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The Concepts section helps you learn about the parts of the Kubernetes system and the abstractions Kubernetes uses to represent your cluster , and helps you obtain a deeper understanding of how Kubernetes works. Overview Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available. Cluster Architecture The architectural concepts behind Kubernetes. Containers Technology for packaging an application along with its runtime dependencies. Workloads Understand Pods, the smallest deployable compute object in Kubernetes, and the higher-level abstractions that help you to run them. Services, Load Balancing, and Networking Concepts and resources behind networking in Kubernetes. Storage Ways to provide both long-term and temporary storage to Pods in your cluster. Configuration Resour

ces that Kubernetes provides for configuring Pods. Security Concepts for keeping your cloud-native workload secure. Policies Manage security and best-practices with policies. Scheduling, Preemption and Eviction In Kubernetes, scheduling refers to making sure that Pods are matched to Nodes so that the kubelet can run them. Preemption is the process of terminating Pods with lower Priority so tha

Pods with higher Priority can schedule on Nodes. Eviction is the process of proactively terminating one or more Pods on resource-starved Nodes. Cluster Administration Lower-level detail relevant to creating or administering a Kubernetes cluster. Windows in Kubernetes Kubernetes supports nodes that run Microsoft Windows. Extending Kubernetes Different ways to change the behavior of your Kubernetes cluster. Overview Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available. This page is an overview of Kubernetes. Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are wi

dely available. The name Kubernetes originates from Greek, meaning helmsman or pilot. K8s as an abbreviation results from counting the eight letters between the "K" and the "s". Google open- sourced the Kubernetes project in 2014. Kubernetes combines over 15 years of Google's experience running production workloads at scale with best-of-breed ideas and practices from the community. Going back in time Let's take a look at why Kubernetes is so useful by going back in time. Deployment evolution Traditional deployment era: Early on, organizations ran applications on physical servers. There was no way to define resource boundaries for applications in a physical server, and this caused resource allocation issues. For example, if multiple applications run on a physical server, there can be instances where one application would take up most of the resources, and as a result, the other applications would underperform. A solution for this would be to run each application on a different physica

l server. But this did not scale as resources were underutilized, and it was expensive for organizations to maintain many physical servers. Virtualized deployment era: As a solution, virtualization was introduced. It allows you to run multiple Virtual Machines (VMs) on a single physical server's CPU. Virtualization allows applications to be isolated between VMs and provides a level of security as the information of one application cannot be freely accessed by another application

Virtualization allows better utilization of resources in a physical server and allows better scalability because an application can be added or updated easily, reduces hardware costs, and much more. With virtualization you can present a set of physical resources as a cluster of disposable virtual machines. Each VM is a full machine running all the components, including its own operating system, on top of the virtualized hardware. Container deployment era: Containers are similar to VMs, but they have relaxed isolation properties to share the Operating System (OS) among the applications. Therefore, containers are considered lightweight. Similar to a VM, a container has its own filesystem, share of CPU, memory, process space, and more. As they are decoupled from the underlying infrastructure, they are portable across clouds and OS distributions. Containers have become popular because they provide extra benefits, such as: Agile application creation and deployment: increased ease and effic

iency of container image creation compared to VM image use. Continuous development, integration, and deployment: provides for reliable and frequent container image build and deployment with quick and efficient rollbacks (due to image immutability). Dev and Ops separation of concerns: create application container images at build/release time rather than deployment time, thereby decoupling applications from infrastructure. Observability: not only surfaces OS-level information and metrics, but also application health and other signals. Environmental consistency across development, testing, and production: runs the same on a laptop as it does in the cloud. Cloud and OS distribution portability: runs on Ubuntu, RHEL, CoreOS, on-premises, on major public clouds, and anywhere else. Application-centric management: raises the level of abstraction from running an OS on virtual hardware to running an application on an OS using logical resources. Loosely coupled, distributed, elastic, liberated mi

cro-services: applications are broken into smaller, independent pieces and can be deployed and managed dynamically – not a monolithic stack running on one big single-purpose machine. Resource isolation: predictable application performance. Resource utilization: high efficiency and density. Why you need Kubernetes and what it can do Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Wouldn't it be easier if this behavior was handled by a system? That's how Kubernetes comes to the rescue! Kubernetes provides you with a framework to run distributed systems resiliently. It takes care of scaling and failover for your application, provides deployment patterns, and more. For example: Kubernetes can easily manage a canary deployment for your system.• • • • • • • • •

Kubernetes provides you with: Service discovery and load balancing Kubernetes can expose a container using the DNS name or using their own IP address. If traffic to a container is high, Kubernetes is able to load balance and distribute the network traffic so that the deployment is stable. Storage orchestration Kubernetes allows you to automatically mount a storage system of your choice, such as local storages, public cloud providers, and more. Automated rollouts and rollbacks You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate. For example, you can automate Kubernetes to create new containers for your deployment, remove existing containers and adopt all their resources to the new container. Automatic bin packing You provide Kubernetes with a cluster of nodes that it can use to run containerized tasks. You tell Kubernetes how much CPU and memory (RAM) each container needs. Kube

rnetes can fit containers onto your nodes to make the best use of your resources. Self-healing Kubernetes restarts containers that fail, replaces containers, kills containers that don't respond to your user-defined health check, and doesn't advertise them to clients until they are ready to serve. Secret and configuration management Kubernetes lets you store and manage sensitive information, such as passwords, OAuth tokens, and SSH keys. You can deploy and update secrets and application configuration without rebuilding your container images, and without exposing secrets in your stack configuration. Batch execution In addition to services, Kubernetes can manage your batch and CI workloads, replacing containers that fail, if desired. Horizontal scaling Scale your application up and down with a simple command, with a UI, or automatically based on CPU usage. IPv4/IPv6 dual-stack Allocation of IPv4 and IPv6 addresses to Pods and Services Designed for extensibility Add features to your

Kubernetes cluster without changing upstream source code. What Kubernetes is not Kubernetes is not a traditional, all-inclusive PaaS (Platform as a Service) system. Since Kubernetes operates at the container level rather than at the hardware level, it provides some generally applicable features common to PaaS offerings, such as deployment, scaling, load balancing, and lets users integrate their logging, monitoring, and alerting solutions. However, Kubernetes is not monolithic, and these default solutions are optional and pluggable. Kubernetes provides the building blocks for building developer platforms, but preserves user choice and flexibility where it is important. Kubernetes: Does not limit the types of applications supported. Kubernetes aims to support an extremely diverse variety of workloads, including stateless, stateful, and data-processing workloads. If an application can run in a container, it should run great on Kubernetes. Does not deploy source code and does not build you

r application. Continuous Integration, Delivery, and Deployment (CI/CD) workflows are determined by organization cultures and preferences as well as technical requirements. Does not provide application-level services, such as middleware (for example, message buses), data-processing frameworks (for example, Spark), databases (for example, MySQL), caches, nor cluster storage systems (for example, Ceph) as built-in services.• • • • • • • • • • • •

Such components can run on Kubernetes, and/or can be accessed by applications running on Kubernetes through portable mechanisms, such as the Open Service Broker . Does not dictate logging, monitoring, or alerting solutions. It provides some integrations as proof of concept, and mechanisms to collect and export metrics. Does not provide nor mandate a configuration language/system (for example, Jsonnet). It provides a declarative API that may be targeted by arbitrary forms of declarative specifications. Does not provide nor adopt any comprehensive machine configuration, maintenance, management, or self-healing systems. Additionally, Kubernetes is not a mere orchestration system. In fact, it eliminates the need for orchestration. The technical definition of orchestration is execution of a defined workflow: first do A, then B, then C. In contrast, Kubernetes comprises a set of independent, composable control processes that continuously drive the current state towards the provided desired s

tate. It shouldn't matter how you get from A to C. Centralized control is also not required. This results in a system that is easier to use and more powerful, robust, resilient, and extensible. What's next Take a look at the Kubernetes Components Take a look at the The Kubernetes API Take a look at the Cluster Architecture Ready to Get Started ? Objects In Kubernetes Kubernetes objects are persistent entities in the Kubernetes system. Kubernetes uses these entities to represent the state of your cluster. Learn about the Kubernetes object model and how to work with these objects. This page explains how Kubernetes objects are represented in the Kubernetes API, and how you can express them in .yaml format. Understanding Kubernetes objects Kubernetes objects are persistent entities in the Kubernetes system. Kubernetes uses these entities to represent the state of your cluster. Specifically, they can describe: What containerized applications are running (and on which nodes) The resources

available to those applications The policies around how those applications behave, such as restart policies, upgrades, and fault-tolerance A Kubernetes object is a "record of intent"--once you create the object, the Kubernetes system will constantly work to ensure that object exists. By creating an object, you're effectively telling the Kubernetes system what you want your cluster's workload to look like; this is your cluster's desired state . To work with Kubernetes objects—whether to create, modify, or delete them—you'll need to use the Kubernetes API . When you use the kubectl command-line interface, for example, the CLI• • • • • • • • • •

makes the necessary Kubernetes API calls for you. You can also use the Kubernetes API directly in your own programs using one of the Client Libraries . Object spec and status Almost every Kubernetes object includes two nested object fields that govern the object's configuration: the object spec and the object status . For objects that have a spec, you have to set this when you create the object, providing a description of the characteristics you want the resource to have: its desired state . The status describes the current state of the object, supplied and updated by the Kubernetes system and its components. The Kubernetes control plane continually and actively manages every object's actual state to match the desired state you supplied. For example: in Kubernetes, a Deployment is an object that can represent an application running on your cluster. When you create the Deployment, you might set the Deployment spec to specify that you want three replicas of the application to be runni

ng. The Kubernetes system reads the Deployment spec and starts three instances of your desired application--updating the status to match your spec. If any of those instances should fail (a status change), the Kubernetes system responds to the difference between spec and status by making a correction--in this case, starting a replacement instance. For more information on the object spec, status, and metadata, see the Kubernetes API Conventions . Describing a Kubernetes object When you create an object in Kubernetes, you must provide the object spec that describes its desired state, as well as some basic information about the object (such as a name). When you use the Kubernetes API to create the object (either directly or via kubectl ), that API request must include that information as JSON in the request body. Most often, you provide the information to kubectl in file known as a manifest . By convention, manifests are YAML (you could also use JSON format). Tools such as kubectl conver

t the information from a manifest into JSON or another supported serialization format when making the API request over HTTP. Here's an example manifest that shows the required fields and object spec for a Kubernetes Deployment: application/deployment.yaml apiVersion : apps/v1 kind: Deployment metadata : name : nginx-deployment spec: selector : matchLabels : app: nginx replicas : 2 # tells deployment to run 2 pods matching the template template : metadata : labels : app: ngin

spec: containers : - name : nginx image : nginx:1.14.2 ports : - containerPort : 80 One way to create a Deployment using a manifest file like the one above is to use the kubectl apply command in the kubectl command-line interface, passing the .yaml file as an argument. Here's an example: kubectl apply -f https://k8s.io/examples/application/deployment.yaml The output is similar to this: deployment.apps/nginx-deployment created Required fields In the manifest (YAML or JSON file) for the Kubernetes object you want to create, you'll need to set values for the following fields: apiVersion - Which version of the Kubernetes API you're using to create this object kind - What kind of object you want to create metadata - Data that helps uniquely identify the object, including a name string, UID, and optional namespace spec - What state you desire for the object The precise format of the object spec is different for every Kubernetes object, and contains

nested fields specific to that object. The Kubernetes API Reference can help you find the spec format for all of the objects you can create using Kubernetes. For example, see the spec field for the Pod API reference. For each Pod, the .spec field specifies the pod and its desired state (such as the container image name for each container within that pod). Another example of an object specification is the spec field for the StatefulSet API. For StatefulSet, the .spec field specifies the StatefulSet and its desired state. Within the .spec of a StatefulSet is a template for Pod objects. That template describes Pods that the StatefulSet controller will create in order to satisfy the StatefulSet specification. Different kinds of object can also have different .status ; again, the API reference pages detail the structure of that .status field, and its content for each different type of object. Note: See Configuration Best Practices for additional information on writing YAML configur

ation files. Server side field validation Starting with Kubernetes v1.25, the API server offers server side field validation that detects unrecognized or duplicate fields in an object. It provides all the functionality of kubectl -- validate on the server side. The kubectl tool uses the --validate flag to set the level of field validation. It accepts the values ignore , warn , and strict while also accepting the values true (equivalent to strict ) and false (equivalent to ignore ). The default validation setting for kubectl is --validate=true .• • •

Strict Strict field validation, errors on validation failure Warn Field validation is performed, but errors are exposed as warnings rather than failing the request Ignore No server side field validation is performed When kubectl cannot connect to an API server that supports field validation it will fall back to using client-side validation. Kubernetes 1.27 and later versions always offer field validation; older Kubernetes releases might not. If your cluster is older than v1.27, check the documentation for your version of Kubernetes. What's next If you're new to Kubernetes, read more about the following: Pods which are the most important basic Kubernetes objects. Deployment objects. Controllers in Kubernetes. kubectl and kubectl commands . Kubernetes Object Management explains how to use kubectl to manage objects. You might need to install kubectl if you don't already have it available. To learn about the Kubernetes API in general, visit: Kubernetes API overview To learn about o

bjects in Kubernetes in more depth, read other pages in this section: Kubernetes Object Management Object Names and IDs Labels and Selectors Namespaces Annotations Field Selectors Finalizers Owners and Dependents Recommended Labels Kubernetes Object Management The kubectl command-line tool supports several different ways to create and manage Kubernetes objects . This document provides an overview of the different approaches. Read the Kubectl book for details of managing objects by Kubectl. Management techniques Warning: A Kubernetes object should be managed using only one technique. Mixing and matching techniques for the same object results in undefined behavior.• • • • • • • • • • • • •

Management techniqueOperates onRecommended environmentSupported writersLearning curve Imperative commands Live objects Development projects 1+ Lowest Imperative object configurationIndividual files Production projects 1 Moderate Declarative object configurationDirectories of filesProduction projects 1+ Highest Imperative commands When using imperative commands, a user operates directly on live objects in a cluster. The user provides operations to the kubectl command as arguments or flags. This is the recommended way to get started or to run a one-off task in a cluster. Because this technique operates directly on live objects, it provides no history of previous configurations. Examples Run an instance of the nginx container by creating a Deployment object: kubectl create deployment nginx --image nginx Trade-offs Advantages compared to object configuration: Commands are expressed as a single action word. Commands require only a single step to make changes to the cluster. Disadvantages c

ompared to object configuration: Commands do not integrate with change review processes. Commands do not provide an audit trail associated with changes. Commands do not provide a source of records except for what is live. Commands do not provide a template for creating new objects. Imperative object configuration In imperative object configuration, the kubectl command specifies the operation (create, replace, etc.), optional flags and at least one file name. The file specified must contain a full definition of the object in YAML or JSON format. See the API reference for more details on object definitions. Warning: The imperative replace command replaces the existing spec with the newly provided one, dropping all changes to the object missing from the configuration file. This approach should not be used with resource types whose specs are updated independently of the configuration file. Services of type LoadBalancer , for example, have their externalIPs field updated independently f

rom the configuration by the cluster.• • • • •

Examples Create the objects defined in a configuration file: kubectl create -f nginx.yaml Delete the objects defined in two configuration files: kubectl delete -f nginx.yaml -f redis.yaml Update the objects defined in a configuration file by overwriting the live configuration: kubectl replace -f nginx.yaml Trade-offs Advantages compared to imperative commands: Object configuration can be stored in a source control system such as Git. Object configuration can integrate with processes such as reviewing changes before push and audit trails. Object configuration provides a template for creating new objects. Disadvantages compared to imperative commands: Object configuration requires basic understanding of the object schema. Object configuration requires the additional step of writing a YAML file. Advantages compared to declarative object configuration: Imperative object configuration behavior is simpler and easier to understand. As of Kubernetes version 1.5, imperative object configuration

is more mature. Disadvantages compared to declarative object configuration: Imperative object configuration works best on files, not directories. Updates to live objects must be reflected in configuration files, or they will be lost during the next replacement. Declarative object configuration When using declarative object configuration, a user operates on object configuration files stored locally, however the user does not define the operations to be taken on the files. Create, update, and delete operations are automatically detected per-object by kubectl . This enables working on directories, where different operations might be needed for different objects. Note: Declarative object configuration retains changes made by other writers, even if the changes are not merged back to the object configuration file. This is possible by using the patch API operation to write only observed differences, instead of using the replace API operation to replace the entire object configuration.• •

• • • • • •

Examples Process all object configuration files in the configs directory, and create or patch the live objects. You can first diff to see what changes are going to be made, and then apply: kubectl diff -f configs/ kubectl apply -f configs/ Recursively process directories: kubectl diff -R -f configs/ kubectl apply -R -f configs/ Trade-offs Advantages compared to imperative object configuration: Changes made directly to live objects are retained, even if they are not merged back into the configuration files. Declarative object configuration has better support for operating on directories and automatically detecting operation types (create, patch, delete) per-object. Disadvantages compared to imperative object configuration: Declarative object configuration is harder to debug and understand results when they are unexpected. Partial updates using diffs create complex merge and patch operations. What's next Managing Kubernetes Objects Using Imperative Commands Imperative Management of Kube

rnetes Objects Using Configuration Files Declarative Management of Kubernetes Objects Using Configuration Files Declarative Management of Kubernetes Objects Using Kustomize Kubectl Command Reference Kubectl Book Kubernetes API Reference Object Names and IDs Each object in your cluster has a Name that is unique for that type of resource. Every Kubernetes object also has a UID that is unique across your whole cluster. For example, you can only have one Pod named myapp-1234 within the same namespace , but you can have one Pod and one Deployment that are each named myapp-1234 . For non-unique user-provided attributes, Kubernetes provides labels and annotations .• • • • • • • • • •

Names A client-provided string that refers to an object in a resource URL, such as /api/v1/pods/some- name . Only one object of a given kind can have a given name at a time. However, if you delete the object, you can make a new object with the same name. Names must be unique across all API versions of the same resource. API resources are distinguished by their API group, resource type, namespace (for namespaced resources), and name. In other words, API version is irrelevant in this context. Note: In cases when objects represent a physical entity, like a Node representing a physical host, when the host is re-created under the same name without deleting and re-creating the Node, Kubernetes treats the new host as the old one, which may lead to inconsistencies. Below are four types of commonly used name constraints for resources. DNS Subdomain Names Most resource types require a name that can be used as a DNS subdomain name as defined in RFC 1123 . This means the name must: contain no m

ore than 253 characters contain only lowercase alphanumeric characters, '-' or '.' start with an alphanumeric character end with an alphanumeric character RFC 1123 Label Names Some resource types require their names to follow the DNS label standard as defined in RFC 1123. This means the name must: contain at most 63 characters contain only lowercase alphanumeric characters or '-' start with an alphanumeric character end with an alphanumeric character RFC 1035 Label Names Some resource types require their names to follow the DNS label standard as defined in RFC 1035. This means the name must: contain at most 63 characters contain only lowercase alphanumeric characters or '-' start with an alphabetic character end with an alphanumeric character Note: The only difference between the RFC 1035 and RFC 1123 label standards is that RFC 1123 labels are allowed to start with a digit, whereas RFC 1035 labels can start with a lowercase alphabetic character only.• • • • • • • • • • •

Path Segment Names Some resource types require their names to be able to be safely encoded as a path segment. In other words, the name may not be "." or ".." and the name may not contain "/" or "%". Here's an example manifest for a Pod named nginx-demo . apiVersion : v1 kind: Pod metadata : name : nginx-demo spec: containers : - name : nginx image : nginx:1.14.2 ports : - containerPort : 80 Note: Some resource types have additional restrictions on their names. UIDs A Kubernetes systems-generated string to uniquely identify objects. Every object created over the whole lifetime of a Kubernetes cluster has a distinct UID. It is intended to distinguish between historical occurrences of similar entities. Kubernetes UIDs are universally unique identifiers (also known as UUIDs). UUIDs are standardized as ISO/IEC 9834-8 and as ITU-T X.667. What's next Read about labels and annotations in Kubernetes. See the Identifiers and Names in Kubernetes design document. Labels and S

electors Labels are key/value pairs that are attached to objects such as Pods. Labels are intended to be used to specify identifying attributes of objects that are meaningful and relevant to users, but do not directly imply semantics to the core system. Labels can be used to organize and to select subsets of objects. Labels can be attached to objects at creation time and subsequently added and modified at any time. Each object can have a set of key/value labels defined. Each Key must be unique for a given object. "metadata" : { "labels" : { "key1" : "value1" , "key2" : "value2" } }•

Labels allow for efficient queries and watches and are ideal for use in UIs and CLIs. Non- identifying information should be recorded using annotations . Motivation Labels enable users to map their own organizational structures onto system objects in a loosely coupled fashion, without requiring clients to store these mappings. Service deployments and batch processing pipelines are often multi-dimensional entities (e.g., multiple partitions or deployments, multiple release tracks, multiple tiers, multiple micro- services per tier). Management often requires cross-cutting operations, which breaks encapsulation of strictly hierarchical representations, especially rigid hierarchies determined by the infrastructure rather than by users. Example labels: "release" : "stable" , "release" : "canary" "environment" : "dev" , "environment" : "qa" , "environment" : "production" "tier" : "frontend" , "tier" : "backend" , "tier" : "cache" "partition" : "customerA" , "partition" : "customerB" "track"

: "daily" , "track" : "weekly" These are examples of commonly used labels ; you are free to develop your own conventions. Keep in mind that label Key must be unique for a given object. Syntax and character set Labels are key/value pairs. Valid label keys have two segments: an optional prefix and name, separated by a slash ( /). The name segment is required and must be 63 characters or less, beginning and ending with an alphanumeric character ( [a-z0-9A-Z] ) with dashes ( -), underscores ( _), dots ( .), and alphanumerics between. The prefix is optional. If specified, the prefix must be a DNS subdomain: a series of DNS labels separated by dots ( .), not longer than 253 characters in total, followed by a slash ( /). If the prefix is omitted, the label Key is presumed to be private to the user. Automated system components (e.g. kube-scheduler , kube-controller-manager , kube-apiserver , kubectl , or other third-party automation) which add labels to end-user objects must specify a prefix.

The kubernetes.io/ and k8s.io/ prefixes are reserved for Kubernetes core components. Valid label value: must be 63 characters or less (can be empty), unless empty, must begin and end with an alphanumeric character ( [a-z0-9A-Z] ), could contain dashes ( -), underscores ( _), dots ( .), and alphanumerics between. For example, here's a manifest for a Pod that has two labels environment: production and app: nginx : apiVersion : v1 kind: Pod metadata : name : label-demo• • • • • • •

labels : environment : production app: nginx spec: containers : - name : nginx image : nginx:1.14.2 ports : - containerPort : 80 Label selectors Unlike names and UIDs , labels do not provide uniqueness. In general, we expect many objects to carry the same label(s). Via a label selector , the client/user can identify a set of objects. The label selector is the core grouping primitive in Kubernetes. The API currently supports two types of selectors: equality-based and set-based . A label selector can be made of multiple requirements which are comma-separated. In the case of multiple requirements, all must be satisfied so the comma separator acts as a logical AND (&&) operator. The semantics of empty or non-specified selectors are dependent on the context, and API types that use selectors should document the validity and meaning of them. Note: For some API types, such as ReplicaSets, the label selectors of two instances must not overlap within a namespace, or t

he controller can see that as conflicting instructions and fail to determine how many replicas should be present. Caution: For both equality-based and set-based conditions there is no logical OR (||) operator. Ensure your filter statements are structured accordingly. Equality-based requirement Equality- or inequality-based requirements allow filtering by label keys and values. Matching objects must satisfy all of the specified label constraints, though they may have additional labels as well. Three kinds of operators are admitted =,==,!=. The first two represent equality (and are synonyms), while the latter represents inequality . For example: environment = production tier != frontend The former selects all resources with key equal to environment and value equal to production . The latter selects all resources with key equal to tier and value distinct from frontend , and all resources with no labels with the tier key. One could filter for resources in production excluding fronten

d using the comma operator: environment=production,tier!=frontend One usage scenario for equality-based label requirement is for Pods to specify node selection criteria. For example, the sample Pod below selects nodes with the label " accelerator=nvidia- tesla-p100 ". apiVersion : v1 kind: Pod metadata

name : cuda-test spec: containers : - name : cuda-test image : "registry.k8s.io/cuda-vector-add:v0.1" resources : limits : nvidia.com/gpu : 1 nodeSelector : accelerator : nvidia-tesla-p100 Set-based requirement Set-based label requirements allow filtering keys according to a set of values. Three kinds of operators are supported: in,notin and exists (only the key identifier). For example: environment in (production, qa) tier notin (frontend, backend) partition !partition The first example selects all resources with key equal to environment and value equal to production or qa. The second example selects all resources with key equal to tier and values other than frontend and backend , and all resources with no labels with the tier key. The third example selects all resources including a label with key partition ; no values are checked. The fourth example selects all resources without a label with key partition ; no values are checked. Sim

ilarly the comma separator acts as an AND operator. So filtering resources with a partition key (no matter the value) and with environment different than qa can be achieved using partition,environment notin (qa) . The set-based label selector is a general form of equality since environment=production is equivalent to environment in (production) ; similarly for != and notin . Set-based requirements can be mixed with equality-based requirements. For example: partition in (customerA, customerB),environment!=qa . API LIST and WATCH filtering LIST and WATCH operations may specify label selectors to filter the sets of objects returned using a query parameter. Both requirements are permitted (presented here as they would appear in a URL query string): equality-based requirements: ?labelSelector=environment%3Dproduction,tier%3Dfrontend set-based requirements: ?labelSelector=environment+in+ %28production%2Cqa%29%2Ctier+in+%28frontend%29• • • • •

Both label selector styles can be used to list or watch resources via a REST client. For example, targeting apiserver with kubectl and using equality-based one may write: kubectl get pods -l environment =production,tier =frontend or using set-based requirements: kubectl get pods -l 'environment in (production),tier in (frontend)' As already mentioned set-based requirements are more expressive. For instance, they can implement the OR operator on values: kubectl get pods -l 'environment in (production, qa)' or restricting negative matching via notin operator: kubectl get pods -l 'environment,environment notin (frontend)' Set references in API objects Some Kubernetes objects, such as services and replicationcontrollers , also use label selectors to specify sets of other resources, such as pods . Service and ReplicationController The set of pods that a service targets is defined with a label selector. Similarly, the population of pods that a replicationcontroller should manage is

also defined with a label selector. Label selectors for both objects are defined in json or yaml files using maps, and only equality- based requirement selectors are supported: "selector" : { "component" : "redis" , } or selector : component : redis This selector (respectively in json or yaml format) is equivalent to component=redis or component in (redis) . Resources that support set-based requirements Newer resources, such as Job, Deployment , ReplicaSet , and DaemonSet , support set-based requirements as well. selector : matchLabels : component : redis matchExpressions : - { key: tier, operator: In, values : [cache] } - { key: environment, operator: NotIn, values : [dev]

matchLabels is a map of {key,value} pairs. A single {key,value} in the matchLabels map is equivalent to an element of matchExpressions , whose key field is "key", the operator is "In", and the values array contains only "value". matchExpressions is a list of pod selector requirements. Valid operators include In, NotIn, Exists, and DoesNotExist. The values set must be non-empty in the case of In and NotIn. All of the requirements, from both matchLabels and matchExpressions are ANDed together -- they must all be satisfied in order to match. Selecting sets of nodes One use case for selecting over labels is to constrain the set of nodes onto which a pod can schedule. See the documentation on node selection for more information. Using labels effectively You can apply a single label to any resources, but this is not always the best practice. There are many scenarios where multiple labels should be used to distinguish resource sets from one another. For instance, different applicat

ions would use different values for the app label, but a multi-tier application, such as the guestbook example , would additionally need to distinguish each tier. The frontend could carry the following labels: labels : app: guestbook tier: frontend while the Redis master and replica would have different tier labels, and perhaps even an additional role label: labels : app: guestbook tier: backend role: master and labels : app: guestbook tier: backend role: replica The labels allow for slicing and dicing the resources along any dimension specified by a label: kubectl apply -f examples/guestbook/all-in-one/guestbook-all-in-one.yaml kubectl get pods -Lapp -Ltier -Lrole NAME READY STATUS RESTARTS AGE APP TIER ROLE guestbook-fe-4nlpb 1/1 Running 0 1m guestbook frontend <none> guestbook-fe-ght6d 1/1 Running 0 1m guestbook frontend <none> guestbook-fe-jpy62

1/1 Running 0 1m guestbook frontend <none> guestbook-redis-master-5pg3b 1/1 Running 0 1m guestbook backend master guestbook-redis-replica-2q2yf 1/1 Running 0 1m guestbook backend replica guestbook-redis-replica-qgazl 1/1 Running 0 1m guestbook backend replic

my-nginx-divi2 1/1 Running 0 29m nginx <none> <none> my-nginx-o0ef1 1/1 Running 0 29m nginx <none> <none> kubectl get pods -lapp =guestbook,role =replica NAME READY STATUS RESTARTS AGE guestbook-redis-replica-2q2yf 1/1 Running 0 3m guestbook-redis-replica-qgazl 1/1 Running 0 3m Updating labels Sometimes you may want to relabel existing pods and other resources before creating new resources. This can be done with kubectl label . For example, if you want to label all your NGINX Pods as frontend tier, run: kubectl label pods -l app=nginx tier=fe pod/my-nginx-2035384211-j5fhi labeled pod/my-nginx-2035384211-u2c7e labeled pod/my-nginx-2035384211-u3t6x labeled This first filters all pods with the label "app=nginx", and then labels them with the "tier=fe". To see the pods you labeled, run: kubectl get pods -l app=nginx -L tier NAME

READY STATUS RESTARTS AGE TIER my-nginx-2035384211-j5fhi 1/1 Running 0 23m fe my-nginx-2035384211-u2c7e 1/1 Running 0 23m fe my-nginx-2035384211-u3t6x 1/1 Running 0 23m fe This outputs all "app=nginx" pods, with an additional label column of pods' tier (specified with - L or --label-columns ). For more information, please see kubectl label . What's next Learn how to add a label to a node Find Well-known labels, Annotations and Taints See Recommended labels Enforce Pod Security Standards with Namespace Labels Read a blog on Writing a Controller for Pod Labels Namespaces In Kubernetes, namespaces provides a mechanism for isolating groups of resources within a single cluster. Names of resources need to be unique within a namespace, but not across namespaces. Namespace-based scoping is applicable only for namespaced objects (e.g. Deployments, Services, etc) and not for cluster-wide objects (e.g. St

orageClass, Nodes, PersistentVolumes, etc) .• • • •

When to Use Multiple Namespaces Namespaces are intended for use in environments with many users spread across multiple teams, or projects. For clusters with a few to tens of users, you should not need to create or think about namespaces at all. Start using namespaces when you need the features they provide. Namespaces provide a scope for names. Names of resources need to be unique within a namespace, but not across namespaces. Namespaces cannot be nested inside one another and each Kubernetes resource can only be in one namespace. Namespaces are a way to divide cluster resources between multiple users (via resource quota ). It is not necessary to use multiple namespaces to separate slightly different resources, such as different versions of the same software: use labels to distinguish resources within the same namespace. Note: For a production cluster, consider not using the default namespace. Instead, make other namespaces and use those. Initial namespaces Kubernetes starts with fo

ur initial namespaces: default Kubernetes includes this namespace so that you can start using your new cluster without first creating a namespace. kube-node-lease This namespace holds Lease objects associated with each node. Node leases allow the kubelet to send heartbeats so that the control plane can detect node failure. kube-public This namespace is readable by all clients (including those not authenticated). This namespace is mostly reserved for cluster usage, in case that some resources should be visible and readable publicly throughout the whole cluster. The public aspect of this namespace is only a convention, not a requirement. kube-system The namespace for objects created by the Kubernetes system. Working with Namespaces Creation and deletion of namespaces are described in the Admin Guide documentation for namespaces . Note: Avoid creating namespaces with the prefix kube- , since it is reserved for Kubernetes system namespaces. Viewing namespaces You can list the current na

mespaces in a cluster using: kubectl get namespac

NAME STATUS AGE default Active 1d kube-node-lease Active 1d kube-public Active 1d kube-system Active 1d Setting the namespace for a request To set the namespace for a current request, use the --namespace flag. For example: kubectl run nginx --image =nginx --namespace =<insert-namespace-name-here> kubectl get pods --namespace =<insert-namespace-name-here> Setting the namespace preference You can permanently save the namespace for all subsequent kubectl commands in that context. kubectl config set-context --current --namespace =<insert-namespace-name-here> # Validate it kubectl config view --minify | grep namespace: Namespaces and DNS When you create a Service , it creates a corresponding DNS entry . This entry is of the form <service-name>.<namespace-name>.svc.cluster.local , which means that if a container only uses <service-name> , it will resolve to the service which is local to a namespace. This is useful for using the same configura

tion across multiple namespaces such as Development, Staging and Production. If you want to reach across namespaces, you need to use the fully qualified domain name (FQDN). As a result, all namespace names must be valid RFC 1123 DNS labels . Warning: By creating namespaces with the same name as public top-level domains , Services in these namespaces can have short DNS names that overlap with public DNS records. Workloads from any namespace performing a DNS lookup without a trailing dot will be redirected to those services, taking precedence over public DNS. To mitigate this, limit privileges for creating namespaces to trusted users. If required, you could additionally configure third-party security controls, such as admission webhooks , to block creating any namespace with the name of public TLDs . Not all objects are in a namespace Most Kubernetes resources (e.g. pods, services, replication controllers, and others) are in some namespaces. However namespace resources are not themselve

s in a namespace. And low-level resources, such as nodes and persistentVolumes , are not in any namespace. To see which Kubernetes resources are and aren't in a namespace

# In a namespace kubectl api-resources --namespaced =true # Not in a namespace kubectl api-resources --namespaced =false Automatic labelling FEATURE STATE: Kubernetes 1.22 [stable] The Kubernetes control plane sets an immutable label kubernetes.io/metadata.name on all namespaces. The value of the label is the namespace name. What's next Learn more about creating a new namespace . Learn more about deleting a namespace . Annotations You can use Kubernetes annotations to attach arbitrary non-identifying metadata to objects . Clients such as tools and libraries can retrieve this metadata. Attaching metadata to objects You can use either labels or annotations to attach metadata to Kubernetes objects. Labels can be used to select objects and to find collections of objects that satisfy certain conditions. In contrast, annotations are not used to identify and select objects. The metadata in an annotation can be small or large, structured or unstructured, and can include characters not permi

tted by labels. It is possible to use labels as well as annotations in the metadata of the same object. Annotations, like labels, are key/value maps: "metadata" : { "annotations" : { "key1" : "value1" , "key2" : "value2" } } Note: The keys and the values in the map must be strings. In other words, you cannot use numeric, boolean, list or other types for either the keys or the values. Here are some examples of information that could be recorded in annotations: Fields managed by a declarative configuration layer. Attaching these fields as annotations distinguishes them from default values set by clients or servers, and from auto-generated fields and fields set by auto-sizing or auto-scaling systems.• •

Build, release, or image information like timestamps, release IDs, git branch, PR numbers, image hashes, and registry address. Pointers to logging, monitoring, analytics, or audit repositories. Client library or tool information that can be used for debugging purposes: for example, name, version, and build information. User or tool/system provenance information, such as URLs of related objects from other ecosystem components. Lightweight rollout tool metadata: for example, config or checkpoints. Phone or pager numbers of persons responsible, or directory entries that specify where that information can be found, such as a team web site. Directives from the end-user to the implementations to modify behavior or engage non- standard features. Instead of using annotations, you could store this type of information in an external database or directory, but that would make it much harder to produce shared client libraries and tools for deployment, management, introspection, and the like. Synta

x and character set Annotations are key/value pairs. Valid annotation keys have two segments: an optional prefix and name, separated by a slash ( /). The name segment is required and must be 63 characters or less, beginning and ending with an alphanumeric character ( [a-z0-9A-Z] ) with dashes ( -), underscores ( _), dots ( .), and alphanumerics between. The prefix is optional. If specified, the prefix must be a DNS subdomain: a series of DNS labels separated by dots ( .), not longer than 253 characters in total, followed by a slash ( /). If the prefix is omitted, the annotation Key is presumed to be private to the user. Automated system components (e.g. kube-scheduler , kube-controller-manager , kube-apiserver , kubectl , or other third-party automation) which add annotations to end-user objects must specify a prefix. The kubernetes.io/ and k8s.io/ prefixes are reserved for Kubernetes core components. For example, here's a manifest for a Pod that has the annotation imageregistry: ht

tps:// hub.docker.com/ : apiVersion : v1 kind: Pod metadata : name : annotations-demo annotations : imageregistry : "https://hub.docker.com/" spec: containers : - name : nginx image : nginx:1.14.2 ports : - containerPort : 80• • • • • •

What's next Learn more about Labels and Selectors . Find Well-known labels, Annotations and Taints Field Selectors Field selectors let you select Kubernetes objects based on the value of one or more resource fields. Here are some examples of field selector queries: metadata.name=my-service metadata.namespace!=default status.phase=Pending This kubectl command selects all Pods for which the value of the status.phase field is Running : kubectl get pods --field-selector status.phase =Running Note: Field selectors are essentially resource filters . By default, no selectors/filters are applied, meaning that all resources of the specified type are selected. This makes the kubectl queries kubectl get pods and kubectl get pods --field-selector "" equivalent. Supported fields Supported field selectors vary by Kubernetes resource type. All resource types support the metadata.name and metadata.namespace fields. Using unsupported field selectors produces an error. For example: kubectl g

et ingress --field-selector foo.bar =baz Error from server (BadRequest): Unable to find "ingresses" that match label selector "", field selector "foo.bar=baz": "foo.bar" is not a known field selector: only "metadata.name", "metadata.namespace" Supported operators You can use the =, ==, and != operators with field selectors ( = and == mean the same thing). This kubectl command, for example, selects all Kubernetes Services that aren't in the default namespace: kubectl get services --all-namespaces --field-selector metadata.namespace! =default Note: Set-based operators (in, notin , exists ) are not supported for field selectors. Chained selectors As with label and other selectors, field selectors can be chained together as a comma-separated list. This kubectl command selects all Pods for which the status.phase does not equal Running and the spec.restartPolicy field equals Always :• • • •

kubectl get pods --field-selector =status.phase! =Running,spec.restartPolicy =Always Multiple resource types You can use field selectors across multiple resource types. This kubectl command selects all Statefulsets and Services that are not in the default namespace: kubectl get statefulsets,services --all-namespaces --field-selector metadata.namespace! =default Finalizers Finalizers are namespaced keys that tell Kubernetes to wait until specific conditions are met before it fully deletes resources marked for deletion. Finalizers alert controllers to clean up resources the deleted object owned. When you tell Kubernetes to delete an object that has finalizers specified for it, the Kubernetes API marks the object for deletion by populating .metadata.deletionTimestamp , and returns a 202 status code (HTTP "Accepted"). The target object remains in a terminating state while the control plane, or other components, take the actions defined by the finalizers. After these actions are complet

e, the controller removes the relevant finalizers from the target object. When the metadata.finalizers field is empty, Kubernetes considers the deletion complete and deletes the object. You can use finalizers to control garbage collection of resources. For example, you can define a finalizer to clean up related resources or infrastructure before the controller deletes the target resource. You can use finalizers to control garbage collection of objects by alerting controllers to perform specific cleanup tasks before deleting the target resource. Finalizers don't usually specify the code to execute. Instead, they are typically lists of keys on a specific resource similar to annotations. Kubernetes specifies some finalizers automatically, but you can also specify your own. How finalizers work When you create a resource using a manifest file, you can specify finalizers in the metadata.finalizers field. When you attempt to delete the resource, the API server handling the delete reque

st notices the values in the finalizers field and does the following: Modifies the object to add a metadata.deletionTimestamp field with the time you started the deletion. Prevents the object from being removed until all items are removed from its metadata.finalizers field Returns a 202 status code (HTTP "Accepted") The controller managing that finalizer notices the update to the object setting the metadata.deletionTimestamp , indicating deletion of the object has been requested. The controller then attempts to satisfy the requirements of the finalizers specified for that resource. Each time a finalizer condition is satisfied, the controller removes that key from the resource's finalizers field. When the finalizers field is emptied, an object with a deletionTimestamp field• •

set is automatically deleted. You can also use finalizers to prevent deletion of unmanaged resources. A common example of a finalizer is kubernetes.io/pv-protection , which prevents accidental deletion of PersistentVolume objects. When a PersistentVolume object is in use by a Pod, Kubernetes adds the pv-protection finalizer. If you try to delete the PersistentVolume , it enters a Terminating status, but the controller can't delete it because the finalizer exists. When the Pod stops using the PersistentVolume , Kubernetes clears the pv-protection finalizer, and the controller deletes the volume. Note: When you DELETE an object, Kubernetes adds the deletion timestamp for that object and then immediately starts to restrict changes to the .metadata.finalizers field for the object that is now pending deletion. You can remove existing finalizers (deleting an entry from the finalizers list) but you cannot add a new finalizer. You also cannot modify the deletionTimestamp for an objec

t once it is set. After the deletion is requested, you can not resurrect this object. The only way is to delete it and make a new similar object. Owner references, labels, and finalizers Like labels , owner references describe the relationships between objects in Kubernetes, but are used for a different purpose. When a controller manages objects like Pods, it uses labels to track changes to groups of related objects. For example, when a Job creates one or more Pods, the Job controller applies labels to those pods and tracks changes to any Pods in the cluster with the same label. The Job controller also adds owner references to those Pods, pointing at the Job that created the Pods. If you delete the Job while these Pods are running, Kubernetes uses the owner references (not labels) to determine which Pods in the cluster need cleanup. Kubernetes also processes finalizers when it identifies owner references on a resource targeted for deletion. In some situations, finalizers can block t

he deletion of dependent objects, which can cause the targeted owner object to remain for longer than expected without being fully deleted. In these situations, you should check finalizers and owner references on the target owner and dependent objects to troubleshoot the cause. Note: In cases where objects are stuck in a deleting state, avoid manually removing finalizers to allow deletion to continue. Finalizers are usually added to resources for a reason, so forcefully removing them can lead to issues in your cluster. This should only be done when the purpose of the finalizer is understood and is accomplished in another way (for example, manually cleaning up some dependent object). What's next Read Using Finalizers to Control Deletion on the Kubernetes blog.• •

Owners and Dependents In Kubernetes, some objects are owners of other objects. For example, a ReplicaSet is the owner of a set of Pods. These owned objects are dependents of their owner. Ownership is different from the labels and selectors mechanism that some resources also use. For example, consider a Service that creates EndpointSlice objects. The Service uses labels to allow the control plane to determine which EndpointSlice objects are used for that Service. In addition to the labels, each EndpointSlice that is managed on behalf of a Service has an owner reference. Owner references help different parts of Kubernetes avoid interfering with objects they don’t control. Owner references in object specifications Dependent objects have a metadata.ownerReferences field that references their owner object. A valid owner reference consists of the object name and a UID within the same namespace as the dependent object. Kubernetes sets the value of this field automatically for objec

ts that are dependents of other objects like ReplicaSets, DaemonSets, Deployments, Jobs and CronJobs, and ReplicationControllers. You can also configure these relationships manually by changing the value of this field. However, you usually don't need to and can allow Kubernetes to automatically manage the relationships. Dependent objects also have an ownerReferences.blockOwnerDeletion field that takes a boolean value and controls whether specific dependents can block garbage collection from deleting their owner object. Kubernetes automatically sets this field to true if a controller (for example, the Deployment controller) sets the value of the metadata.ownerReferences field. You can also set the value of the blockOwnerDeletion field manually to control which dependents block garbage collection. A Kubernetes admission controller controls user access to change this field for dependent resources, based on the delete permissions of the owner. This control prevents unauthorized users f

rom delaying owner object deletion. Note: Cross-namespace owner references are disallowed by design. Namespaced dependents can specify cluster-scoped or namespaced owners. A namespaced owner must exist in the same namespace as the dependent. If it does not, the owner reference is treated as absent, and the dependent is subject to deletion once all owners are verified absent. Cluster-scoped dependents can only specify cluster-scoped owners. In v1.20+, if a cluster- scoped dependent specifies a namespaced kind as an owner, it is treated as having an unresolvable owner reference, and is not able to be garbage collected. In v1.20+, if the garbage collector detects an invalid cross-namespace ownerReference , or a cluster-scoped dependent with an ownerReference referencing a namespaced kind, a warning Event with a reason of OwnerRefInvalidNamespace and an involvedObject of the invalid dependent is reported. You can check for that kind of Event by running kubectl get events -A -- field-se

lector=reason=OwnerRefInvalidNamespace

Ownership and finalizers When you tell Kubernetes to delete a resource, the API server allows the managing controller to process any finalizer rules for the resource. Finalizers prevent accidental deletion of resources your cluster may still need to function correctly. For example, if you try to delete a PersistentVolume that is still in use by a Pod, the deletion does not happen immediately because the PersistentVolume has the kubernetes.io/pv-protection finalizer on it. Instead, the volume remains in the Terminating status until Kubernetes clears the finalizer, which only happens after the PersistentVolume is no longer bound to a Pod. Kubernetes also adds finalizers to an owner resource when you use either foreground or orphan cascading deletion . In foreground deletion, it adds the foreground finalizer so that the controller must delete dependent resources that also have ownerReferences.blockOwnerDeletion=true before it deletes the owner. If you specify an orphan deletion p

olicy, Kubernetes adds the orphan finalizer so that the controller ignores dependent resources after it deletes the owner object. What's next Learn more about Kubernetes finalizers . Learn about garbage collection . Read the API reference for object metadata . Recommended Labels You can visualize and manage Kubernetes objects with more tools than kubectl and the dashboard. A common set of labels allows tools to work interoperably, describing objects in a common manner that all tools can understand. In addition to supporting tooling, the recommended labels describe applications in a way that can be queried. The metadata is organized around the concept of an application . Kubernetes is not a platform as a service (PaaS) and doesn't have or enforce a formal notion of an application. Instead, applications are informal and described with metadata. The definition of what an application contains is loose. Note: These are recommended labels. They make it easier to manage applications but ar

en't required for any core tooling. Shared labels and annotations share a common prefix: app.kubernetes.io . Labels without a prefix are private to users. The shared prefix ensures that shared labels do not interfere with custom user labels. Labels In order to take full advantage of using these labels, they should be applied on every resource object.• •

Key Description Example Type app.kubernetes.io/name The name of the application mysql string app.kubernetes.io/ instanceA unique name identifying the instance of an applicationmysql- abcxzystring app.kubernetes.io/ versionThe current version of the application (e.g., a SemVer 1.0 , revision hash, etc.)5.7.21 string app.kubernetes.io/ componentThe component within the architecture database string app.kubernetes.io/part-ofThe name of a higher level application this one is part ofwordpress string app.kubernetes.io/ managed-byThe tool being used to manage the operation of an applicationhelm string To illustrate these labels in action, consider the following StatefulSet object: # This is an excerpt apiVersion : apps/v1 kind: StatefulSet metadata : labels : app.kubernetes.io/name : mysql app.kubernetes.io/instance : mysql-abcxzy app.kubernetes.io/version : "5.7.21" app.kubernetes.io/component : database app.kubernetes.io/part-of : wordpress app.kubernetes.io/manag

ed-by : helm Applications And Instances Of Applications An application can be installed one or more times into a Kubernetes cluster and, in some cases, the same namespace. For example, WordPress can be installed more than once where different websites are different installations of WordPress. The name of an application and the instance name are recorded separately. For example, WordPress has a app.kubernetes.io/name of wordpress while it has an instance name, represented as app.kubernetes.io/instance with a value of wordpress-abcxzy . This enables the application and instance of the application to be identifiable. Every instance of an application must have a unique name. Examples To illustrate different ways to use these labels the following examples have varying complexity. A Simple Stateless Service Consider the case for a simple stateless service deployed using Deployment and Service objects. The following two snippets represent how the labels could be used in their simplest fo

rm. The Deployment is used to oversee the pods running the application itself

apiVersion : apps/v1 kind: Deployment metadata : labels : app.kubernetes.io/name : myservice app.kubernetes.io/instance : myservice-abcxzy ... The Service is used to expose the application. apiVersion : v1 kind: Service metadata : labels : app.kubernetes.io/name : myservice app.kubernetes.io/instance : myservice-abcxzy ... Web Application With A Database Consider a slightly more complicated application: a web application (WordPress) using a database (MySQL), installed using Helm. The following snippets illustrate the start of objects used to deploy this application. The start to the following Deployment is used for WordPress: apiVersion : apps/v1 kind: Deployment metadata : labels : app.kubernetes.io/name : wordpress app.kubernetes.io/instance : wordpress-abcxzy app.kubernetes.io/version : "4.9.4" app.kubernetes.io/managed-by : helm app.kubernetes.io/component : server app.kubernetes.io/part-of : wordpress ... The Service is used to expo

se WordPress: apiVersion : v1 kind: Service metadata : labels : app.kubernetes.io/name : wordpress app.kubernetes.io/instance : wordpress-abcxzy app.kubernetes.io/version : "4.9.4" app.kubernetes.io/managed-by : helm app.kubernetes.io/component : server app.kubernetes.io/part-of : wordpress ..

MySQL is exposed as a StatefulSet with metadata for both it and the larger application it belongs to: apiVersion : apps/v1 kind: StatefulSet metadata : labels : app.kubernetes.io/name : mysql app.kubernetes.io/instance : mysql-abcxzy app.kubernetes.io/version : "5.7.21" app.kubernetes.io/managed-by : helm app.kubernetes.io/component : database app.kubernetes.io/part-of : wordpress ... The Service is used to expose MySQL as part of WordPress: apiVersion : v1 kind: Service metadata : labels : app.kubernetes.io/name : mysql app.kubernetes.io/instance : mysql-abcxzy app.kubernetes.io/version : "5.7.21" app.kubernetes.io/managed-by : helm app.kubernetes.io/component : database app.kubernetes.io/part-of : wordpress ... With the MySQL StatefulSet and Service you'll notice information about both MySQL and WordPress, the broader application, are included. Kubernetes Components A Kubernetes cluster consists of the components that are a part

of the control plane and a set of machines called nodes. When you deploy Kubernetes, you get a cluster. A Kubernetes cluster consists of a set of worker machines, called nodes , that run containerized applications. Every cluster has at least one worker node. The worker node(s) host the Pods that are the components of the application workload. The control plane manages the worker nodes and the Pods in the cluster. In production environments, the control plane usually runs across multiple computers and a cluster usually runs multiple nodes, providing fault-tolerance and high availability. This document outlines the various components you need to have for a complete and working Kubernetes cluster. Components of Kubernetes The components of a Kubernetes cluste

Control Plane Components The control plane's components make global decisions about the cluster (for example, scheduling), as well as detecting and responding to cluster events (for example, starting up a new pod when a Deployment's replicas field is unsatisfied). Control plane components can be run on any machine in the cluster. However, for simplicity, setup scripts typically start all control plane components on the same machine, and do not run user containers on this machine. See Creating Highly Available clusters with kubeadm for an example control plane setup that runs across multiple machines. kube-apiserver The API server is a component of the Kubernetes control plane that exposes the Kubernetes API. The API server is the front end for the Kubernetes control plane. The main implementation of a Kubernetes API server is kube-apiserver . kube-apiserver is designed to scale horizontally—that is, it scales by deploying more instances. You can run several instances of kube-apiserv

er and balance traffic between those instances. etcd Consistent and highly-available key value store used as Kubernetes' backing store for all cluster data. If your Kubernetes cluster uses etcd as its backing store, make sure you have a back up plan for the data. You can find in-depth information about etcd in the official documentation . kube-scheduler Control plane component that watches for newly created Pods with no assigned node , and selects a node for them to run on. Factors taken into account for scheduling decisions include: individual and collective resource requirements, hardware/software/policy constraints, affinity and anti-affinity specifications, data locality, inter-workload interference, and deadlines. kube-controller-manager Control plane component that runs controller processes. Logically, each controller is a separate process, but to reduce complexity, they are all compiled into a single binary and run in a single process. There are many different types of contr

ollers. Some examples of them are: Node controller: Responsible for noticing and responding when nodes go down. Job controller: Watches for Job objects that represent one-off tasks, then creates Pods to run those tasks to completion.•

EndpointSlice controller: Populates EndpointSlice objects (to provide a link between Services and Pods). ServiceAccount controller: Create default ServiceAccounts for new namespaces. The above is not an exhaustive list. cloud-controller-manager A Kubernetes control plane component that embeds cloud-specific control logic. The cloud controller manager lets you link your cluster into your cloud provider's API, and separates out the components that interact with that cloud platform from components that only interact with your cluster. The cloud-controller-manager only runs controllers that are specific to your cloud provider. If you are running Kubernetes on your own premises, or in a learning environment inside your own PC, the cluster does not have a cloud controller manager. As with the kube-controller-manager, the cloud-controller-manager combines several logically independent control loops into a single binary that you run as a single process. You can scale horizontally (run more t

han one copy) to improve performance or to help tolerate failures. The following controllers can have cloud provider dependencies: Node controller: For checking the cloud provider to determine if a node has been deleted in the cloud after it stops responding Route controller: For setting up routes in the underlying cloud infrastructure Service controller: For creating, updating and deleting cloud provider load balancers Node Components Node components run on every node, maintaining running pods and providing the Kubernetes runtime environment. kubelet An agent that runs on each node in the cluster. It makes sure that containers are running in a Pod. The kubelet takes a set of PodSpecs that are provided through various mechanisms and ensures that the containers described in those PodSpecs are running and healthy. The kubelet doesn't manage containers which were not created by Kubernetes. kube-proxy kube-proxy is a network proxy that runs on each node in your cluster, implementing p

art of the Kubernetes Service concept. kube-proxy maintains network rules on nodes. These network rules allow network communication to your Pods from network sessions inside or outside of your cluster. kube-proxy uses the operating system packet filtering layer if there is one and it's available. Otherwise, kube-proxy forwards the traffic itself.• • • •

Container runtime A fundamental component that empowers Kubernetes to run containers effectively. It is responsible for managing the execution and lifecycle of containers within the Kubernetes environment. Kubernetes supports container runtimes such as containerd , CRI-O , and any other implementation of the Kubernetes CRI (Container Runtime Interface) . Addons Addons use Kubernetes resources ( DaemonSet , Deployment , etc) to implement cluster features. Because these are providing cluster-level features, namespaced resources for addons belong within the kube-system namespace. Selected addons are described below; for an extended list of available addons, please see Addons . DNS While the other addons are not strictly required, all Kubernetes clusters should have cluster DNS , as many examples rely on it. Cluster DNS is a DNS server, in addition to the other DNS server(s) in your environment, which serves DNS records for Kubernetes services. Containers started by Kubernetes automatica

lly include this DNS server in their DNS searches. Web UI (Dashboard) Dashboard is a general purpose, web-based UI for Kubernetes clusters. It allows users to manage and troubleshoot applications running in the cluster, as well as the cluster itself. Container Resource Monitoring Container Resource Monitoring records generic time-series metrics about containers in a central database, and provides a UI for browsing that data. Cluster-level Logging A cluster-level logging mechanism is responsible for saving container logs to a central log store with search/browsing interface. Network Plugins Network plugins are software components that implement the container network interface (CNI) specification. They are responsible for allocating IP addresses to pods and enabling them to communicate with each other within the cluster

What's next Learn more about the following: Nodes and their communication with the control plane. Kubernetes controllers . kube-scheduler which is the default scheduler for Kubernetes. Etcd's official documentation . Several container runtimes in Kubernetes. Integrating with cloud providers using cloud-controller-manager . kubectl commands. The Kubernetes API The Kubernetes API lets you query and manipulate the state of objects in Kubernetes. The core of Kubernetes' control plane is the API server and the HTTP API that it exposes. Users, the different parts of your cluster, and external components all communicate with one another through the API server. The core of Kubernetes' control plane is the API server . The API server exposes an HTTP API that lets end users, different parts of your cluster, and external components communicate with one another. The Kubernetes API lets you query and manipulate the state of API objects in Kubernetes (for example: Pods, Namespaces, ConfigMaps,

and Events). Most operations can be performed through the kubectl command-line interface or other command-line tools, such as kubeadm , which in turn use the API. However, you can also access the API directly using REST calls. Kubernetes provides a set of client libraries for those looking to write applications using the Kubernetes API. Each Kubernetes cluster publishes the specification of the APIs that the cluster serves. There are two mechanisms that Kubernetes uses to publish these API specifications; both are useful to enable automatic interoperability. For example, the kubectl tool fetches and caches the API specification for enabling command-line completion and other features. The two supported mechanisms are as follows: The Discovery API provides information about the Kubernetes APIs: API names, resources, versions, and supported operations. This is a Kubernetes specific term as it is a separate API from the Kubernetes OpenAPI. It is intended to be a brief summary of the a

vailable resources and it does not detail specific schema for the resources. For reference about resource schemas, please refer to the OpenAPI document. The Kubernetes OpenAPI Document provides (full) OpenAPI v2.0 and 3.0 schemas for all Kubernetes API endpoints. The OpenAPI v3 is the preferred method for accessing OpenAPI as it provides a more comprehensive and accurate view of the API. It includes all the available API paths, as well as all resources consumed and produced for every operations on every endpoints. It also includes any extensibility components that a cluster supports. The data is a complete specification and is significantly larger than that from the Discovery API.• • • • • • • •

Discovery API Kubernetes publishes a list of all group versions and resources supported via the Discovery API. This includes the following for each resource: Name Cluster or namespaced scope Endpoint URL and supported verbs Alternative names Group, version, kind The API is available both aggregated and unaggregated form. The aggregated discovery serves two endpoints while the unaggregated discovery serves a separate endpoint for each group version. Aggregated discovery FEATURE STATE: Kubernetes v1.27 [beta] Kubernetes offers beta support for aggregated discovery, publishing all resources supported by a cluster through two endpoints ( /api and /apis ). Requesting this endpoint drastically reduces the number of requests sent to fetch the discovery data from the cluster. You can access the data by requesting the respective endpoints with an Accept header indicating the aggregated discovery resource: Accept: application/ json;v=v2beta1;g=apidiscovery.k8s.io;as=APIGroupDiscoveryList . Wit

hout indicating the resource type using the Accept header, the default response for the /api and /apis endpoint is an unaggregated discovery document. The discovery document for the built-in resources can be found in the Kubernetes GitHub repository. This Github document can be used as a reference of the base set of the available resources if a Kubernetes cluster is not available to query. The endpoint also supports ETag and protobuf encoding. Unaggregated discovery Without discovery aggregation, discovery is published in levels, with the root endpoints publishing discovery information for downstream documents. A list of all group versions supported by a cluster is published at the /api and /apis endpoints. Example: { "kind": "APIGroupList", "apiVersion": "v1", "groups": [ { "name": "apiregistration.k8s.io", "versions": [ { "groupVersion": "apiregistration.k8s.io/v1", "version": "v1"• • • •

} ], "preferredVersion": { "groupVersion": "apiregistration.k8s.io/v1", "version": "v1" } }, { "name": "apps", "versions": [ { "groupVersion": "apps/v1", "version": "v1" } ], "preferredVersion": { "groupVersion": "apps/v1", "version": "v1" } }, ... } Additional requests are needed to obtain the discovery document for each group version at / apis/<group>/<version> (for example: /apis/rbac.authorization.k8s.io/v1alpha1 ), which advertises the list of resources served under a particular group version. These endpoints are used by kubectl to fetch the list of resources supported by a cluster. OpenAPI interface definition For details about the OpenAPI specifications, see the OpenAPI documentation . Kubernetes serves both OpenAPI v2.0 and OpenAPI v3.0. OpenAPI v3 is the preferred method of accessing the OpenAPI because it offers a more comprehensive (lossless) r

epresentation of Kubernetes resources. Due to limitations of OpenAPI version 2, certain fields are dropped from the published OpenAPI including but not limited to default , nullable , oneOf . OpenAPI V2 The Kubernetes API server serves an aggregated OpenAPI v2 spec via the /openapi/v2 endpoint. You can request the response format using request headers as follows: Valid request header values for OpenAPI v2 queries Header Possible values Notes Accept- Encodinggzipnot supplying this header is also acceptable Acceptapplication/com.github.proto- openapi.spec.v2@v1.0+protobufmainly for intra-cluster use application/json default * serves application/jso

OpenAPI V3 FEATURE STATE: Kubernetes v1.27 [stable] Kubernetes supports publishing a description of its APIs as OpenAPI v3. A discovery endpoint /openapi/v3 is provided to see a list of all group/versions available. This endpoint only returns JSON. These group/versions are provided in the following format: { "paths": { ..., "api/v1": { "serverRelativeURL": "/openapi/v3/api/v1? hash=CC0E9BFD992D8C59AEC98A1E2336F899E8318D3CF4C68944C3DEC640AF5AB52D864A C50DAA8D145B3494F75FA3CFF939FCBDDA431DAD3CA79738B297795818CF" }, "apis/admissionregistration.k8s.io/v1": { "serverRelativeURL": "/openapi/v3/apis/admissionregistration.k8s.io/v1? hash=E19CC93A116982CE5422FC42B590A8AFAD92CDE9AE4D59B5CAAD568F083AD07946E6 CB5817531680BCE6E215C16973CD39003B0425F3477CFD854E89A9DB6597" }, .... } } The relative URLs are pointing to immutable OpenAPI descriptions, in order to improve client- side caching. The proper HTTP caching heade