Google kubernetes Engine with Google CI/CD Implementation
- 1. Google Kubernetes Engine (GKE) Topics we will be covering in the presentation are: • What is GKE • Why GKE is different from other cloud • How to implement an application in GKE (A Demo) • CI CD implémentation on GKE
- 2. 1. What is GKE? Google Kubernetes Engine (GKE) is a management and orchestration system for Docker container and container clusters that run within Google's public cloud services. Google Kubernetes Engine is based on Kubernetes, Google's open source container management system. We use Google Kubernetes commands and resources to deploy and manage your applications, perform administration tasks and set policies, and monitor the health of your deployed workloads. Some main features of GKE : Create or resize Docker container clusters Create container pods, replication controllers, jobs, services or load balancers Update and upgrade container clusters Automatic scaling of your cluster's node instance count
- 3. 2. Why GKE is different from other cloud Differences on the basis of below parameters GKE AKS EKS Scalability GKE provide the ability to add different ‘nodepools’ (or ‘nodegroups’) which allows different machine types to join the worker pool. In AKS you can only scale up to similar nodes. In GKE addition of a nodepool is a single step process, in EKS you need to additionally connect the new nodepool to the cluster manually. Availability GKE provides high availability of their clusters in two modes: multi- zonal and regional. In multi-zonal mode, there is only one master node but there can be worker nodes in different zones. In regional mode, the master nodes are also spread across all the zones to provide even better HA. AKS does not have high availability for their master nodes, as of date. The worker nodes are part of Availability Zones so they provide HA EKS also provides HA master and worker nodes spread across multiple availability zones very similar to GKE’s regional mode Add-ons GKE provides support for Calico as its network plugin which enables Network Policies to be defined for inter-pod communication AKS supports Network Policies through kube-router project which has to be installed manually EKS also provides Calico integration though it has to be setup manually. Network policies are crucial for securing the platform especially in a multi- tenant environment. Pricing Short-term (100 hrs)/per month 40$ 60$ 50$ + 20$* (* master)
- 4. .
- 5. Application Deployment in GKE In our demo we are going to deploy a Node.js application on our GKE cluster. The flow will be like: We will take the application source from GitHub. We will create a Dockerfile, which will copy all the important libraries and other important packages used for running the application, with that we will build a docker image, later which will be used at the time of deployment We will create a Deployment.yaml file for deployment purpose We will create a Service.yaml file for exposing our application with outer world.
- 6. Fetching the code from GitHub Go the GKE cluster that you have created and do #git clone https://github.com/Piyushkamboj/NodeJS-GKE.git Front End of Application will look like:
- 7. DockerFile We will Build Image using Docker build command: #docker build –t (path of dockerfile) After Successfully creation of Docker image, we will push the image to google container registry using below command: #docker tag (source_image) gcr.io/testproject-piyush/nodejsapp:v1 #docker push gcr.io/testproject-piyush/nodejsapp:v1 Note : Instead gcr.io we can also use : us.gcr.io , eu.gcr.io , asia.gcr.io Depends on which location our registry exist.
- 8. Deployment and Service File Deployment.yaml Service.yaml
- 9. Creating deployment and exposing the application We will use the deployment.yaml and service.yaml file we have created earlier Note: run the below command in the location where above two files are present #kubectl apply -f deployment.yaml #kubectl apply -f service.yaml
- 10. The Front Page of application on Browser
- 11. CI/CD implementation on GKE We will learn how to create CI/CD pipeline and thus deploying the build(Docker image) on Google k8s cluster. The steps in whole process would be: Creating a Dockerfile which will include all the libraries and dependencies to run the application in dockerised form. The Dockerfile must be in the root directory of application. Creating Deployment.yaml and service.yaml file. It will includes the steps of our deployment and exposure of created image on k8s cluster Creating a cloudbuild.yaml file, the cloudbuild.yaml file will perform the complete task. Setting up IAM for cloud builder so that it has permissions to deploy the images in GKE. Setup build trigger.
- 12. Creation of Dockerfile and Deployment.yaml File As we have created Docker and deployment file earlier so we will just push both of the file to the source code repository (GitHub) and we will synch google cloud source repository with GitHub
- 13. Create Cloudbuild.yaml file Cloudbuild.yaml file with the help of Build trigger will automate everything which we were doing manually. From creating a docker file to deploying it to the GKE cluster.
- 16. Set up IAM We will setup IAM for cloud builder so that it has permissions to deploy the images in GKE. To do this, navigate to IAM & Admin →IAM on the side menu. Here, you would see an entry in the format :- “<project-number>@cloudbuild.gserviceaccount.com” with the role, Cloud Build Service Account. Edit the role and add Kubernetes Engine Admin role to it as well.
- 17. Setup Build Trigger In the Cloudbuild section there is one option to setup build trigger by clicking it we have to fill some details as below
- 18. Run the created Trigger After running check the history in cloudbuild section