Book Image

Kubernetes - A Complete DevOps Cookbook

By : Murat Karslioglu
Book Image

Kubernetes - A Complete DevOps Cookbook

By: Murat Karslioglu

Overview of this book

Kubernetes is a popular open source orchestration platform for managing containers in a cluster environment. With this Kubernetes cookbook, you’ll learn how to implement Kubernetes using a recipe-based approach. The book will prepare you to create highly available Kubernetes clusters on multiple clouds such as Amazon Web Services (AWS), Google Cloud Platform (GCP), Azure, Alibaba, and on-premises data centers. Starting with recipes for installing and configuring Kubernetes instances, you’ll discover how to work with Kubernetes clients, services, and key metadata. You’ll then learn how to build continuous integration/continuous delivery (CI/CD) pipelines for your applications, and understand various methods to manage containers. As you advance, you’ll delve into Kubernetes' integration with Docker and Jenkins, and even perform a batch process and configure data volumes. You’ll get to grips with methods for scaling, security, monitoring, logging, and troubleshooting. Additionally, this book will take you through the latest updates in Kubernetes, including volume snapshots, creating high availability clusters with kops, running workload operators, new inclusions around kubectl and more. By the end of this book, you’ll have developed the skills required to implement Kubernetes in production and manage containers proficiently.

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Table of Contents (12 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Sections
Get in touch
1
Building Production-Ready Kubernetes Clusters
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
Free Chapter
2
Operating Applications on Kubernetes
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
3
Building CI/CD Pipelines
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
Setting up a CI/CD pipeline on Azure DevOps
4
Automating Tests in 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
5
Preparing for Stateful Workloads
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
6
Disaster Recovery and Backup
Disaster Recovery and Backup
Technical requirements
Configuring and managing S3 object storage using MinIO
Managing Kubernetes Volume Snapshots and restore
Application backup and recovery using Velero
Application backup and recovery using Kasten
Cross-cloud application migration
7
Scaling and Upgrading Applications
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
8
Observability and Monitoring on Kubernetes
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
9
Securing Applications and Clusters
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
10
Logging with Kubernetes
Logging with Kubernetes
Technical requirements
Accessing Kubernetes logs locally
Accessing application-specific logs
Building centralized logging in Kubernetes using the EFK stack
Logging Kubernetes using Google Stackdriver
Using a managed Kubernetes logging service
Logging for your Jenkins CI/CD environment
11
Other Books You May Enjoy
Other Books You May Enjoy
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Automating Tests in DevOps

In this chapter, we will discuss automating tests in DevOps workflow to accelerate time to production, reduce the loss of delivery risks, and detect service anomalies using known test automation tools on Kubernetes. After following the recipes in this chapter, you will have gained the skills to prevent known defects as well as quickly find new defects to reduce service downtime.

In this chapter, we will cover the following recipes:

  • 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 static code analysis with SonarQube
  • Detecting license compliance issues with Fossa
Previous Section
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