container to a set of CPUs.

    If the Memory Manager and feature gate are enabled, then the MemoryManager can be used to process independently of the CPU Manager – e.g. allocate HugePages or guarnteed memory.

    If Device Plugins are enabled, then it can be turned on to allocate Devices next to NUMA node resources (e.g., SR-IOV NICs). This may be used independent of the typical CPU/Memory management for GPUs and other machine devices.

    Generally, these are all used together to generate a BitMask that admits a pod using a best-effort, restricted, or single-numa-node policy.

    An important limitation is the Maximum Number of NUMA nodes is hard-coded to 8. When there are more than eight NUMA nodes, it’ll error out when assigning to the topology. The reason for this is related to state explosion and computational complexity.

    1. Check the worker nodes CPU if the NUMA returns 1, it’s a single NUMA node. If it returns 2 or more, it’s multiple NUMA nodes.
    sh-4.4# lscpu | grep 'NUMA node(s)'
    NUMA node(s):        1
    

    The kubernetes/enhancements repo contains great detail on the flows and weaknesses of the TopologyManager.

    To enable the Topology Manager, one uses Feature Gates:

    And OpenShift prefers the FeatureSet LatencySensitive

    1. Via FeatureGate
    $ oc patch featuregate cluster -p '{"spec": {"featureSet": "LatencySensitive"}}' --type merge
    

    Which turns on the basic TopologyManager /etc/kubernetes/kubelet.conf

      "featureGates": {
        "APIPriorityAndFairness": true,
        "CSIMigrationAzureFile": false,
        "CSIMigrationvSphere": false,
        "DownwardAPIHugePages": true,
        "RotateKubeletServerCertificate": true,
        "TopologyManager": true
      },
    
    1. Create a custom KubeletConfig, this allows targeted TopologyManager feature enablement.

    file: cpumanager-kubeletconfig.yaml

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: cpumanager-enabled
    spec:
      machineConfigPoolSelector:
        matchLabels:
          custom-kubelet: cpumanager-enabled
      kubeletConfig:
         cpuManagerPolicy: static 
         cpuManagerReconcilePeriod: 5s 
    
    $ oc create -f cpumanager-kubeletconfig.yaml
    

    Net: They can be used independent of each other. They should be turned on at the same time to maximize the benefits.

    There are some examples and test cases out there for Kubernetes and OpenShift

    1. Red Hat Sys Engineering Team Test cases for Performance Addon Operator which is now the Cluster Node Tuning Operator– These are the clearest tests, which apply directly to the Topology Manager.
    2. Kube Test Cases

    This is one of the best examples k8stopologyawareschedwg/sample-device-plugin.

    Tools to know about

    1. GitHub: numalign (amd64) – you can download this in the releases. In this fork prb112/numalign I added ppc64le to the build
    2. numactl and numastat are superbly helpful to see the topology spread on a node link to a handy pdf on numa I’ve been starting up a fedora container with numactl and numastat installed

    Final note, I had written down that fedora is a great combination with taskset and numactl if you copy in the binaries. I think I used Fedora 35/36 as a container. link

    Yes. I built a Hugepages hungry container Hugepages. I also looked at hugepages_tests.go and the test plan.

    When it came down to it, I used my hunger container with the example.

    I hope this helps others as they start to work with Topology Manager.

    References

    Red Hat

    1. Red Hat Topology Aware Scheduling in Kubernetes Part 1: The High Level Business Case
    2. Red Hat Topology Awareness in Kubernetes Part 2: Don’t we already have a Topology Manager?

    OpenShift

    1. OpenShift 4.11: Using the Topology Manager
    2. OpenShift 4.11: Using device plug-ins to access external resources with pods
    3. OpenShift 4.11: Using Device Manager to make devices available to nodes Device Manager
    4. OpenShift 4.11: About Single Root I/O Virtualization (SR-IOV) hardware networks – Device Manager
    5. OpenShift 4.11: Adding a pod to an SR-IOV additional network
    6. OpenShift 4.11: Using CPU Manager CPU Manager

    Kubernetes

    1. Kubernetes: Topology Manager Blog
    2. Feature Highlight: CPU Manager
    3. Feature: Utlizing the NUMA-aware Memory Manager

    Kubernetes Enhancement

    1. KEP-693: Node Topology Manager e2e tests: Link
    2. KEP-2625: CPU Manager e2e tests: Link
    3. KEP-1769: Memory Manager Source: Link PR: Link
  • Switching to use Kubernetes with Flannel on RHEL on P10

    I needed to switch from calico to flannel. Here is the recipe I followed to setting up Kubernetes 1.25.2 on a Power 10 using Flannel.

    Switching to use Kubernetes with Flannel on RHEL on P10

    1. Connect to both VMs (in split terminal)
    ssh root@control-1
    ssh root@worker-1
    
    1. Run Reset (acknowledge that you want to proceed)
    kubeadm reset
    
    1. Remove Calico
    rm /etc/cni/net.d/10-calico.conflist 
    rm /etc/cni/net.d/calico-kubeconfig
    iptables-save | grep -i cali | iptables -F
    iptables-save | grep -i cali | iptables -X 
    
    1. Initialize the cluster
    kubeadm init --cri-socket=unix:///var/run/crio/crio.sock --pod-network-cidr=192.168.0.0/16
    
    1. Setup kubeconfig
    mkdir -p $HOME/.kube
    sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
    sudo chown $(id -u):$(id -g) $HOME/.kube/config
    
    1. Add the plugins:
    curl -O https://github.com/containernetworking/plugins/releases/download/v1.1.1/cni-plugins-linux-ppc64le-v1.1.1.tgz -L
    cp cni-plugins-linux-ppc64le-v1.1.1.tgz /opt/cni/bin
    cd /opt/cni/bin
    tar xvfz cni-plugins-linux-ppc64le-v1.1.1.tgz 
    chmod +x /opt/cni/bin/*
    cd ~
    systemctl restart crio kubelet
    
    1. Download https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml

    2. Edit the containers to point to the right instance, per the notes in the yaml to the ppc64le manifests

    3. Update net-conf.json

      net-conf.json: |
        {
          "Network": "192.168.0.0/16",
          "Backend": {
            "Type": "vxlan"
          }
        }
    
    1. Join the Cluster

    kubeadm join 1.1.1.1:6443 –token y004bg.sc65cp7fqqm7ladg
    –discovery-token-ca-cert-hash sha256:1c32dacdf9b934b7bbd6d13fde9312a35709e2f5849008acec8f597eb5a5dad9

    1. Add role to the workers
    kubectl label node worker-01.ocp-power.xyz node-role.kubernetes.io/worker=worker
    

    Ref: https://gist.github.com/rkaramandi/44c7cea91501e735ea99e356e9ae7883 Ref: https://www.buzzwrd.me/index.php/2022/02/16/calico-to-flannel-changing-kubernetes-cni-plugin/

  • Operator Doesn’t Install Successfully: How to restart it

    You see there is an issue with the unpacking your operator in the Operator Hub.

    Recreate the Job that does the download by recreating the job and subscription.

    1. Find the Job (per RH 6459071)
    $ oc get job -n openshift-marketplace -o json | jq -r '.items[] | select(.spec.template.spec.containers[].env[].value|contains ("myop")) | .metadata.name'

    2. Reset the download the Job

    for i in $(oc get job -n openshift-marketplace -o json | jq -r '.items[] | select(.spec.template.spec.containers[].env[].value|contains ("myop")) | .metadata.name'); do
      oc delete job $i -n openshift-marketplace; 
      oc delete configmap $i -n openshift-marketplace; 
    done

    3. Recreate your Subscription and you’ll see more details on the Job’s failure. Keep an eagle eye on the updates as it rolls over quickly.

    Message: rpc error: code = Unknown desc = pinging container registry registry.stage.redhat.io: Get "https://xyz/v2/": x509: certificate signed by unknown authority.

    You’ve seen how to restart the download/pull through job.

  • IBM Cloud cluster-api: building a CAPI image

    Per the IBM Cloud Kubernetes cluster-api provider, I followed the raw instructions with some amendments.

    Steps

    1. Provision an Ubuntu 20.04 image.

    2. Update the apt repository

    $ apt update
    
    1. Install the dependencies (more than what’s in the instructions)
    $ apt install qemu-kvm libvirt-daemon-system libvirt-clients virtinst cpu-checker libguestfs-tools libosinfo-bin make git unzip ansible python3-pip
    
    1. Clone the image-builder repo
    $ git clone https://github.com/kubernetes-sigs/image-builder.git
    
    1. Change to the capi image
    $ cd image-builder/images/capi
    
    1. Make the deps-raw to confirm everything is working.
    $ make deps-raw
    
    1. Create the ubuntu-2004 image.
    $ make build-qemu-ubuntu-2004
    

    Once complete you’ll see:

    ==> qemu: Running post-processor: custom-post-processor (type shell-local)
    ==> qemu (shell-local): Running local shell script: /tmp/packer-shell078717884
    Build 'qemu' finished after 12 minutes 8 seconds.
    
    ==> Wait completed after 12 minutes 8 seconds
    
    ==> Builds finished. The artifacts of successful builds are:
    --> qemu: VM files in directory: ./output/ubuntu-2004-kube-v1.22.9
    --> qemu: VM files in directory: ./output/ubuntu-2004-kube-v1.22.9
    
    1. Append the .qcow2 extension
    $ mv ./output/ubuntu-2004-kube-v1.22.9/ubuntu-2004-kube-v1.22.9 ./output/ubuntu-2004-kube-v1.22.9/ubuntu-2004-kube-v1.22.9.qcow2
    

    You can now upload the output to IBM Cloud Object Storage.

    A couple quick tips:

    • If you see any warnings, you can get advanced details using export PACKER_LOG=1 which puts out the full packer logging. see Packer
    • KVM module not found indicates you are running in a nested KVM, you’ll have to swap out of the VM and enable nested KVM. Fedora: Docs
    • Adding a VM to VPC is documented here Console: customImage
  • IBM Power Developer eXchange – An opportunity to connect likeminds

    There is a new IBM Power Developer eXchange where you can connect with the team I’m a part of to discuss OpenShift on Power or Kubernetes on Power. It’s an avenue to talk directly to the Subject Matter Experts in an open arena.

    Are you interested in furthering the development of open source applications on IBM Power? JOIN the IBM Power Developer eXchange to access numerous resources and expand your knowledge. https://ibm.biz/power-developer #PDeX #PowerSystems #Linux #OSS

  • Downloading pvsadm and getting VIP details

    pvsadm is an unsupported tool that helps with Power Virtual Server administration. I needed this detail for my CAPI tests.

    1. Get the latest download_url per StackOverflow
    $ curl -s https://api.github.com/repos/ppc64le-cloud/pvsadm/releases/latest | grep browser_download_url | cut -d '"' -f 4
    ...
    https://github.com/ppc64le-cloud/pvsadm/releases/download/v0.1.7/pvsadm-linux-ppc64le
    ...
    
    1. Download the pvsadm tool using the url from above.
    $ curl -o pvsadm -L https://github.com/ppc64le-cloud/pvsadm/releases/download/v0.1.7/pvsadm-linux-ppc64le
      % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                     Dload  Upload   Total   Spent    Left  Speed
      0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
    100 21.4M  100 21.4M    0     0  34.9M      0 --:--:-- --:--:-- --:--:-- 34.9M
    
    1. Make the pvsadm tool executable
    $ chmod +x pvsadm
    
    1. Create the API Key at https://cloud.ibm.com/iam/apikeys

    2. On the terminal, export the IBMCLOUD_API_KEY.

    $ export IBMCLOUD_API_KEY=...REDACTED...      
    
    1. Grab the details of your network VIP using your service name and network.
    $ ./pvsadm get ports --instance-name demo --network topman-pub-net
    I0808 10:41:26.781531  125151 root.go:49] Using an API key from IBMCLOUD_API_KEY environment variable
    +-------------+----------------+----------------+-------------------+--------------------------------------+--------+
    | DESCRIPTION |   EXTERNALIP   |   IPADDRESS    |    MACADDRESS     |                PORTID                | STATUS |
    +-------------+----------------+----------------+-------------------+--------------------------------------+--------+
    |             | 1.1.1.1        | 2.2.2.2        | aa:24:7c:5d:cb:bb | aaa-bbb-ccc-ddd-eee                  | ACTIVE |
    +-------------+----------------+----------------+-------------------+--------------------------------------+--------+
    
  • PowerVS: Grabbing a VM Instance Console

    1. Create the API Key at https://cloud.ibm.com/iam/apikeys

    2. On the terminal, export the IBMCLOUD_API_KEY.

    $  export IBMCLOUD_API_KEY=...REDACTED...      
    
    1. Login to the IBM Cloud using the commandline tool https://www.ibm.com/cloud/cli
    $ ibmcloud login --apikey "${IBMCLOUD_API_KEY}" -r ca-tor
    API endpoint: https://cloud.ibm.com
    Authenticating...
    OK
    
    Targeted account Demo <-> 1012
    
    Targeted region ca-tor
    
    Users of 'ibmcloud login --vpc-cri' need to use this API to login until July 6, 2022: https://cloud.ibm.com/apidocs/vpc-metadata#create-iam-token
                          
    API endpoint:      https://cloud.ibm.com   
    Region:            ca-tor   
    User:              myuser@us.ibm.com   
    Account:           Demo <-> 1012   
    Resource group:    No resource group targeted, use 'ibmcloud target -g RESOURCE_GROUP'   
    CF API endpoint:      
    Org:                  
    Space:  
    
    1. List your PowerVS services
    $ ibmcloud pi sl
    Listing services under account Demo as user myuser@us.ibm.com...
    ID                                                                                                                   Name   
    crn:v1:bluemix:public:power-iaas:mon01:a/999999c1f1c29460e8c2e4bb8888888:ADE123-8232-4a75-a9d4-0e1248fa30c6::     demo-service   
    
    1. Target your PowerVS instance
    $ ibmcloud pi st crn:v1:bluemix:public:power-iaas:mon01:a/999999c1f1c29460e8c2e4bb8888888:ADE123-8232-4a75-a9d4-0e1248fa30c6::    
    
    1. List the PowerVS Services’ VMs
    $ ibmcloud pi ins                                                  
    Listing instances under account Demo as user myuser@us.ibm.com...
    ID                                     Name                                   Path   
    12345-ae8f-494b-89f3-5678   control-plane-x       /pcloud/v1/cloud-instances/abc-def-ghi-jkl/pvm-instances/12345-ae8f-494b-89f3-5678   
    
    1. Create a Console for the VM instance you want to look at:
    $ ibmcloud pi ingc control-plane-x
    Getting console for instance control-plane-x under account Demo as user myuser@us.ibm.com...
                     
    Name          control-plane-x   
    Console URL   https://mon01-console.power-iaas.cloud.ibm.com/console/index.html?path=%3Ftoken%3not-real  
    
    1. Click on the Console URL, and view in your browser. it can be very helpful.

    I was able to diagnose that I had the wrong reference image.

  • Pause: Use this one, not that one.

    The Red Hat Ecosystem Catalog contains a supported version of the pause container. This container is based on ubi8. This best version of the Pause container to use for multiarch purposes.

    Don’t use docker.io/ibmcom/pause-ppc64le:3.1 when you have a multi-architecture version

    Steps

    1. Create a Pod yaml pointing to the Red Hat registry.
    $ cat << EOF > pod.yaml 
    kind: Pod
    apiVersion: v1
    metadata:
      name: demopod-1
      labels:
        demo: foo
    spec:
      containers:
      - name: pause
        image: registry.access.redhat.com/ubi8/pause:latest
    EOF
    
    1. Create the Pod
    $ oc apply -f pod.yaml 
    pod/demopod-1 created
    
    1. Check the Pod is running.
    $ oc get pods -l demo=foo
    NAME        READY   STATUS    RESTARTS   AGE
    demopod-1   1/1     Running   0          89s
    

    You have a Pause container running in OpenShift.

  • Identifying Kernel Memory Usage Culprits

    After suspecting the Kernel Memory is leaked, using slabtop --sort c where it shows high memory usage. You can use the following steps to confirm the memory usage culprit using slub_debug=U. (Thanks to ServerFault).

    1. Login to OpenShift
    $ oc login
    
    1. Check that you don’t already see 99-master-kargs-slub.
    $ oc get mc 99-master-kargs-slub
    
    1. Create the slub_debug=U kernel argument. Note, that it’s assigned to the master role.
    cat << EOF > 99-master-kargs-slub.yaml
    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfig
    metadata:
      labels:
        machineconfiguration.openshift.io/role: master
      name: 99-master-kargs-slub
    spec:
      kernelArguments:
      - slub_debug=U
    EOF
    
    1. Create the Kernel Arguments Machine Config.
    $ oc apply -f 99-master-kargs-slub.yaml 
    machineconfig.machineconfiguration.openshift.io/99-master-kargs-slub created
    
    1. Wait until the master nodes are updated.
    $ oc wait mcp/master --for condition=updated --timeout=25m
    machineconfigpool.machineconfiguration.openshift.io/master condition met
    
    1. Confirm the node status as soon as it’s up, and list the master nodes.
    $ oc get nodes -l machineconfiguration.openshift.io/role=master
    NAME                                                    STATUS   ROLES    AGE   VERSION
    lon06-master-0.xip.io   Ready    master   30d   v1.23.5+3afdacb
    lon06-master-1.xip.io   Ready    master   30d   v1.23.5+3afdacb
    lon06-master-2.xip.io   Ready    master   30d   v1.23.5+3afdacb
    
    1. Connect to the master node and switch to the root user
    $ ssh core@lon06-master-0.xip.io
    sudo su - 
    
    1. Check the kmalloc-32 allocation
    $  cat /sys/kernel/slab/kmalloc-32/alloc_calls | sort -n  | tail -n 5
       4334 iomap_page_create+0x80/0x190 age=0/654342/2594020 pid=1-39569 cpus=0-7
       5655 selinux_sk_alloc_security+0x5c/0xd0 age=916/1870136/2594937 pid=0-39217 cpus=0-7
      41908 __kernfs_new_node+0x70/0x2d0 age=406911/2326294/2594938 pid=0-38398 cpus=0-7
    9969728 memcg_update_all_list_lrus+0x1bc/0x550 age=2564414/2567167/2594607 pid=1 cpus=0-7
    19861376 __list_lru_init+0x2b8/0x480 age=406870/2007921/2594449 pid=1-38406 cpus=0-7
    

    This points to memcg_update_all_list_lrus is using a lot of resources, which is currently fixed in a patch to the Linux Kernel.

    References

    1. https://serverfault.com/questions/1020241/debugging-kmalloc-64-slab-allocations-memory-leak
    2. http://www.jikos.cz/jikos/Kmalloc_Internals.html
    3. https://stackoverflow.com/questions/20079767/what-is-different-functions-malloc-and-kmalloc
    4. ServerFault: Debugging kmalloc-64 slab allocations / memory leak
    5. Kmalloc Internals: Exploring Linux Kernel Memory Allocation
    6. How I investigated memory leaks in Go using pprof on a large codebase
    7. Using Go 1.10 new trace features to debug an integration test
    8. Kernel Memory Leak Detector
    9. go-slab – slab allocator in go
    10. Red Hat Customer Support Portal: Interpreting /proc/meminfo and free output for Red Hat Enterprise Linux
    11. Red Hat Customer Support Portal: Determine how much memory is being used on the system
    12. Red Hat Customer Support Portal: Determine how much memory and what kind of objects the kernel is allocating