This repository stored the source code for downloading the result of ferderated learning.
系列文章-第6篇：这个系列已完结，如对您有帮助，求点赞收藏评论。
读者寄语：再小的帆，也能远航！
- 【k8s完整实战教程0】前言
- 【k8s完整实战教程1】源码管理-Coding
- 【k8s完整实战教程2】腾讯云搭建k8s托管集群
- 【k8s完整实战教程3】k8s集群部署kubesphere
- 【k8s完整实战教程4】使用kubesphere部署项目到k8s
- 【k8s完整实战教程5】网络服务配置（nodeport/loadbalancer/ingress）
- 【k8s完整实战教程6】完整实践-部署一个federated_download项目
17211@hqc MINGW64 ~
$ cd /d/research/git_repository/
17211@hqc MINGW64 /d/research/git_repository (master)
$ ls
Federated/ federated_with_flask/ hello_world/
17211@hqc MINGW64 /d/research/git_repository (master)
$ git clone https://e.coding.net/hqc12/hqc/federated_download.git
Cloning into 'federated_download'...
remote: Enumerating objects: 31, done.
remote: Counting objects: 100% (31/31), done.
remote: Compressing objects: 100% (22/22), done.
remote: Total 31 (delta 5), reused 0 (delta 0), pack-reused 0
Receiving objects: 100% (31/31), 12.44 KiB | 849.00 KiB/s, done.
Resolving deltas: 100% (5/5), done.
17211@hqc MINGW64 /d/research/git_repository (master)
$ ls
Federated/ federated_download/ federated_with_flask/ hello_world/
17211@hqc MINGW64 /d/research/git_repository (master)
$ cd federated_download/
17211@hqc MINGW64 /d/research/git_repository/federated_download (master)
$ ls
Dockerfile README.md main.py requirement.txt static/ templates/打开pycharm，运行测试
出错了，查找资料好像说是conda环境中存在两个该.dll文件造成的，运行在docker中应该不会出现这个问题。 为了进行本地测试，还是在本地解决一下，代码加上：
import os
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"再次运行测试：
两个网址都可以进行访问
点击即可下载
成功！！！
好像没法指定下载到设置的downloads文件夹中，就是直接浏览器下载。因此这个文件夹可以不要了。
直接使用现有仓库
采用之前的构建计划，更换一下代码仓库即可
另外，为提升二次构建镜像的速度，设置缓存目录
缓存目录设置参考：https://coding.net/help/docs/ci/configuration/cache.html 由于使用的是pip下载依赖，因此设置对应的缓存目录
构建时 Dockerfile中COPY源码进容器这一步骤 出现问题，多方尝试之后，下面这样是ok的。
FROM python:3.7
WORKDIR . # 指定容器工作目录
COPY Dockerfile main.py requirement.txt ./
COPY /templates/download.html ./templates/download.html
RUN pip install -r requirement.txt
EXPOSE 5000
RUN /bin/bash -c 'echo init ok'
CMD ["python", "main.py"]注意：
- 目标路径必须是一个目录，并以/ 结尾
- 不能直接复制文件夹，它默认会只复制文件夹中的文件，破坏文件结构
构建成功：
成功！
按之前的记录搭建即可
# 登录
ubuntu@VM-1-15-ubuntu:~$ sudo docker login -u federated_project-1667453994942 -p 55a845e185c9bda4ba21fd2227a7538b55717b00 hqc12-docker.pkg.coding.net
WARNING! Using --password via the CLI is insecure. Use --password-stdin.
WARNING! Your password will be stored unencrypted in /home/ubuntu/.docker/config.json.
Configure a credential helper to remove this warning. See
https://docs.docker.com/engine/reference/commandline/login/#credentials-store
Login Succeeded
# 拉取
ubuntu@VM-1-15-ubuntu:~$ sudo docker pull hqc12-docker.pkg.coding.net/hqc/federated_project/federated-download:v0.0.1
v0.0.1: Pulling from hqc/federated_project/federated-download
17c9e6141fdb: Pull complete
de4a4c6caea8: Pull complete
4edced8587e6: Pull complete
a7969cffbf46: Pull complete
74fbfde6af91: Pull complete
16fe51aed899: Pull complete
a418194ab798: Pull complete
e1b9101d5fa4: Pull complete
c0b070a4672c: Pull complete
7094a060c489: Pull complete
6927575c3e2a: Pull complete
be9ca32391c3: Pull complete
aa5d393447e7: Pull complete
Digest: sha256:4a2cb2995c0a9e10e2bef840a39e96843c043d50256c70d95bd7fc2f2a0362fe
Status: Downloaded newer image for hqc12-docker.pkg.coding.net/hqc/federated_project/federated-download:v0.0.1
hqc12-docker.pkg.coding.net/hqc/federated_project/federated-download:v0.0.1# 查看当前镜像
ubuntu@VM-1-15-ubuntu:~$ sudo docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
hqc12-docker.pkg.coding.net/hqc/federated_project/federated-download v0.0.1 135908d3f14b 50 minutes ago 3.32GB
...
# 打新的标签
ubuntu@VM-1-15-ubuntu:~$ sudo docker tag 135908d3f14b federated-download:v0.0.1
...
# 删除之前的镜像
ubuntu@VM-1-15-ubuntu:~$ sudo docker rmi hqc12-docker.pkg.coding.net/hqc/federated_project/federated-download:v0.0.1
Untagged: hqc12-docker.pkg.coding.net/hqc/federated_project/federated-download:v0.0.1
Untagged: hqc12-docker.pkg.coding.net/hqc/federated_project/federated-download@sha256:4a2cb2995c0a9e10e2bef840a39e96843c043d50256c70d95bd7fc2f2a0362fe
# 再次查看
ubuntu@VM-1-15-ubuntu:~$ sudo docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
federated-download v0.0.1 135908d3f14b 51 minutes ago 3.32GB
...
# 运行
ubuntu@VM-1-15-ubuntu:~$ sudo docker run federated-download:v0.0.1
2022-11-03 05:56:57.531568: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2022-11-03 05:56:57.531673: E tensorflow/stream_executor/cuda/cuda_driver.cc:313] failed call to cuInit: UNKNOWN ERROR (303)
2022-11-03 05:56:57.531708: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (ac30a6317b98): /proc/driver/nvidia/version does not exist
2022-11-03 05:56:57.532244: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2022-11-03 05:56:57.559485: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 2494085000 Hz
2022-11-03 05:56:57.559964: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fb718000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2022-11-03 05:56:57.560008: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
11493376/11490434 [==============================] - 1s 0us/step
ubuntu@VM-1-15-ubuntu:~$没法持续运行。
# 创建deployment的yaml文件
ubuntu@VM-1-15-ubuntu:~$ vim federated-dp.yaml
# 创建service的yaml文件
ubuntu@VM-1-15-ubuntu:~$ vim federated-svc.yaml
ubuntu@VM-1-15-ubuntu:~$ ls
federated-dp.yaml federated-svc.yaml
# 部署deployment
ubuntu@VM-1-15-ubuntu:~$ kubectl apply -f federated-dp.yaml
deployment.apps/federated-deployment created
# 查看，暂时正常
ubuntu@VM-1-15-ubuntu:~$ kubectl get all
NAME READY STATUS RESTARTS AGE
pod/federated-deployment-54f5db67fd-g8p9j 1/1 Running 0 6s
pod/federated-deployment-54f5db67fd-tdwdl 1/1 Running 0 6s
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/federated-deployment 2/2 2 2 6s
NAME DESIRED CURRENT READY AGE
replicaset.apps/federated-deployment-54f5db67fd 2 2 2 6s
# 部署service
ubuntu@VM-1-15-ubuntu:~$ kubectl apply -f federated-svc.yaml
service/federated-service created
# 查看，暂时也正常
ubuntu@VM-1-15-ubuntu:~$ kubectl get all
NAME READY STATUS RESTARTS AGE
pod/federated-deployment-54f5db67fd-g8p9j 1/1 Running 0 35s
pod/federated-deployment-54f5db67fd-tdwdl 1/1 Running 0 35s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/federated-service NodePort 172.16.253.172 <none> 80:30000/TCP 3s
service/kubernetes ClusterIP 172.16.252.1 <none> 443/TCP 37m
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/federated-deployment 2/2 2 2 36s
NAME DESIRED CURRENT READY AGE
replicaset.apps/federated-deployment-54f5db67fd 2 2 2 36s
# 过一会儿查看，出错
ubuntu@VM-1-15-ubuntu:~$ kubectl get all
NAME READY STATUS RESTARTS AGE
pod/federated-deployment-54f5db67fd-2hn6s 0/1 Evicted 0 33s
pod/federated-deployment-54f5db67fd-ddxts 0/1 Evicted 0 33s
pod/federated-deployment-54f5db67fd-dn9dn 0/1 Evicted 0 33s
pod/federated-deployment-54f5db67fd-g8p9j 0/1 Evicted 0 113s
pod/federated-deployment-54f5db67fd-jkrfn 0/1 Evicted 0 33s
pod/federated-deployment-54f5db67fd-jwfqp 0/1 Evicted 0 33s
pod/federated-deployment-54f5db67fd-mjxk8 0/1 Evicted 0 33s
pod/federated-deployment-54f5db67fd-mm8b6 0/1 Evicted 0 32s
pod/federated-deployment-54f5db67fd-tdwdl 1/1 Running 0 113s
pod/federated-deployment-54f5db67fd-wh6qk 0/1 ImagePullBackOff 0 32s
pod/federated-deployment-54f5db67fd-xdktv 0/1 Evicted 0 33s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/federated-service NodePort 172.16.253.172 <none> 80:30000/TCP 80s
service/kubernetes ClusterIP 172.16.252.1 <none> 443/TCP 39m
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/federated-deployment 1/2 2 1 113s
NAME DESIRED CURRENT READY AGE
replicaset.apps/federated-deployment-54f5db67fd 2 2 1 113s失败
1 安装
kubectl apply -f https://github.com/kubesphere/ks-installer/releases/download/v3.3.0/kubesphere-installer.yaml
2 下载配置文件
wget https://github.com/kubesphere/ks-installer/releases/download/v3.3.0/cluster-configuration.yaml
3 更改配置文件
vim cluster-configuration.yaml
4 部署配置文件
kubectl apply -f cluster-configuration.yaml
5 查看部署过程
kubectl logs -n kubesphere-system $(kubectl get pod -n kubesphere-system -l 'app in (ks-install, ks-installer)' -o jsonpath='{.items[0].metadata.name}') -f
安装完成，虽然报错但可以正常登录（是因为服务器资源不足的原因，过一会会变好）
- 获取coding制品仓库的配置令牌
- kubesphere中创建秘钥
配置-保密字典-创建
应用负载-工作负载-创建
成功！
kubesphere-应用负载-服务-创建
失败！
python改为3.9版本
可以访问，并且可以正常下载。
至此，实践成功！
源码开源，若对您有所帮助，请不要吝啬您的star，开放交流学习才能进步！