KubeFATE 部署多集群联邦学习平台 FATE

Henry Zhang

发布于 2020-06-02 14:43:10

2.2K0

发布于 2020-06-02 14:43:10

文章被收录于专栏：亨利笔记亨利笔记

本文将介绍如何使用 KubeFATE 在两个 Kubernetes 集群上部署互通的两个FATE 实例。这两个 FATE 可以完成各种联邦学习的任务。

完成后将会得到下图的结构：

先决条件

两个独立的 Kubernetes 集群 v1.16.0+；
两个集群都可以连接互联网也可以互通；
两个部署机器，分别可以执行两个集群的 kubectl 命令；
两个 Kubernetes 都已经部署了 ingress-controller ；

本教程的两个 Kubernetes 集群我们分别称为【A集群】和【B集群】

部署的两个 FATE 实例分别称为【PartyA】和【PartyB】

开始

检查集群

A集群的信息

[deploy-A]$ kubectl get node -o wide
NAME     STATUS     ROLES    AGE    VERSION   INTERNAL-IP    EXTERNAL-IP   OS-IMAGE                KERNEL-VERSION                CONTAINER-RUNTIME
master   Ready      master   191d   v1.17.3   192.168.10.1   <none>        CentOS Linux 7 (Core)   3.10.0-1062.12.1.el7.x86_64   docker://19.3.5
node-0   Ready      <none>   191d   v1.17.3   192.168.10.2   <none>        CentOS Linux 7 (Core)   3.10.0-1062.12.1.el7.x86_64   docker://19.3.3
node-1   Ready      <none>   191d   v1.17.3   192.168.10.3   <none>        CentOS Linux 7 (Core)   3.10.0-1062.12.1.el7.x86_64   docker://19.3.3

B集群的信息

[deploy-B]$ kubectl get node -o wide
NAME     STATUS    ROLES    AGE    VERSION   INTERNAL-IP     EXTERNAL-IP  OS-IMAGE                KERNEL-VERSION                CONTAINER-RUNTIME
master   Ready     master   191d   v1.17.3   192.168.9.1     <none>       CentOS Linux 7 (Core)   3.10.0-1062.12.1.el7.x86_64   docker://19.3.5
node-0   Ready     <none>   191d   v1.17.3   192.168.9.2     <none>       CentOS Linux 7 (Core)   3.10.0-1062.12.1.el7.x86_64   docker://19.3.5
node-1   Ready     <none>   191d   v1.17.3   192.168.9.3     <none>       CentOS Linux 7 (Core)   3.10.0-1062.12.1.el7.x86_64   docker://19.3.5

下载KubeFATE:

Kubefate 的开源地址https://github.com/FederatedAI/KubeFATE

打开链接https://github.com/FederatedAI/KubeFATE/releases

Kubefate是容器化部署FATE的最佳实践，项目更新较快，建议使用最新的releases。

下载 The KubeFATE release pack ，得到kubefate-k8s-v1.3.0-a.tar.gz这个文件，解压下载的这个文件，得到一个可执行文件和四个 yaml 文件

# A集群解压
[deploy-A]$ tar -zxvf kubefate-k8s-v1.3.0-a.tar.gz 
kubefate
cluster.yaml
config.yaml
kubefate.yaml
rbac-config.yaml

# B集群解压
[deploy-B]$ tar -zxvf kubefate-k8s-v1.3.0-a.tar.gz 
kubefate
cluster.yaml
config.yaml
kubefate.yaml
rbac-config.yaml

在 Kubernetes 上安装 KubeFATE server

分别创建 KubeFATE server 的 namespace 和 RBAC 权限

在A集群和B集群分别部署rbac-config.yaml

# A集群
[deploy-A]$ kubectl apply -f ./rbac-config.yaml
namespace/kube-fate created
serviceaccount/kubefate-admin created
clusterrolebinding.rbac.authorization.k8s.io/kubefate created

# B集群
[deploy-B]$ kubectl apply -f ./rbac-config.yaml
namespace/kube-fate created
serviceaccount/kubefate-admin created
clusterrolebinding.rbac.authorization.k8s.io/kubefate created

部署 KubeFATE server

在A集群和B集群分别部署kubefate.yaml

# A集群
[deploy-A]$ kubectl apply -f ./kubefate.yaml
deployment.apps/kubefate created
deployment.apps/mongo created
service/mongo created
service/kubefate created
ingress.extensions/kubefate created

# B集群
[deploy-B]$ kubectl apply -f ./kubefate.yaml
deployment.apps/kubefate created
deployment.apps/mongo created
service/mongo created
service/kubefate created
ingress.extensions/kubefate created

查看部署结果

# A集群
[deploy-A]$ kubectl get pod,ingress -n kube-fate
NAME                                            READY   STATUS    RESTARTS   AGE
pod/kubefate-5465d889bb-4hwz6                   1/1     Running   0          3m54s
pod/mongo-7b66bf7d87-hdl5c                      1/1     Running   0          3m54s

NAME                                          HOSTS          ADDRESS          PORTS   AGE
ingress.extensions/kubefate                   kubefate.net   10.184.104.151   80      3m53s

# B集群
[deploy-B]$ kubectl get pod,ingress -n kube-fate
NAME                                            READY   STATUS    RESTARTS   AGE
pod/kubefate-64d57cb855-lks2f                   1/1     Running   0          3m54s
pod/mongo-56684d6c86-96s96                      1/1     Running   0          3m54s

NAME                                          HOSTS          ADDRESS          PORTS   AGE
ingress.extensions/kubefate                   kubefate.net   10.184.104.151   80      3m53s

如果两个pod的状态都是Running说明kubefate server已经部署成功了。

配置ingress host

分别在AB两个部署机配置 kubefate.net 的 ingress 解析

# A集群
# 查看ingress的pod运行的的node的名称
[deploy-A]$ kubectl get pod -A -o wide | grep ingress
kube-system   nginx-ingress-controller-6fc5bcc8c9-l2vnx   1/1     Running     3          41h   172.17.0.2       node-0   <none>           <none>

# B集群
# 查看ingress的pod运行的的node的名称
[deploy-B]$ kubectl get pod -A -o wide | grep ingress
kube-system   nginx-ingress-controller-6d747b878f-9cdxt   1/1     Running     2          40h   172.17.0.2       node-0   <none>           <none>

可以看到两边对应的 node 都是node-0这个节点，通过前面查看的集群信息可以知道：

A集群node-0的 ip 是192.168.10.2
B集群node-0的 ip是192.168.9.2

分别设置对应的host

# A集群
[deploy-A]$ echo "192.168.10.2 kubefate.net" >> /etc/hosts

# B集群
[deploy-B]$ echo "192.168.9.2 kubefate.net" >> /etc/hosts

测试 kubefate 命令行工具与 KubeFATE server 的互通性

安装 kubefate 命令行工具

# A集群
[deploy-A]$ chmod +x ./kubefate && sudo mv ./kubefate /usr/local/bin/kubefate

# B集群
[deploy-B]$ chmod +x ./kubefate && sudo mv ./kubefate /usr/local/bin/kubefate

查看是否连通

# A集群
[deploy-A]$ kubefate version
* kubefate service version=v1.0.2        # 出现这一行表示kubefate server连通成功
* kubefate commandLine version=v1.0.2

# B集群
[deploy-B]$ kubefate version
* kubefate service version=v1.0.2        # 出现这一行表示kubefate server连通成功
* kubefate commandLine version=v1.0.2

分别修改需要部署的 PartyA 和 PartyB 的配置文件

cluster.yaml是 KubeFATE 部署 FATE 实例的部署配置文件，包含了 FATE 实例的一些基本信息，详细的介绍可以查看这里(https://github.com/FederatedAI/KubeFATE/blob/master/docs/configurations/FATE_cluster_configuration.md)。

PartyA的配置文件cluster-A.yaml

# A集群
name: fate-10000
namespace: fate-10000
chartName: fate
chartVersion: v1.3.0-a
partyId: 10000
modules:
  - proxy
  - egg
  - federation
  - metaService
  - mysql
  - redis
  - roll
  - python

proxy:
  type: NodePort
  nodePort: 30010
  partyList:
    - partyId: 9999
      partyIp: 192.168.9.3
      partyPort: 30009
egg:
  count: 3

PartyB的配置文件cluster-B.yaml

# B集群
name: fate-9999
namespace: fate-9999
chartName: fate
chartVersion: v1.3.0-a
partyId: 9999
modules:
  - proxy
  - egg
  - federation
  - metaService
  - mysql
  - redis
  - roll
  - python

proxy:
  type: NodePort
  nodePort: 30009
  partyList:
    - partyId: 10000
      partyIp: 192.168.10.3
      partyPort: 30010
egg:
  count: 3

创建需要的namespace

# A集群
[deploy-A]$ kubectl create namespace fate-10000
namespace/fate-10000 created

# B集群
[deploy-B]$ kubectl create namespace fate-9999
namespace/fate-9999 created

部署FATE

使用kubefate命令行工具部署FATE:

# A集群
[deploy-A]$ kubefate cluster install -f ./cluster-A.yaml
create job success, job id=5b37a5a3-f33b-4967-ae0c-73bea5770c49

# B集群
[deploy-B]$ kubefate cluster install -f ./cluster-B.yaml
create job success, job id=5b1dfdc9-7744-4911-a2e4-009e0fdfcb49

查看部署状态

部署 FATE 的时候会创建一个部署的 job，查看 job 的运行状态可以了解 FATE 是否部署成功。

# A集群
[deploy-A]$ kubefate job describe 5b37a5a3-f33b-4967-ae0c-73bea5770c49
UUID         5b37a5a3-f33b-4967-ae0c-73bea5770c49
StartTime    2020-04-23 07:06:19                 
EndTime      2020-04-23 07:06:22                 
Status       Success                             
Creator      admin                               
ClusterId    0e41ff79-d3be-416d-a53c-af13a7bfdf58
Result       Cluster install success             
SubJobs      []

# B集群
[deploy-B]$ kubefate job describe 5b1dfdc9-7744-4911-a2e4-009e0fdfcb49
UUID         5b1dfdc9-7744-4911-a2e4-009e0fdfcb49
StartTime    2020-04-24 02:58:10                 
EndTime      2020-04-24 02:58:13               
Status       Success                             
Creator      admin                               
ClusterId    d8a1f86e-ac9b-4218-b569-b9093b34c911
Result       Cluster install success             
SubJobs      []

查看 FATE 的信息，了解 FATE 的运行状态

# A集群
[deploy-A]$ kubefate cluster describe 0e41ff79-d3be-416d-a53c-af13a7bfdf58
UUID            0e41ff79-d3be-416d-a53c-af13a7bfdf58
Name            fate-10000
NameSpace       fate-10000
ChartName       fate
ChartVersion    v1.3.0-c
Revision        1 
Status          Running 
Values          {"chartName":"fate","chartVersion":"v1.3.0-c","egg":{"count":3},"modules":["proxy","egg","federation","metaService","mysql","redis","roll","python","client"],"name":"fate-10000","namespace":"fate-10000","partyId":10000,"proxy":{"nodePort":30010,"partyList":[{"partyId":9999,"partyIp":"192.168.9.3","partyPort":30009}],"type":"NodePort"}}     
Config          map[chartName:fate chartVersion:v1.3.0-c egg:map[count:3] modules:[proxy egg federation metaService mysql redis roll python client] name:fate-10000 namespace:fate-10000 partyId:10000 proxy:map[nodePort:30010 partyList:[map[partyId:9999 partyIp:192.168.9.3 partyPort:30009]] type:NodePort]] 
Info            map[dashboard:10000.fateboard.kubefate.net ip:192.168.10.3 modules:[client-6bdb7cd59d-whhx8 egg0-5b44548fbd-dwv7g egg1-685b57d7f5-ftpzg egg2-6687f8486b-f6nwn federation-6d799b5cfd-hrtnp meta-service-54db9f8fbc-6xv9q mysql-6bc77fc46c-fdlhp proxy-8d758c997-v6kq6 python-77bb96fd78-xnjgp redis-9546f56b-jbmxw roll-77dfbb54dc-2q2mb] port:30010]


# B集群
[deploy-B]$ kubefate cluster describe d8a1f86e-ac9b-4218-b569-b9093b34c911
UUID            d8a1f86e-ac9b-4218-b569-b9093b34c911
Name            fate-9999
NameSpace       fate-9999 
ChartName       fate
ChartVersion    v1.3.0-c
Revision        1  
Status          Running  
Values          {"chartName":"fate","chartVersion":"v1.3.0-c","egg":{"count":3},"modules":["proxy","egg","federation","metaService","mysql","redis","roll","python","client"],"name":"fate-9999","namespace":"fate-9999","partyId":9999,"proxy":{"nodePort":30009,"partyList":[{"partyId":10000,"partyIp":"192.168.10.3","partyPort":30010}],"type":"NodePort"}}  
Config          map[chartName:fate chartVersion:v1.3.0-c egg:map[count:3] modules:[proxy egg federation metaService mysql redis roll python client] name:fate-9999 namespace:fate-9999 partyId:9999 proxy:map[nodePort:30009 partyList:[map[partyId:10000 partyIp:192.168.10.3 partyPort:30010]] type:NodePort]] 
Info            map[dashboard:9999.fateboard.kubefate.net ip:192.168.9.3 modules:[client-7db8b9fb45-7scr7 egg0-79768fbffb-ndmq2 egg1-6bd6b965cf-vrkmz egg2-67d896f78-b7dz8 federation-547dfd8654-xmhcx meta-service-9c74f597f-t9zlw mysql-7788cc95-b24vz proxy-6687bffc77-hjj5x python-68df558bb6-bhxr7 redis-864f95f74-p86pv roll-bf7cf74c9-52qqj] port:30009]

配置 FATEboard 的 host

分别配置双方的 FATEboard 和 notebook 的 host，就像配置kubefate.net一样，我们只需要向hosts文件添加一行记录，就可以在浏览器查看使用 FATEboard 和 notebook

# A集群
[deploy-A]$ echo "192.168.10.2 10000.fateboard.kubefate.net" >> /etc/hosts

# B集群
[deploy-B]$ echo "192.168.9.2 9999.fateboard.kubefate.net" >> /etc/hosts

配置成功后可以在浏览器打开 FATEBoard 的 url 查看

10000.fateboard.kubefate.net

9999.fateboard.kubefate.net

类似如下的页面：

检查 Party A和 PartyB 双方的互通性

互相连通的两个 party 就可以完成各种联邦学习的任务，接下来我们通过 toy_example 来测试双方的互通性。

打开 PartyA 的 python container，

# A集群
[deploy-A]$ kubectl exec -it svc/fateflow -c python -n fate-10000 -- bash
(venv) [root@python-77bb96fd78-xnjgp python]

执行 toy_example 脚本，

(venv) [root@python-77bb96fd78-xnjgp python]# cd examples/toy_example/
(venv) [root@python-77bb96fd78-xnjgp toy_example]# python run_toy_example.py 10000 9999 1
stdout:{
    "data": {
        "board_url": "http://fateboard:8080/index.html#/dashboard?job_id=202004270647307032491&role=guest&party_id=10000",
        "job_dsl_path": "/data/projects/fate/python/jobs/202004270647307032491/job_dsl.json",
        "job_runtime_conf_path": "/data/projects/fate/python/jobs/202004270647307032491/job_runtime_conf.json",
        "logs_directory": "/data/projects/fate/python/logs/202004270647307032491",
        "model_info": {
            "model_id": "guest-10000#host-9999#model",
            "model_version": "202004270647307032491"
        }
    },
    "jobId": "202004270647307032491",
    "retcode": 0,
    "retmsg": "success"
}


job status is running
job status is running
job status is running
...

如果出现下面的结果代表双方已经成功互通，