In this section, we will create the resource configurations required to deploy your applications in Kubernetes. You will learn how to create a Kubernetes manifest, deploy a workload, and roll out a new version using Yet Another Markup Language (YAML) files.
- 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
Deploying workloads using YAML files
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