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k8s
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Commit 3080f4fa
authored
Dec 16, 2020
by
tingweiwang
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gpu判断条件修复,修复预处理器推送镜像到kpl_k8s问题。
1 parent
9c938687
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15 additions
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26 deletions
script/k8s/deploy-gpu-k8s.sh
script/k8s/deploy-gpu-k8s.sh
View file @
3080f4f
...
...
@@ -10,10 +10,8 @@ new_harbor_ip=192.168.1.32
harbor_host
=
192.168.1.32:5000
harbor_passwd
=
admin
#写死的不能改,harbor配置文件中password写死了,当前只能是admin
harbor_user
=
admin
image_
path
=
/root/images
#写死的不能改
image_
file
=
/root/images.tar.gz
#写死的不能改
interface
=
'eth*|enp*|eno*|ens*'
#本机内网IP的物理网卡名称,用于flannel的配置。
image_list
=
`
cat
$image_path
/image_list.txt
`
image_list_ksy
=
`
cat
$image_path
/image_list_ksy.txt
`
host_name
=
`
hostname
`
harbor_user_name
=
admin
harbor_auth_token
=
$(
echo
-n
"
${
harbor_user
}
:
${
harbor_passwd
}
"
| base64
)
...
...
@@ -213,7 +211,7 @@ ansible master -m shell -a "systemctl daemon-reload && service flanneld restart
###################################根据不同节点类型,安装设置docker#####################################
echo
"判断当前节点是gpu,还是cpu节点,根据节点不同,完成不同操作&& sleep 2"
test
=
`
lspci |grep -i nvidia|wc -l
`
if
[
$test
-gt
0
]
;
then
if
[
$test
-gt
3
]
;
then
echo
"当前节点是GPU节点,开始安装gpu docker"
&&
sleep 2
&&
apt install nvidia-docker2 --allow-unauthenticated -y
echo
"当前harbor仓库地址为
$harbor_host
"
sed -i s/harbor_host/
$harbor_host
/g /root/k8s/config/daemon.json_gpu
...
...
@@ -447,27 +445,18 @@ echo "您的harbor服务器访问地址为:$harbor_host,已经自动创建harbor
sleep 4
docker login
$harbor_host
-uadmin -p
$harbor_passwd
###########################推送私有镜像到harbor仓库#######
echo
"####################开始执行镜像导入###########################"
for
image
in
`
ls
$image_path
|grep -Ev
"*.sh"
|grep -Ev
"*.txt"
|grep -Ev
"images.tar.gz"
`
do
echo
"开始导入
$image
镜像"
docker load -i
$image_path
/
$image
done
echo
"#####################开始执行镜像推送############################"
for
i
in
${
image_list
[@]
}
do
image_name
=
`
echo
$i
|awk -F
"/"
'{print $3}'
`
docker tag
$i
$harbor_host
/k8s/
$image_name
echo
"开始push
$harbor_host
/k8s/
$image_name
镜像"
docker push
$harbor_host
/k8s/
$image_name
done
for
j
in
${
image_list_ksy
[@]
}
do
image_name
=
`
echo
$j
|awk -F
"/"
'{print $4}'
`
docker tag
$j
$harbor_host
/k8s/
$image_name
echo
"开始push
$harbor_host
/k8s/
$image_name
镜像"
docker push
$harbor_host
/k8s/
$image_name
done
echo
"####################判断私有镜像文件是否存在###########################"
test
-f
$image_file
if
[
$?
-eq 0
]
;
then
echo
"私有镜像文件存在,开始解压压缩包"
&&
sleep 2
&&
tar -xvzf
$image_file
-C /root/
&&
\
cp -a /root/images/push-set.sh /root/images/push-set-
`
date +%F-%H-%M
`
.sh
&&
\
sed -i s/harbor_host/
$harbor_host
/g /root/images/push-set-
`
date +%F-%H-%M
`
.sh
&&
\
sh /root/images/push-set-
`
date +%F-%H-%M
`
.sh
&&
\
mv /root/images/push-set-
`
date +%F-%H-%M
`
.sh /tmp
else
echo
"不存在/root/images.tar.gz,退出脚本"
exit
466
################################安装coredns以及nvidia-kubernetes插件##########
sed -i s/harbor_host/
$harbor_host
/g /root/k8s/config/coredns.yaml
kubectl create -f /root/k8s/config/coredns.yaml
...
...
@@ -484,7 +473,7 @@ echo "alias kp='kubectl -n kpl'" >> ~/.bashrc
sleep 5
##############################################################################
test
=
`
lspci |grep -i nvidia |wc -l
`
if
[
$test
-gt
0
]
;
then
if
[
$test
-gt
3
]
;
then
echo
"为gpu节点打lable"
&&
sleep 1
kubectl label node
$host_name
autodl
=
true
kpl
=
true
gpu
=
true
cpu
=
true
user_job_node
=
true
internal_service_node
=
true
else
...
...
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