book

Kubernetes: Up and Running

by Kelsey Hightower, Brendan Burns, Joe Beda

September 2017

Intermediate to advanced

269 pages

4h 38m

English

O'Reilly Media, Inc.

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Kubernetes: A DedicationWho Should Read This BookWhy We Wrote This BookA Word on Cloud-Native Applications TodayNavigating This BookOnline ResourcesConventions Used in This BookUsing Code ExamplesO’Reilly SafariHow to Contact Us
VelocityThe Value of ImmutabilityDeclarative ConfigurationSelf-Healing SystemsScaling Your Service and Your TeamsDecouplingEasy Scaling for Applications and ClustersScaling Development Teams with MicroservicesSeparation of Concerns for Consistency and ScalingAbstracting Your InfrastructureEfficiencySummary
Container ImagesThe Docker Image FormatBuilding Application Images with DockerDockerfilesImage SecurityOptimizing Image SizesStoring Images in a Remote RegistryThe Docker Container RuntimeRunning Containers with DockerExploring the kuard ApplicationLimiting Resource UsageCleanupSummary
Installing Kubernetes on a Public Cloud ProviderGoogle Container ServiceInstalling Kubernetes with Azure Container ServiceInstalling Kubernetes on Amazon Web ServicesInstalling Kubernetes Locally Using minikubeRunning Kubernetes on Raspberry PiThe Kubernetes ClientChecking Cluster StatusListing Kubernetes Worker NodesCluster ComponentsKubernetes ProxyKubernetes DNSKubernetes UISummary
NamespacesContextsViewing Kubernetes API ObjectsCreating, Updating, and Destroying Kubernetes ObjectsLabeling and Annotating ObjectsDebugging CommandsSummary
Pods in KubernetesThinking with PodsThe Pod ManifestCreating a PodCreating a Pod ManifestRunning PodsListing PodsPod DetailsDeleting a PodAccessing Your PodUsing Port ForwardingGetting More Info with LogsRunning Commands in Your Container with execCopying Files to and from ContainersHealth ChecksLiveness ProbeReadiness ProbeTypes of Health ChecksResource ManagementResource Requests: Minimum Required ResourcesCapping Resource Usage with LimitsPersisting Data with VolumesUsing Volumes with PodsDifferent Ways of Using Volumes with PodsPersisting Data Using Remote DisksPutting It All TogetherSummary
LabelsApplying LabelsModifying LabelsLabel SelectorsLabel Selectors in API ObjectsAnnotationsDefining AnnotationsCleanupSummary
What Is Service Discovery?The Service ObjectService DNSReadiness ChecksLooking Beyond the ClusterCloud IntegrationAdvanced DetailsEndpointsManual Service Discoverykube-proxy and Cluster IPsCluster IP Environment VariablesCleanupSummary
Reconciliation LoopsRelating Pods and ReplicaSetsAdopting Existing ContainersQuarantining ContainersDesigning with ReplicaSetsReplicaSet SpecPod TemplatesLabelsCreating a ReplicaSetInspecting a ReplicaSetFinding a ReplicaSet from a PodFinding a Set of Pods for a ReplicaSetScaling ReplicaSetsImperative Scaling with kubectl ScaleDeclaratively Scaling with kubectl applyAutoscaling a ReplicaSetDeleting ReplicaSetsSummary
DaemonSet SchedulerCreating DaemonSetsLimiting DaemonSets to Specific NodesAdding Labels to NodesNode SelectorsUpdating a DaemonSetUpdating a DaemonSet by Deleting Individual PodsRolling Update of a DaemonSetDeleting a DaemonSetSummary

The Job ObjectJob PatternsOne ShotParallelismWork QueuesSummary
ConfigMapsCreating ConfigMapsUsing a ConfigMapSecretsCreating SecretsConsuming SecretsPrivate Docker RegistriesNaming ConstraintsManaging ConfigMaps and SecretsListingCreatingUpdatingSummary
Your First DeploymentDeployment InternalsCreating DeploymentsManaging DeploymentsUpdating DeploymentsScaling a DeploymentUpdating a Container ImageRollout HistoryDeployment StrategiesRecreate StrategyRollingUpdate StrategySlowing Rollouts to Ensure Service HealthDeleting a DeploymentSummary
Importing External ServicesServices Without SelectorsLimitations of External Services: Health CheckingRunning Reliable SingletonsRunning a MySQL SingletonDynamic Volume ProvisioningKubernetes-Native Storage with StatefulSetsProperties of StatefulSetsManually Replicated MongoDB with StatefulSetsAutomating MongoDB Cluster CreationPersistent Volumes and StatefulSetsOne Final Thing: Readiness ProbesSummary
ParsePrerequisitesBuilding the parse-serverDeploying the parse-serverTesting ParseGhostConfiguring GhostRedisConfiguring RedisCreating a Redis ServiceDeploying RedisPlaying with Our Redis ClusterSummary
Parts ListFlashing ImagesFirst Boot: MasterSetting Up NetworkingInstalling KubernetesSetting Up the ClusterSummary

Content preview from Kubernetes: Up and Running

Chapter 9. DaemonSets

ReplicaSets are generally about creating a service (e.g., a web server) with multiple replicas for redundancy. But that is not the only reason you may want to replicate a set of Pods within a cluster. Another reason to replicate a set of Pods is to schedule a single Pod on every node within the cluster. Generally, the motivation for replicating a Pod to every node is to land some sort of agent or daemon on each node, and the Kubernetes object for achieving this is the DaemonSet.

A DaemonSet ensures a copy of a Pod is running across a set of nodes in a Kubernetes cluster. DaemonSets are used to deploy system daemons such as log collectors and monitoring agents, which typically must run on every node. DaemonSets share similar functionality with ReplicaSets; both create Pods that are expected to be long-running services and ensure that the desired state and the observed state of the cluster match.

Given the similarities between DaemonSets and ReplicaSets, it’s important to understand when to use one over the other. ReplicaSets should be used when your application is completely decoupled from the node and you can run multiple copies on a given node without special consideration. DaemonSets should be used when a single copy of your application must run on all or a subset of the nodes in the cluster.

You should generally not use scheduling restrictions or other parameters to ensure that Pods do not colocate on the same node. If you find yourself wanting a single ...