Google Cloud Platform (GCP) provides persistent block-level storage volumes for use with Google Kubernetes Engine (GKE) instances. In this section, we will create storage classes for your applications in Kubernetes running in the GKE. You will learn to create a StorageClass resource in Kubernetes, you will learn about the parameters available with the variation in performance of GCP PD volume types, and also use the new CSI.
- Title Page
- Copyright and Credits
- Dedication
- About Packt
- Contributors
- Preface
- Building Production-Ready Kubernetes Clusters
- Technical requirements
- Configuring a Kubernetes cluster on Amazon Web Services 
- Configuring a Kubernetes cluster on Google Cloud Platform
- Configuring a Kubernetes cluster on Microsoft Azure
- Configuring a Kubernetes cluster on Alibaba Cloud
- Configuring and managing Kubernetes clusters with Rancher
- Configuring Red Hat OpenShift 
- Configuring a Kubernetes cluster using Ansible
- Troubleshooting installation issues
- Operating Applications on Kubernetes
- Technical requirements
- Deploying workloads using YAML files
- Deploying workloads using Kustomize
- Deploying workloads using Helm charts
- Deploying and operating applications using Kubernetes operators
- Deploying and managing the life cycle of Jenkins X
- Deploying and managing the life cycle of GitLab
- Building CI/CD Pipelines
- Technical requirements
- Creating a CI/CD pipeline in Jenkins X
- Creating a CI/CD pipeline in GitLab
- Creating a CI/CD pipeline in CircleCI
- Setting up a CI/CD pipeline using GitHub Actions
- Setting up a CI/CD pipeline on Amazon Web Services
- Setting up a CI/CD pipeline with Spinnaker on Google Cloud Build
- Getting ready
- How to do it...
- Installing and configuring the Spin CLI
- Configuring a service account for the CI/CD
- Configuring events to trigger a pipeline
- Deploying Spinnaker using Helm
- Creating a Google Cloud Source code repository
- Building projects with Google Cloud Build
- Configuring a Spinnaker pipeline
- Rolling out an application to production
- See also
- Setting up a CI/CD pipeline on Azure DevOps
- Automating Tests in DevOps
- Technical requirements
- Building event-driven automation with StackStorm
- Automating tests with the Litmus framework
- Automating Chaos Engineering with Gremlin
- Automating your code review with Codacy
- Detecting bugs and anti-patterns with SonarQube
- Detecting license compliance issues with FOSSA
- Preparing for Stateful Workloads
- Technical requirements
- Managing Amazon EBS volumes in Kubernetes
- Managing GCE PD volumes in Kubernetes
- Managing Azure Disk volumes in Kubernetes
- Configuring and managing persistent storage using Rook
- Configuring and managing persistent storage using OpenEBS
- Setting up NFS for shared storage on Kubernetes
- Troubleshooting storage issues
- Disaster Recovery and Backup
- Scaling and Upgrading Applications
- Technical requirements
- Scaling applications on Kubernetes
- Assigning applications to nodes
- Creating an external load balancer
- Creating an ingress service and service mesh using Istio
- Creating an ingress service and service mesh using Linkerd
- Auto-healing pods in Kubernetes
- Managing upgrades through blue/green deployments
- Observability and Monitoring on Kubernetes
- Technical requirements
- Monitoring in Kubernetes
- Inspecting containers
- Monitoring using Amazon CloudWatch
- Monitoring using Google Stackdriver
- Monitoring using Azure Monitor
- Monitoring Kubernetes using Prometheus and Grafana
- Monitoring and performance analysis using Sysdig
- Managing the cost of resources using Kubecost
- Securing Applications and Clusters
- Technical requirements
- Using RBAC to harden cluster security
- Configuring Pod Security Policies
- Using Kubernetes CIS Benchmark for security auditing
- Building DevSecOps into the pipeline using Aqua Security
- Monitoring suspicious application activities using Falco
- Securing credentials using HashiCorp Vault
- Logging with Kubernetes
- Other Books You May Enjoy
Managing GCE PD volumes in Kubernetes
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