Look Inside
FREE
You can see this entire book for free.Click the table of contents to start reading.
Authoritative and exhaustive. In a hands-on style, the author teaches how to manage the complete lifecycle of any distributed and scalable application.
Kubernetes in Action is a comprehensive guide to effectively developing and running applications in a Kubernetes environment. Before diving into Kubernetes, the book gives an overview of container technologies like Docker, including how to build containers, so that even readers who haven't used these technologies before can get up and running.
About the Technology
Kubernetes is Greek for “helmsman,” your guide through unknown waters. The Kubernetes container orchestration system safely manages the structure and flow of a distributed application, organizing containers and services for maximum efficiency. Kubernetes serves as an operating system for your clusters, eliminating the need to factor the underlying network and server infrastructure into your designs.About the book
Kubernetes in Action teaches you to use Kubernetes to deploy container-based distributed applications. You'll start with an overview of Docker and Kubernetes before building your first Kubernetes cluster. You'll gradually expand your initial application, adding features and deepening your knowledge of Kubernetes architecture and operation. As you navigate this comprehensive guide, you'll explore high-value topics like monitoring, tuning, and scaling.
Table of Contents takes you straight to the bookdetailed table of contents
Part 1: The Overview
1. Introducing Kubernetes
1.1. Understanding the need for a system like Kubernetes
1.1.1. Providing a consistent environment to applications
1.1.2. Moving to continuous delivery and DevOps
1.2. Introducing container technologies
1.2.1. Understanding what containers are
1.2.2. Introducing the Docker container platform
1.2.3. Introducing rkt — an alternative to Docker
1.3. Introducing Kubernetes
1.3.1. Understanding its origins
1.3.2. Looking at Kubernetes from the top of a mountain
1.3.3. Understanding the architecture of a Kubernetes cluster
1.3.4. Running an application on Kubernetes
1.3.5. Understanding the benefits of using Kubernetes
1.4. Summary
2. First steps with Docker and Kubernetes
2.1. Creating, running and sharing a Docker image
2.1.1. Installing Docker and running a Hello World container
2.1.2. Creating a trivial Node.js app
2.1.3. Creating a Dockerfile for the Docker image
2.1.4. Building the Docker image
2.1.5. Running the Docker image
2.1.6. Exploring the inside of a running container
2.1.7. Stopping and removing a container
2.1.8. Pushing the image to a Docker registry
2.2. Setting up a Kubernetes cluster
2.2.1. Running a local single-node Kubernetes cluster with minikube
2.2.2. Using a hosted Google Container Engine Kubernetes cluster
2.2.3. Setting up an alias and command-line completion for kubectl
2.3. Running our first app on Kubernetes
2.3.1. Deploying our Node.js app
2.3.2. Accessing our web application
2.3.3. The logical parts of our system
2.3.4. Horizontally scaling the application
2.3.5. Examining what nodes our app is running on
2.3.6. Introducing the Kubernetes Dashboard
2.4. Summary
Part 2: Core concepts
3. Pods: running containers in Kubernetes
3.1. Introducing pods
3.1.1. Understanding why we need pods
3.1.2. Understanding pods
3.1.3. Organizing containers across pods properly
3.2. Creating pods from YAML or JSON descriptors
3.2.1. Examining a YAML descriptor of an existing pod
3.2.2. Creating a simple YAML descriptor for a pod
3.2.3. Using kubectl create to create the pod
3.2.4. Viewing application logs
3.2.5. Sending requests to the pod
3.3. Organizing pods with labels
3.3.1. Introducing labels
3.3.2. Specifying labels when creating a pod
3.3.3. Modifying labels of existing pods
3.4. Listing subsets of pods through label selectors
3.4.1. Listing pods using a label selector
3.4.2. Using multiple conditions in a label selector
3.5. Using labels and selectors to constrain pod scheduling
3.5.1. Using labels for categorizing worker nodes
3.5.2. Scheduling pods to specific nodes
3.5.3. Scheduling to one specific node
3.6. Annotating pods
3.6.1. Looking up an object's annotations
3.6.2. Adding and modifying annotations
3.7. Using namespaces to group resources
3.7.1. Understanding the need for namespaces
3.7.2. Discovering other namespaces and their pods
3.7.3. Creating a namespace
3.7.4. Managing objects in other namespaces
3.7.5. Understanding the isolation provided by namespaces
3.8. Stopping and removing pods
3.8.1. Deleting a pod by name
3.8.2. Deleting pods using label selectors
3.8.3. Deleting pods by deleting the whole namespace
3.8.4. Deleting all pods in a namespace, while keeping the namespace
3.8.5. Deleting (almost) all resources in a namespace
3.9. Summary
4. Replication and other controllers: deploying managed pods
4.1. Keeping pods healthy
4.1.1. Introducing liveness probes
4.1.2. Creating an HTTP-based liveness probe
4.1.3. Seeing a liveness probe in action
4.1.4. Configuring additional properties of the liveness probe
4.1.5. Creating good and effective liveness probes
4.2. Introducing Replication Controllers
4.2.1. The operation of a replication controller
4.2.2. Creating a replication controller
4.2.3. Seeing the replication controller in action
4.2.4. Moving pods in and out of the scope of a replication controller
4.2.5. Changing the pod template
4.2.6. Horizontally scaling pods
4.2.7. Deleting a replication controller
4.3. Using ReplicaSets instead of replication controllers
4.3.1. Comparing a ReplicaSet to a ReplicationController
4.3.2. Defining a ReplicaSet
4.3.3. Creating and examining a ReplicaSet
4.3.4. Using the ReplicaSet's more expressive label selectors
4.3.5. Wrapping up ReplicaSets
4.4. Running exactly one pod on each node with DaemonSets
4.4.1. Using a DaemonSet for running a pod on every node
4.4.2. Using a DaemonSet to run pods only on some nodes
4.5. Running pods that perform a single completable task
4.5.1. Introducing the Job resource
4.5.2. Defining a Job
4.5.3. Seeing a Job run a pod
4.5.4. Running multiple pod instances in a Job
4.5.5. Limiting the time allowed for a job pod to complete
4.6. Scheduling jobs to run periodically or once in the future
4.6.1. Creating a CronJob
4.6.2. Understanding how scheduled jobs are run
4.7. Summary
5. Services: enabling clients to discover and talk to pods
5.1. Introducing services
5.1.1. Creating services
5.1.2. Discovering services
5.2. Connecting to services living outside the cluster
5.2.1. Introducing service endpoints
5.2.2. Manually configuring service endpoints
5.2.3. Creating an alias for an external service
5.3. Exposing services to external clients
5.3.1. Using a NodePort service
5.3.2. Exposing a service through an external load balancer
5.3.3. Understanding the peculiarities of external connections
5.4. Exposing services externally through an Ingress resource
5.4.1. Creating an Ingress resource
5.4.2. Accessing the service through the ingress
5.4.3. Exposing multiple services through the same domain name
5.4.4. Configuring Ingress to handle TLS traffic
5.5. Signaling when a pod is ready to accept connections
5.5.1. Introducing readiness probes
5.5.2. Adding a readiness probe to a pod
5.5.3. Understanding how real-world readiness probes should work
5.6. Using a headless service for discovering individual pods
5.6.1. Creating a headless service
5.6.2. Discovering pods through DNS
5.6.3. Discovering all pods - including those that aren't ready
5.7. Troubleshooting services
5.8. Summary
6. Volumes: attaching disk storage to containers
6.1. Introducing Volumes
6.1.1. Explaining volumes in an example
6.1.2. Introducing available volumes types
6.2. Using volumes to share data between containers
6.2.1. Using an emptyDir volume
6.2.2. Using a Git repository as the starting point for a volume
6.3. Accessing files on the worker node's filesystem
6.3.1. Introducing the hostPath volume
6.3.2. Examining system pods that use hostPath volumes
6.4. Using persistent storage
6.4.1. Using a GCE Persistent Disk in a pod volume
6.4.2. Using other types of volumes with underlying persistent storage
6.5. Decoupling pods from the underlying storage technology
6.5.1. Introducing PersistentVolumes and PersistentVolumeClaims
6.5.2. Creating a PersistentVolume
6.5.3. Claiming a PersistentVolume by creating a PersistentVolumeClaim
6.5.4. Using a PersistentVolumeClaim in a pod
6.5.5. Understanding the benefits of using persistent volumes and claims
6.5.6. Recycling persistent volumes
6.6. Dynamic provisioning of persistent volumes
6.6.1. Defining the available storage types through StorageClass resources
6.6.2. Requesting the storage class in a PersistentVolumeClaim
6.6.3. Dynamic provisioning without specifying a storage class
6.7. Summary
7. ConfigMaps & Secrets: configuring applications
7.1. Configuring apps in general
7.2. Passing command-line arguments to containers
7.2.1. Defining the command and arguments in Docker
7.3. Setting environment variables for a container
7.3.1. Specifying an environment variable in a container definition
7.4. Decoupling configuration with a ConfigMap
7.4.1. Creating a ConfigMap
7.4.2. Passing a ConfigMap entry to a container as an environment variable
7.4.3. Passing all entries of a ConfigMap as environment variables at once
7.4.4. Passing a ConfigMap entry as a command-line argument
7.4.5. Using a configMap volume to expose ConfigMap entries as files
7.4.6. Updating an app's config without having to restart the app
7.5. Using Secrets to pass sensitive data to containers
7.5.1. Exposing a secret as a set files in a secret volume
7.5.2. Creating a Secret
7.5.3. Comparing ConfigMaps and Secrets
7.5.4. Understanding image pull secrets
7.6. Summary
8. Accessing pod metadata and other resources from applications
8.1. Passing metadata through the Downward API
8.1.1. Understanding the available metadata
8.1.2. Exposing metadata through environment variables
8.1.3. Passing metadata through files in a downwardAPI volume
8.2. Talking to the Kubernetes API server
8.2.1. Exploring the Kubernetes REST API
8.2.2. Talking to the API server from within a pod
8.2.3. Simplifying API server communication with ambassador containers
8.2.4. Using client libraries to talk to the API server
8.3. Summary
9. Deployments: updating applications declaratively
9.1. Replacing pods with a new version
9.1.1. Deleting old pods and replacing them with new ones afterwards
9.1.2. Spinning up new pods and then deleting the old ones
9.2. Performing an automatic rolling update with kubectl
9.3. Using Deployments for managing apps declaratively
9.3.1. Creating a Deployment
9.3.2. Updating a Deployment
9.3.3. Rolling back a deployment
9.3.4. Controlling the rate of the rollout
9.3.5. Blocking rollouts of bad versions
9.4. Summary
10. StatefulSets: deploying replicated stateful applications
10.1. Running multiple replicas with separate storage and identity for each
10.2. Introducing StatefulSets
10.2.1. Providing a stable network identity
10.2.2. Providing stable dedicated storage to each pet
10.3. Creating and using a StatefulSet
10.3.1. Creating the app and container image
10.3.2. Deploying the app through a StatefulSet
10.3.3. Playing with our pets
10.4. Discovering other members of the StatefulSet
10.4.1. Implementing peer discovery through DNS
10.4.2. Updating a stateful set
10.4.3. Trying out our clustered data store
10.5. Summary
Part 3: Beyond the basics
11. Understanding Kubernetes internals
11.1. Understanding the architecture
11.1.1. Understanding the distributed nature of Kubernetes components
11.1.2. Understanding how Kubernetes uses etcd
11.1.3. Understanding what the API server does
11.1.4. Understanding how the API server notifies clients of resource changes
11.1.5. Understanding the Scheduler
11.1.6. Introducing the controllers running in the Controller Manager
11.1.7. Understanding what the Kubelet does
11.1.8. Understanding the role of the Service Proxy
11.1.9. Introducing Kubernetes add-ons
11.1.10. Bringing it all together
11.2. Understanding how controllers cooperate
11.2.1. Understanding which components are involved
11.2.2. Understanding the chain of events
11.2.3. Observing cluster events
11.3. Exploring what a running pod is
11.4. Understanding inter-pod networking
11.4.1. Understanding what the network must be like
11.4.2. Diving deeper into how networking works
11.4.3. Introducing the Container Network Interface
11.5. Understanding how services are implemented
11.5.1. Introducing the kube-proxy
11.5.2. Understanding how kube-proxy uses iptables
11.6. Understanding highly-available clusters
11.6.1. Making your apps highly available
11.6.2. Making Kubernetes Control Plane components highly available
11.7. Summary
12. Securing clusters using authentication and authorization
12.1. Understanding authentication
12.1.1. Understanding users and groups
12.1.2. Introducing service accounts
12.1.3. Creating service accounts
12.1.4. Assigning a service account to a pod
12.2. Securing the cluster with Role Based Access Control
12.2.1. Introducing the RBAC authorization plugin
12.2.2. Introducing RBAC resources
12.2.3. Using Roles and RoleBindings
12.2.4. Using ClusterRoles and ClusterRoleBindings
12.2.5. Understandingdefault ClusterRoles and ClusterRoleBindings
12.2.6. Granting authorization permissions wisely
12.3. Summary
13. Securing cluster nodes and the network
13.1. Using the host node’s namespaces in a pod
13.1.1. Using the node’s network namespace in a pod
13.1.2. Binding to a host port without using the host’s network namespace
13.1.3. Using the node’s PID and IPC namespaces
13.2. Configuring the container’s security context
13.2.1. Running a container as a specific user
13.2.2. Preventing a container from running as root
13.2.3. Running pods in privileged mode
13.2.4. Adding individual Kernel capabilities to a container
13.2.5. Dropping capabilities from a container
13.2.6. Preventing processes from writing to the container’s filesystem
13.2.7. Sharing volumes when containers run as different users
13.3. Restricting the use of security-related features in pods
13.3.1. Introducing the PodSecurityPolicy resource
13.3.2. Understanding runAsUser, fsGroup and supplementalGroups policies
13.3.3. Configuring allowed, default and disallowed capabilities
13.3.4. Constraining the types of volumes pods can use
13.3.5. Assigningdifferent PodSecurityPolicies to different users and groups
13.4. Isolating the pod network
13.4.1. Enabling network isolation in a namespace
13.4.2. Allowing only some pods in the namespace to connect to a server pod
13.4.3. Isolating the network between Kubernetes namespaces
13.5. Summary
14. Managing computational resources
14.1. Requesting resources for a pod’s containers
14.1.1. Creating pods with resource requests
14.1.2. Understanding how resource requests affect scheduling
14.1.3. Understanding how CPU requests affect CPU time sharing
14.1.4. Defining and requesting custom resources
14.2. Limiting resources available to a container
14.2.1. Setting a hard limit for the amount of resources a container can use
14.2.2. Exceeding the limits
14.2.3. Understanding how apps in containers see limits
14.3. Understanding PodQoS classes
14.3.1. Defining the QoS class for a pod
14.3.2. Understanding which process getskilled when memory is low
14.4. Setting default requests and limits for pods per namespace
14.4.1. Introducing the LimitRange resource
14.4.2. Creating a LimitRange object
14.4.3. Enforcing the limits
14.4.4. Applying default resource requests and limits
14.5. Limiting the total resources available in a namespace
14.5.1. Introducing the ResourceQuota resource
14.5.2. Specifying a quota for persistent storage
14.5.3. Limiting the number of objects that can be created
14.5.4. Specifying quotas for specific pod states and/or QoS classes
14.6. Monitoring pod resource usage
14.6.1. Collecting and retrieving actual resource usages
14.6.2. Storing and analyzing historical resource consumption statistics
14.7. Summary
15. Automatic scaling of pods & cluster nodes
15.1. Horizontal pod auto-scaling
15.1.1. Understanding the autoscaling process
15.1.2. Scaling based on CPU utilization
15.1.3. Scaling based on memory consumption
15.1.4. Scaling all the way down to zero replicas
15.2. Vertical pod auto-scaling
15.3. Horizontal scaling of cluster nodes
15.3.1. Preventing pods from being scheduled to a node
15.3.2. Introducing the Cluster Autoscaler
15.3.3. Enabling the cluster autoscaler
15.3.4. Limiting pod disruption during cluster scale-down
15.4. Summary
16. Advanced scheduling
16.1. Using taints and tolerations to repel pods from some nodes
16.1.1. Introducing taints and tolerations
16.1.2. Adding custom taints to a node
16.1.3. Adding tolerations to Pods
16.1.4. Understanding what taints and tolerations can be used for
16.2. Using node affinity to attract pods to certain nodes
16.2.1. Specifying hard node affinity rules
16.2.2. Prioritizing nodes when scheduling a Pod
16.3. Co-locating pods with pod affinity and anti-affinity
16.3.1. Using inter-pod affinity to deploy Pods on the same node
16.3.2. Deploying pods in the same rack, availability zone or geographic region
16.3.3. Expressing Pod affinity preferences instead of hard requirements
16.3.4. Scheduling pods away from each other with pod anti-affinity
16.4. Summary
17. Best practices for developing apps
17.1. Bringing everything together
17.2. Understanding the pod's lifecycle
17.2.1. Applications must expect to be killed and relocated
17.2.2. Rescheduling of dead or partially dead pods
17.2.3. Adding lifecycle hooks
17.2.4. Understanding pod shutdown
17.3. Making sure all client requests are handled properly
17.3.1. Preventing broken client connections when a pod is starting up
17.3.2. Preventing broken connections during pod shutdown
17.3.3. Making good container images
17.3.4. Properly tagging your images and using imagePullPolicy wisely
17.3.5. Using multi-dimensional instead of single-dimensional labels
17.3.6. Describing each resource through annotations
17.3.7. Providing information on why the process terminated
17.4. Best practices for development and testing
17.4.1. Running apps outside of Kubernetes during development
17.4.2. Using minikube as the next step in development
17.4.3. Versioning resource manifests
17.4.4. Employing Continuous Integration and Continuous Delivery (CI/CD)
17.5. Summary
18. Extending Kubernetes
18.1. Defining custom API objects
18.1.1. Introducing ThirdPartyResources
18.1.2. Automating ThirdPartyResources
18.1.3. Validating custom objects
18.2. Replacing Kubernetes components
18.2.1. Replacing Docker with rkt
18.2.2. Using other container runtimes through the CRI
18.3. Platforms built on top of Kubernetes
18.3.1. Red Hat OpenShift Container Platform
18.4. Summary
Appendixes
Appendix A: Using kubectl with multiple clusters
A.1. Switching between minikube and Google Container Engine
A.2. Using kubectl with multiple clusters or namespaces
A.2.1. Configuring the location of the kubeconfig file
A.2.2. Understanding the contents of the kubeconfig file
A.2.3. Listing, adding and modifying kubeconfig entries
A.2.4. Switching between contexts
A.2.5. Listing contexts and clusters
A.2.6. Cleaning up contexts and clusters
Appendix B: Setting up a multi-node cluster with kubeadm
B.1. Setting up the OS and required packages
B.1.1. Creating the virtual machine
B.1.2. Configuring the network adapter for the VM
B.1.3. Installing the operating system
B.1.4. Installing Docker and Kubernetes
B.1.5. Cloning the VM
B.2. Configuring the master with kubeadm
B.3. Configuring worker nodes with kubeadm
B.4. Setting up the container network
B.5. Using the cluster from our local machine
Appendix C: Using other Container Runtimes
C.1. Replacing Docker with rkt
C.1.1. Configuring Kubernetes to use rkt
C.1.2. Trying out rkt with Minikube
C.2. Using other container runtimes through the CRI
C.2.1. Introducing the CRI-O Container Runtime
C.2.2. Running apps in Virtual Machines instead of Containers
Appendix D: Cluster federation
D.1. Introducing Kubernetes Cluster Federation
D.2. Understanding the architecture
D.3. Understanding federated API objects
D.4. Achieving high availability through federated clusters
What's inside
- Kubernetes’ internals
- Deploying containers across a cluster
- Securing clusters
- Updating applications with zero downtime
placing your order...
Don't refresh or navigate away from the page.
- customers also bought these items
- Cloud Native Patterns
- Securing DevOps
- Microservices Patterns
- Docker in Action, Second Edition
- Machine Learning with TensorFlow, Second Edition
Prices displayed in rupees will be charged in USD when you check out.
customers also reading
This book
1-hop
2-hops
3-hops
FREE domestic shipping on three or more pBooks