Book Image

The DevOps 2.3 Toolkit

By : Viktor Farcic

Book Image

The DevOps 2.3 Toolkit

By: Viktor Farcic

Overview of this book

Building on The DevOps 2.0 Toolkit, The DevOps 2.1 Toolkit: Docker Swarm, and The DevOps 2.2 Toolkit: Self-Sufficient Docker Clusters, Viktor Farcic brings his latest exploration of the DevOps Toolkit as he takes you on a journey to explore the features of Kubernetes. The DevOps 2.3 Toolkit: Kubernetes is a book in the series that helps you build a full DevOps Toolkit. This book in the series looks at Kubernetes, the tool designed to, among other roles, make it easier in the creation and deployment of highly available and fault-tolerant applications at scale, with zero downtime. Within this book, Viktor will cover a wide range of emerging topics, including what exactly Kubernetes is, how to use both first and third-party add-ons for projects, and how to get the skills to be able to call yourself a “Kubernetes ninja.” Work with Viktor and dive into the creation and exploration of Kubernetes with a series of hands-on guides.

Preface

Free Chapter

How Did We Get Here?

How Did We Get Here?

A glimpse from the past

A short history of infrastructure management

A short history of deployment processes

What is a container scheduler?

What is Kubernetes?

Running Kubernetes Cluster Locally

Running Kubernetes Cluster Locally

Installing kubectl

Installing Minikube

Creating a local Kubernetes cluster with Minikube

Creating Pods

Creating a Cluster

Quick and dirty way to run Pods

Defining Pods through declarative syntax

Running multiple containers in a single Pod

Monitoring health

Pods are (almost) useless (by themselves)

Scaling Pods With ReplicaSets

Scaling Pods With ReplicaSets

Creating a Cluster

Creating ReplicaSets

Operating ReplicaSets

Using Services to Enable Communication between Pods

Using Services to Enable Communication between Pods

Creating a Cluster

Creating Services by exposing ports

Creating Services through declarative syntax

Splitting the Pod and establishing communication through Services

Defining multiple objects in the same YAML file

Discovering Services

Kubernetes Pods, ReplicaSets, and Services compared to Docker Swarm stacks

Deploying Releases with Zero-Downtime

Deploying Releases with Zero-Downtime

Creating a Cluster

Deploying new releases

Updating Deployments

Zero-Downtime Deployments

Rolling back or rolling forward?

Rolling back failed Deployments

Merging everything into the same YAML definition

Updating multiple objects

Scaling Deployments

Kubernetes Deployments compared to Docker Swarm stacks

Using Ingress to Forward Traffic

Using Ingress to Forward Traffic

Creating a cluster

Exploring deficiencies when enabling external access through Kubernetes services

Enabling Ingress controllers

Creating Ingress Resources based on paths

Creating Ingress resources based on domains

Creating an Ingress resource with default backends

Kubernetes Ingress compared to Docker Swarm equivalent

Using Volumes to Access Host's File System

Using Volumes to Access Host's File System

Creating a cluster

Accessing host's resources through hostPath volumes

Using hostPath volume type to inject configuration files

Using gitRepo to mount a Git repository

Persisting state through the emptyDir volume type

Using ConfigMaps to Inject Configuration Files

Using ConfigMaps to Inject Configuration Files

Creating a cluster

Injecting configurations from files

Injecting configurations from key/value literals

Injecting configurations from environment files

Converting ConfigMap output into environment variables

Defining ConfigMaps as YAML

A plea NOT to use ConfigMaps!

Kubernetes ConfigMaps compared to Docker Swarm configs

Using Secrets to Hide Confidential Information

Using Secrets to Hide Confidential Information

Creating a Cluster

Exploring built-in Secrets

Creating and mounting generic Secrets

Secrets compared to ConfigMaps

Not so secretive Secrets

Kubernetes Secrets compared to Docker Swarm Secrets

Dividing a Cluster into Namespaces

Dividing a Cluster into Namespaces

Creating a Cluster

Deploying the first release

Exploring virtual clusters

Exploring the existing Namespaces

Deploying to a new Namespace

Communicating between Namespaces

Deleting a Namespace and all its Objects

Kubernetes Namespaces compared to Docker Swarm equivalent (if there is any)

Securing Kubernetes Clusters

Securing Kubernetes Clusters

Accessing Kubernetes API

Authorizing requests

Creating a Cluster

Exploring RBAC authorization

Peeking into pre-defined Cluster roles

Creating Role bindings and Cluster Role bindings

Replacing Users with Groups

Kubernetes RBAC compared to Docker Swarm RBAC

Managing Resources

Managing Resources

Creating a cluster

Defining container memory and CPU resources

Measuring actual memory and CPU consumption

Exploring the effects of discrepancies between resource specifications and resource usage

Adjusting resources based on actual usage

Exploring quality of service (QoS) contracts

Defining resource defaults and limitations within a namespace

Defining resource quotas for a namespace

Kubernetes resource management compared to docker swarm equivalent

Creating a Production-Ready Kubernetes Cluster

Creating a Production-Ready Kubernetes Cluster

What is kubernetes operations (kops) project?

Preparing for the cluster setup

Creating a kubernetes cluster in AWS

Exploring the components that constitute the cluster

Updating the cluster

Upgrading the cluster manually

Upgrading the cluster automatically

Accessing the cluster

Deploying applications

Exploring high-availability and fault-tolerance

Giving others access to the cluster

Destroying the cluster

Kubernetes operations (kops) compared to Docker for AWS

Persisting State

Persisting State

Creating a Kubernetes cluster

Creating AWS volumes

Creating Kubernetes persistent volumes

Claiming persistent volumes

Attaching claimed volumes to Pods

Using storage classes to dynamically provision persistent volumes

Using default storage classes

Creating storage classes

The End

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Exploring high-availability and fault-tolerance

The cluster would not be reliable if it wouldn't be fault tolerant. Kops intents to make it so, but we're going to validate that anyways.

Let's retrieve the list of worker node instances:

aws ec2 \
    describe-instances | jq -r \
    ".Reservations[].Instances[] \
    | select(.SecurityGroups[]\
    .GroupName==\"nodes.$NAME\")\
    .InstanceId"

We used aws ec2 describe-instances to retrieve all the instances (five in total). The output was sent to jq, which filtered them by the security group dedicated to worker nodes.

The output is as follows:

i-063fabc7ad5935db5
i-04d32c91cfc084369

We'll terminate one of the worker nodes. To do that, we'll pick a random one, and retrieve its ID.

INSTANCE_ID=$(aws ec2 \
    describe-instances | jq -r \
    ".Reservations[].Instances[] \ 
 ...