terraform
Deployment workflow
部署工作流程
Before you get started, you need to install environment binaries. In this example the first few steps illustrate how to setup and configure binaries on Mac OSX/Linux.
在开始之前，您需要安装环境二进制文件。 在此示例中，前几个步骤说明了如何在Mac OSX / Linux上设置和配置二进制文件。
Stack used: Terraform, kubectl, YAML, Redis cluster, Python & Go Lang
使用的堆栈：Terraform，kubectl，YAML，Redis群集，Python和Go Lang
Here what is needed before you get started.
在开始之前，这里需要什么。
- terraform executable terraform可执行文件
2. gcloud binaries
2. gcloud二进制文件
3. kubectl/minikube
3. kubectl / minikube
on mac using homebrew
在Mac上使用自制软件
$ brew install kubectl
$ brew install kubectl
Install Docker
安装Docker
4. Setup gcloud creds
4.设置gcloud凭证
export PROJECT_NAME=project-name-123456
gcloud iam service-accounts keys create creds/serviceaccount.json \
--iam-account sa-name@${PROJECT_NAME}.iam.gserviceaccount.com5. It is time to write your declarative IAC code to define your GCP infrastructure provider.
5.是时候编写声明性IAC代码来定义GCP基础结构提供程序了。
provider "google" {
credentials = file("./creds/serviceaccount.json")
project = "project-name-123456"
region = "us-east1"
}6. Define your Kubernetes cluster tf declaration.
6.定义您的Kubernetes集群tf声明。
resource "google_container_cluster" "gke-cluster" {
name = "my-first-gke-cluster"
network = "default"
location = "us-east1-b"
initial_node_count = 3
}7. Initialize terraform:
7.初始化terraform：
8. Before apply dry run terraform with “plan” option
8.在应用带有“计划”选项的空运行地形之前
9. Apply mypkan to continue
9.应用mypkan继续
10. Set project name and get container authentication creds.
10.设置项目名称并获取容器身份验证凭据。
Deploying Redis cluster to GKE
将Redis集群部署到GKE
11. Redis Master config:
11. Redis Master配置：
apiVersion: apps/v1 # for k8s versions before 1.9.0 use apps/v1beta2 and before 1.8.0 use extensions/v1beta1
kind: Deployment
metadata:
name: redis-master
spec:
selector:
matchLabels:
app: redis
role: master
tier: backend
replicas: 1
template:
metadata:
labels:
app: redis
role: master
tier: backend
spec:
containers:
- name: master
image: k8s.gcr.io/redis:e2e # or just image: redis
resources:
requests:
cpu: 100m
memory: 100Mi
ports:
- containerPort: 637912. Deploy redis master to GKE
12.将redis master部署到GKE
13. Create Redis Master service
13.创建Redis Master服务
Config file:
配置文件：
apiVersion: v1
kind: Service
metadata:
name: redis-master
labels:
app: redis
role: master
tier: backend
spec:
type: LoadBalancer
ports:
- port: 6379
targetPort: 6379
selector:
app: redis
role: master
tier: backend14. Redis Slave config:
14. Redis Slave配置：
apiVersion: apps/v1 # for k8s versions before 1.9.0 use apps/v1beta2 and before 1.8.0 use extensions/v1beta1
kind: Deployment
metadata:
name: redis-slave
spec:
selector:
matchLabels:
app: redis
role: slave
tier: backend
replicas: 2
template:
metadata:
labels:
app: redis
role: slave
tier: backend
spec:
containers:
- name: slave
image: gcr.io/google_samples/gb-redisslave:v1
resources:
requests:
cpu: 100m
memory: 100Mi
env:
- name: GET_HOSTS_FROM
value: dns
# If your cluster config does not include a dns service, then to
# instead access an environment variable to find the master
# service's host, comment out the 'value: dns' line above, and
# uncomment the line below:
# value: env
ports:
- containerPort: 6379Deploy slave pods and service
部署从属Pod和服务
Deploying WebApp container to GKE
将WebApp容器部署到GKE
- Dockerfile (webApp) Dockerfile(webApp)
FROM python:3.8.3
LABEL maintainer="Sudheer Kondla, skondla@me.com"
#RUN apt-get -y install python3-pip
RUN mkdir /app
WORKDIR /app
COPY . /app
RUN groupadd -r app &&\
useradd -r -g app -d /home/app -s /sbin/nologin -c "Docker image user" app
#RUN pip3 install --upgrade setuptools pip
RUN apt-get update
RUN apt-get install -y libzmq3-dev python3-pip
RUN apt-get clean && rm -rf /var/lib/apt/lists/*
RUN pip3 install --upgrade pip
RUN pip3 install -r requirements.txt
#RUN cp lib/rdsAdmin.py /usr/lib/python3.4
RUN cp lib/rdsAdmin.py /usr/local/lib/python3.8
#RUN apt-get install -y apt-utils && apt-get install -y curl
RUN apt-get -y install curl
RUN chmod +x dbWebAPI.sh
RUN chown -R app:app /app
USER app
EXPOSE 50443
ENTRYPOINT [ "/bin/bash" ]
CMD [ "dbWebAPI.sh" ]2. Create docker tag, and push it to Google Cloud Registry (GCR).
2.创建docker标签，并将其推送到Google Cloud Registry(GCR)。
3. WebApp deployment
3. WebApp部署
pod declaration :
吊舱声明：
---
apiVersion: "apps/v1"
kind: "Deployment"
metadata:
name: "dbwebapi"
namespace: "default"
labels:
app: "dbwebapi"
spec:
replicas: 3
selector:
matchLabels:
app: "dbwebapi"
template:
metadata:
labels:
app: "dbwebapi"
spec:
containers:
- name: "dbwebapi-sha256-1"
image: "gcr.io/project-name-123456/dbwebapi@sha256:e86321a26fc6393a4b20e6ace38fb3f95d1edebf92e7684d2eaa80aa0b2032c5"
---
apiVersion: "autoscaling/v2beta1"
kind: "HorizontalPodAutoscaler"
metadata:
name: "dbwebapi-hpa-e1lc"
namespace: "default"
labels:
app: "dbwebapi"
spec:
scaleTargetRef:
kind: "Deployment"
name: "dbwebapi"
apiVersion: "apps/v1"
minReplicas: 1
maxReplicas: 5
metrics:
- type: "Resource"
resource:
name: "cpu"
targetAverageUtilization: 80service declaration:
服务声明：
---
apiVersion: "v1"
kind: "Service"
metadata:
name: "dbwebapi-service"
namespace: "default"
labels:
app: "dbwebapi"
spec:
ports:
- protocol: "TCP"
port: 25443
selector:
app: "dbwebapi"
type: "LoadBalancer"
loadBalancerIP: ""Testing Redis connection
测试Redis连接
Testing Python WebApp
测试Python WebApp
Automate this into CI/CD pipelines or manually schedule
将其自动化到CI / CD管道中或手动调度
if [ $# -lt 1 ];
then
echo "USAGE: bash $0 [dbEndpoint"]
exit 1
fi
dbEndpoint=${1}
outfile=$dbEndpoint|cut -f1 -d'.'
cd /home/admin/jobs/new
/usr/bin/curl -k https://35.185.32.145:25443/backup/create \
--data "endpoint=${dbEndpoint}"; \
echoCheck pod logs
检查吊舱日志
Troubleshooting Kube service
对Kube服务进行故障排除
翻译自: https://medium.com/@kondlawork/deploying-apps-on-google-cloud-kubernetes-engine-2c2b835fbf0d
terraform