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Update README kubectl applies for zsh support

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Signed-off-by: Tuomas Katila <tuomas.katila@intel.com>
This commit is contained in:
Tuomas Katila 2022-12-29 12:00:38 +02:00
parent b534c16711
commit 26b8b9bd3d
8 changed files with 30 additions and 30 deletions
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2
cmd/dlb_plugin/README.md
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@ -142,7 +142,7 @@ release version numbers in the format `x.y.z`, corresponding to the branches and
repository. Thus the easiest way to deploy the plugin in your cluster is to run this command
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/dlb_plugin?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/dlb_plugin?ref=<RELEASE_VERSION>'
daemonset.apps/intel-dlb-plugin created
```

2
cmd/dsa_plugin/README.md
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@ -31,7 +31,7 @@ release version numbers in the format `x.y.z`, corresponding to the branches and
repository. Thus the easiest way to deploy the plugin in your cluster is to run this command
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/dsa_plugin?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/dsa_plugin?ref=<RELEASE_VERSION>'
daemonset.apps/intel-dsa-plugin created
```

4
cmd/fpga_plugin/README.md
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@ -151,7 +151,7 @@ The following images are available on the Docker hub:
Depending on the FPGA mode, run either
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/fpga_plugin/overlays/af?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/fpga_plugin/overlays/af?ref=<RELEASE_VERSION>'
namespace/intelfpgaplugin-system created
customresourcedefinition.apiextensions.k8s.io/acceleratorfunctions.fpga.intel.com created
customresourcedefinition.apiextensions.k8s.io/fpgaregions.fpga.intel.com created
@ -168,7 +168,7 @@ issuer.cert-manager.io/intelfpgaplugin-selfsigned-issuer created
```
or
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/fpga_plugin/overlays/region?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/fpga_plugin/overlays/region?ref=<RELEASE_VERSION>'
namespace/intelfpgaplugin-system created
customresourcedefinition.apiextensions.k8s.io/acceleratorfunctions.fpga.intel.com created
customresourcedefinition.apiextensions.k8s.io/fpgaregions.fpga.intel.com created

2
cmd/iaa_plugin/README.md
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@ -31,7 +31,7 @@ release version numbers in the format `x.y.z`, corresponding to the branches and
repository. Thus the easiest way to deploy the plugin in your cluster is to run this command
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/iaa_plugin?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/iaa_plugin?ref=<RELEASE_VERSION>'
daemonset.apps/intel-iaa-plugin created
```

8
cmd/operator/README.md
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@ -20,11 +20,11 @@ Install NFD (if it's not already installed) and node labelling rules (requires N
```
# either with default NFD installation
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd?ref=<RELEASE_VERSION>'
# or when setting up with SGX
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/sgx?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/sgx?ref=<RELEASE_VERSION>'
# and finally, NodeFeatureRules
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/node-feature-rules?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/node-feature-rules?ref=<RELEASE_VERSION>'
```
Make sure both NFD master and worker pods are running:
@ -111,7 +111,7 @@ $ export no_proxy=$no_proxy,.svc,.svc.cluster.local
Finally deploy the operator itself:
```
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/operator/default?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/operator/default?ref=<RELEASE_VERSION>'
```
Now you can deploy the device plugins by creating corresponding custom resources.

4
cmd/qat_plugin/README.md
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@ -104,7 +104,7 @@ release version numbers in the format `x.y.z`, corresponding to the branches and
repository. Thus the easiest way to deploy the plugin in your cluster is to run this command
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/qat_plugin?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/qat_plugin?ref=<RELEASE_VERSION>'
```
Where `<RELEASE_VERSION>` needs to be substituted with the desired [release tag](https://github.com/intel/intel-device-plugins-for-kubernetes/tags) or `main` to get `devel` images.
@ -112,7 +112,7 @@ Where `<RELEASE_VERSION>` needs to be substituted with the desired [release tag]
An alternative kustomization for deploying the plugin is with the debug mode switched on:
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/qat_plugin/overlays/debug?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/qat_plugin/overlays/debug?ref=<RELEASE_VERSION>'
```
> **Note**: It is also possible to run the QAT device plugin using a non-root user. To do this,

12
cmd/sgx_plugin/README.md
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@ -84,8 +84,8 @@ Where `<RELEASE_VERSION>` needs to be substituted with the desired [release tag]
First, deploy `node-feature-discovery`:
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/sgx?ref=<RELEASE_VERSION>
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/node-feature-rules?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/sgx?ref=<RELEASE_VERSION>'
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/nfd/overlays/node-feature-rules?ref=<RELEASE_VERSION>'
```
**Note:** The [default configuration](/deployments/nfd/overlays/node-feature-rules/node-feature-rules.yaml) assumes that the in-tree driver is used and enabled (`CONFIG_X86_SGX=y`). If
@ -94,7 +94,7 @@ the SGX DCAP out-of-tree driver is used, the `kernel.config` match expression mu
Next, deploy the Intel Device plugin operator:
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/operator/default?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/operator/default?ref=<RELEASE_VERSION>'
```
**Note:** See the operator [deployment details](/cmd/operator/README.md) for its dependencies and for setting it up on systems behind proxies.
@ -102,7 +102,7 @@ $ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/
Finally, deploy the SGX device plugin with the operator
```bash
$ kubectl apply -f https://raw.githubusercontent.com/intel/intel-device-plugins-for-kubernetes/<RELEASE_VERSION>/deployments/operator/samples/deviceplugin_v1_sgxdeviceplugin.yaml
$ kubectl apply -f 'https://raw.githubusercontent.com/intel/intel-device-plugins-for-kubernetes/<RELEASE_VERSION>/deployments/operator/samples/deviceplugin_v1_sgxdeviceplugin.yaml'
```
### Installation Using kubectl
@ -193,7 +193,7 @@ for generating SGX quotes for workloads. It is deployed with `hostNetwork: true`
to allow connections to localhost PCCS.
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_aesmd?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_aesmd?ref=<RELEASE_VERSION>'
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
intel-sgx-aesmd-mrnm8 1/1 Running 0 3h47m
@ -219,7 +219,7 @@ $ kubectl get pods
The sample application runs SGX DCAP Quote Generation sample:
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_enclave_apps/overlays/sgx_ecdsa_aesmd_quote?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/sgx_enclave_apps/overlays/sgx_ecdsa_aesmd_quote?ref=<RELEASE_VERSION>'
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
intel-sgx-aesmd-mrnm8 1/1 Running 0 3h55m

2
cmd/vpu_plugin/README.md
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@ -51,7 +51,7 @@ release version numbers in the format `x.y.z`, corresponding to the branches and
repository. Thus the easiest way to deploy the plugin in your cluster is to run this command
```bash
$ kubectl apply -k https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/vpu_plugin?ref=<RELEASE_VERSION>
$ kubectl apply -k 'https://github.com/intel/intel-device-plugins-for-kubernetes/deployments/vpu_plugin?ref=<RELEASE_VERSION>'
daemonset.apps/intel-vpu-plugin created
```