持续集成与持续交付 - 使用Helm在K8S安装Registry
Posted 王万林 Ben
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使用Helm在K8S安装Registry
文章目录
前言
作为容器与Kubernetes解决方案的开发者，我们经常需要将容器镜像推送到/拉取自一个私有Registry。尤其是在做原型或测试时，设置这样一个本地Registry，非常适合开发者个人或者一小组成员访问。
Kubernetes是一个理想的解决方案。本文将演示如何使用Helm安装一个本地Registry。
一、Docker Registry是什么？
Registry是一个存储和内容传递系统，包含有不同标记版本的Docker映像。
样例: the image distribution/registry, with tags 2.0 and 2.1
通过docker push或docker pull与Registry交互
样例: docker pull registry-1.docker.io/distribution/registry:2.1
二、步骤
1.查看K8S集群
命令如下：
controlplane $ kubectl version --short && \\
> kubectl get componentstatus && \\
> kubectl get nodes && \\
> kubectl cluster-info
Client Version: v1.18.0
Server Version: v1.18.0
NAME STATUS MESSAGE ERROR
controller-manager Healthy ok
scheduler Healthy ok
etcd-0 Healthy {"health":"true"}
NAME STATUS ROLES AGE VERSION
controlplane Ready master 12m v1.18.0
node01 Ready <none> 12m v1.18.0
Kubernetes master is running at https://172.17.0.8:6443
dash-kubernetes-dashboard is running at https://172.17.0.8:6443/api/v1/namespaces/kube-system/services/https:dash-kubernetes-dashboard:https/proxy
KubeDNS is running at https://172.17.0.8:6443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy
To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.
controlplane $ helm version --short
v3.1.2+gd878d4d
controlplane $
获取Dashboard的token
controlplane $ token.sh
To access the dashboard click on the Kubernetes Dashboard tab above this command
line. At the sign in prompt select Token and paste in the token that is shown below.
For Kubernetes clusters exposed to the public, always lock administration access including
access to the dashboard. Why? https://www.wired.com/story/cryptojacking-tesla-amazon-cloud/
--- Copy and paste this token for dashboard access ---
eyJhbGciOiJSUzI1NiIsImtpZCI6InJKUUQwMTVtMm5JUjE1VVBNWXFBdndTQVpfeVRXWHUtb0JkOTRaNnMyd1UifQ.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.i--GoSef5Hx_uSdCMILAJnYBrD_vknPjN7Z43IoD00116lP9pw78ytMM9Y3_N5GfnYpoyD4Cn1JKS9avJFWnMoDFuiIQenVZM3NDuKNVtZq7ZW8JgkssaC9gSX25ldYaHwvdSNLBw7iu07ji1K_42OU4KtkkgPNNzGwEEaVjTQ8wIz4zP-sFVRHv1SfFw3r_wlYlTJFr7s3ZxQoD8cpaWR6hheqrsz0DLdw5kfTil-BVjLeZDbbLya-PBRvmj6j-fQA1D_SYJihiDvTR5cqQMb7m1WwHi00K9yF4nG9ml-n-TSfcpw422sIRkk_03HXfhZlObYGThLWIh73WUA3IvA
2.安装Registry
我们使用helm来安装Registry。关于helm的更多知识，请移步到helm官网了解：
controlplane $ helm repo add twuni https://helm.twun.io #为Helm添加chart repository
"twuni" has been added to your repositories
controlplane $ #安装docker-registry应用
controlplane $ helm install registry twuni/docker-registry \\
> --version 1.10.0 \\
> --namespace kube-system \\
> --set service.type=NodePort \\
> --set service.nodePort=31500
NAME: registry
LAST DEPLOYED: Tue May 4 23:53:26 2021
NAMESPACE: kube-system
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
1. Get the application URL by running these commands:
export NODE_PORT=$(kubectl get --namespace kube-system -o jsonpath="{.spec.ports[0].nodePort}" services registry-docker-registry)
export NODE_IP=$(kubectl get nodes --namespace kube-system -o jsonpath="{.items[0].status.addresses[0].address}")
echo http://$NODE_IP:$NODE_PORT
controlplane $ #查看kube-system命名空间下的service
controlplane $ kubectl get service --namespace kube-system
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
dash-kubernetes-dashboard NodePort 10.109.168.165 <none> 80:30000/TCP 112s
kube-dns ClusterIP 10.96.0.10 <none> 53/UDP,53/TCP,9153/TCP 117s
registry-docker-registry NodePort 10.102.51.100 <none> 5000:31500/TCP 3s
controlplane $ export REGISTRY=2886795272-31500-simba10.environments.katacoda.com
controlplane $ kubectl get deployments registry-docker-registry --namespace kube-system
NAME READY UP-TO-DATE AVAILABLE AGE
registry-docker-registry 1/1 1 0 13s
controlplane $ #通过api查看仓库
controlplane $ curl $REGISTRY/v2/_catalog | jq -c
{"repositories":[]}
controlplane $
可以查看到仓库为空。
3.push至Registry
从dockerhub pull一个镜像，push到刚建立的Registry上。
controlplane $ docker pull replicated/dockerfilelint
Using default tag: latest
latest: Pulling from replicated/dockerfilelint
cbdbe7a5bc2a: Pull complete
091983d60f65: Pull complete
7bacc183740f: Pull complete
c4a5a5d270d4: Pull complete
867acec62da8: Pull complete
513c9ceff6ba: Pull complete
a678c69209e5: Pull complete
4d70c498007f: Pull complete
47b1b7b82f1b: Pull complete
Digest: sha256:15ce784e5847966b6d9a88cba348a9429f8b5212f6017180f10ce36b472dfe52
Status: Downloaded newer image for replicated/dockerfilelint:latest
docker.io/replicated/dockerfilelint:latest
controlplane $ docker images | grep lint
replicated/dockerfilelint latest 24b7b3aae3ac 7 months ago 238MB
controlplane $ docker tag replicated/dockerfilelint $REGISTRY/dockerfilelint
controlplane $ docker push $REGISTRY/dockerfilelint
The push refers to repository [2886795272-31500-simba10.environments.katacoda.com/dockerfilelint]
4db43bad3862: Pushed
351191f62788: Pushed
e719c15dabdc: Pushed
530aa387ee5c: Pushed
1f793ff0a8fb: Pushed
aedafbecb0b3: Pushed
db809908a198: Pushed
1b235e8e7bda: Pushed
3e207b409db3: Pushed
latest: digest: sha256:15ce784e5847966b6d9a88cba348a9429f8b5212f6017180f10ce36b472dfe52 size: 2206
controlplane $ curl $REGISTRY/v2/_catalog | jq
{
"repositories": [
"dockerfilelint"
]
}
controlplane $
4.Registry Web页面
上一步我们使用REST查看仓库信息，然而使用网页能更好地展示。这里我们安装joxit/docker-registry-ui来提供干净的网页接口。
controlplane $ cat registry-ui.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: registry-ui-deployment
labels:
app: registry-ui
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
app: registry-ui
template:
metadata:
labels:
app: registry-ui
spec:
containers:
- name: reg-ui
image: joxit/docker-registry-ui:1.5-static
env:
- name: REGISTRY_URL
value: "http://registry-docker-registry:5000"
ports:
- containerPort: 80
---
apiVersion: v1
kind: Service
metadata:
name: registry-ui
labels:
app: registry-ui
namespace: kube-system
spec:
type: NodePort
ports:
- port: 80
targetPort: 80
nodePort: 31000
protocol: TCP
selector:
app: registry-ui
controlplane $ kubectl apply -f registry-ui.yaml
deployment.apps/registry-ui-deployment created
service/registry-ui created
controlplane $
访问web页面
5.build镜像并push
我们从IBM获得一个聪明的应用程序，该应用程序使用Tensorflow来检测乳腺癌肿瘤细胞图像中是否存在有丝分裂。
这个仓库中，待检测的PNG图片大小为64x64。
controlplane $ git clone https://github.com/IBM/MAX-Breast-Cancer-Mitosis-Detector.git && cd MAX-Breast-Cancer-Mitosis-Detector
Cloning into 'MAX-Breast-Cancer-Mitosis-Detector'...
remote: Enumerating objects: 214, done.
remote: Counting objects: 100% (37/37), done.
remote: Compressing objects: 100% (31/31), done.
remote: Total 214 (delta 15), reused 12 (delta 4), pack-reused 177
Receiving objects: 100% (214/214), 705.23 KiB | 2.16 MiB/s, done.
Resolving deltas: 100% (90/90), done.
controlplane $ docker build -t $REGISTRY/max-breast-cancer-mitosis-detector .
Sending build context to Docker daemon 230.4kB
Step 1/12 : FROM quay.io/codait/max-base:v1.4.0
v1.4.0: Pulling from codait/max-base
b8f262c62ec6: Pull complete
0a43c0154f16: Pull complete
906d7b5da8fb: Pull complete
079aad1b3615: Pull complete
1eed0602da40: Pull complete
9bba78d911e2: Pull complete
491429e01696: Pull complete
979d37cd2030: Pull complete
5612cd136ee1: Pull complete
Digest: sha256:1f09c52c5461b4a13b3a2e6166acac5165596a6e3f65b5c168a880cd4ac6bebe
Status: Downloaded newer image for quay.io/codait/max-base:v1.4.0
---> 769b57b767e7
Step 2/12 : ARG model_bucket=https://max-cdn.cdn.appdomain.cloud/max-breast-cancer-mitosis-detector/1.0.1
---> Running in b63a6e917de8
Removing intermediate container b63a6e917de8
---> dcd4cfdd2f14
Step 3/12 : ARG model_file=assets.tar.gz
---> Running in 62b434a90f28
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---> 09c9fb3c1fe4
Step 4/12 : RUN sudo apt-get update && sudo apt-get install -y libopenslide0 gcc && sudo rm -rf /var/lib/apt/lists/*
---> Running in f4c5f38a6488
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man-browser
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Removing intermediate container f4c5f38a6488
---> ed2771c7f2b8
Step 5/12 : RUN wget -nv --show-progress --progress=bar:force:noscroll ${model_bucket}/${model_file} --output-document=assets/${model_file} && tar -x -C assets/ -f assets/${model_file} -v && rm assets/${model_file}
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2021-05-05 00:49:14 URL:https://max-cdn.cdn.appdomain.cloud/max-breast-cancer-mitosis-detector/1.0.1/assets.tar.gz [449605/449605] -> "assets/assets.tar.gz" [1]
./._deep_histopath_model.hdf5
deep_histopath_model.hdf5
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Step 6/12 : COPY requirements.txt .
---> 7494fe1b53df
Step 7/12 : RUN pip install -r requirements.txt
---> Running in 6071bcacd8ee
Collecting h5py==2.9.0
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Collecting numpy==1.17.5
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Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.7/site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard<1.16.0,>=1.15.0->tensorflow==1.15.4->-r requirements.txt (line 2)) (3.4.0)
Building wheels for collected packages: openslide-python, gast, termcolor, wrapt
Building wheel for openslide-python (setup.py): started
Building wheel for openslide-python (setup.py): finished with status 'done'
Created wheel for openslide-python: filename=openslide_python-1.1.1-cp37-cp37m-linux_x86_64.whl size=28775 sha256=ea7698cffe81bee72f82b4805405f70bca92c3c3f50bfa1a1fc5d421f2fbf524
Stored in directory: /home/max/.cache/pip/wheels/58/b3/05/e26ea0e774fe2232c62d3e80f79c6061d23c3dc72b240cd03f
Building wheel for gast (setup.py): started
Building wheel for gast (setup.py): finished with status 'done'
Created wheel for gast: filename=gast-0.2.2-py3-none-any.whl size=7539 sha256=cabd55e2ce2965b78bbf6b820b4b8064818b1b0f9e4e7b451081ecd69b0030f6
Stored in directory: /home/max/.cache/pip/wheels/21/7f/02/420f32a803f7d0967b48dd823da3f558c5166991bfd204eef3
Building wheel for termcolor (setup.py): started
Building wheel for termcolor (setup.py): finished with status 'done'
Created wheel for termcolor: filename=termcolor-1.1.0-py3-none-any.whl sizeCI/CD持续集成与持续交付（下）-------- jenkins的节点管理，用户管理，结合ansible和k8s