1overview - Kubernetes

8/12/22, 2:55 PM Overview | Kubernetes
Overview
Get a high-level outline of Kubernetes and the components it is built from.
1: What is Kubernetes?
2: Kubernetes Components
3: The Kubernetes API
4: Working with Kubernetes Objects
4.1: Understanding Kubernetes Objects
4.2: Kubernetes Object Management
4.3: Object Names and IDs
4.4: Namespaces
4.5: Labels and Selectors
4.6: Annotations
4.7: Field Selectors
4.8: Finalizers
4.9: Owners and Dependents
4.10: Recommended Labels
1 - What is 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 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 widely
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.
https://kubernetes.io/docs/concepts/overview/_print/ 1/37
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 physical 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 efficiency 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 micro-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. Kubernetes 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.
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 your 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 state. 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
Ready to Get Started?
2 - Kubernetes Components
A Kubernetes cluster consists of the components that represent 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.
Kubernetes cluster
API server
api
Cloud controller
c-m
c-m c-c-m manager
c-c-m
c-m c-c-m (optional) c-c-m
Controller
manager c-m
etcd
api
Node Node (persistence store) etcd
api Node
api
kubelet
kubelet
kubelet kubelet kubelet kube-proxy

etcd k-proxy
sched
sched
sched
Scheduler
sched
Control Plane k-proxy k-proxy k-proxy

Control plane
Node
The components of a Kubernetes cluster
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,
set up 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-apiserver 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 those 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.
Some types of these controllers 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.
Endpoints controller: Populates the Endpoints object (that is, joins Services & Pods).
Service Account & Token controllers: Create default accounts and API access tokens for
new namespaces.
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 than 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 part 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
The container runtime is the software that is responsible for running containers.
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 automatically 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.
What's next
Learn about Nodes
Learn about Controllers
Learn about kube-scheduler
Read etcd's official documentation
3 - 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.
Consider using one of the client libraries

if you are writing an application using the
Kubernetes API.
OpenAPI specification
Complete API details are documented using OpenAPI.
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:
Header Possible values Notes
Accept- gzip not supplying this header is

Encoding also acceptable
Accept application/com.github.proto- mainly for intra-cluster use

openapi.spec.v2@v1.0+protobuf
application/json default
* serves application/json
Kubernetes implements an alternative Protobuf based serialization format that

is primarily
intended for intra-cluster communication. For more information
about this format, see the
Kubernetes Protobuf serialization design proposal and the
Interface Definition Language (IDL)
files for each schema located in the Go
packages that define the API objects.
OpenAPI V3
FEATURE STATE: Kubernetes v1.24 [beta]
Kubernetes v1.24 offers beta support for publishing its APIs as OpenAPI v3; this is a
beta
feature that is enabled by default.
You can disable the beta feature by turning off the
feature
gate named OpenAPIV3
for the kube-apiserver component.
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=CC0E9BFD992D8C59AEC98A1E2336
},
"apis/admissionregistration.k8s.io/v1": {
"serverRelativeURL": "/openapi/v3/apis/admissionregistration.k8s.io/v1?has
},
...
The relative URLs are pointing to immutable OpenAPI descriptions, in

order to improve client-
side caching. The proper HTTP caching headers
are also set by the API server for that purpose
( Expires to 1 year in
the future, and Cache-Control to immutable ). When an obsolete URL is
used, the API server returns a redirect to the newest URL.
The Kubernetes API server publishes an OpenAPI v3 spec per Kubernetes

group version at the
/openapi/v3/apis/<group>/<version>?hash=<hash>
endpoint.
Refer to the table below for accepted request headers.
Header Possible values Notes
Accept- gzip not supplying this header is

Encoding also acceptable
Accept application/com.github.proto- mainly for intra-cluster use

openapi.spec.v3@v1.0+protobuf
application/json default
* serves application/json
Persistence
Kubernetes stores the serialized state of objects by writing them into
etcd.
API groups and versioning

To make it easier to eliminate fields or restructure resource representations,
Kubernetes
supports multiple API versions, each at a different API path, such
as /api/v1 or
/apis/rbac.authorization.k8s.io/v1alpha1 .
Versioning is done at the API level rather than at the resource or field level
to ensure that the
API presents a clear, consistent view of system resources
and behavior, and to enable
controlling access to end-of-life and/or
experimental APIs.
To make it easier to evolve and to extend its API, Kubernetes implements

API groups that can
be
enabled or disabled.
API resources are distinguished by their API group, resource type, namespace
(for
namespaced resources), and name. The API server handles the conversion between
API
versions transparently: all the different versions are actually representations
of the same
persisted data. The API server may serve the same underlying data
through multiple API
versions.
For example, suppose there are two API versions, v1 and v1beta1 , for the same
resource. If
you originally created an object using the v1beta1 version of its
API, you can later read,
update, or delete that object
using either the v1beta1 or the v1 API version.
API changes
Any system that is successful needs to grow and change as new use cases emerge or existing
ones change.
Therefore, Kubernetes has designed the Kubernetes API to continuously change
and grow.
The Kubernetes project aims to not break compatibility with existing clients, and to
maintain that
compatibility for a length of time so that other projects have an opportunity to
adapt.
In general, new API resources and new resource fields can be added often and frequently.
Elimination of resources or fields requires following the
API deprecation policy.
Kubernetes makes a strong commitment to maintain compatibility for official Kubernetes

APIs
once they reach general availability (GA), typically at API version v1 . Additionally,
Kubernetes keeps compatibility even for beta API versions wherever feasible:
if you adopt a
beta API you can continue to interact with your cluster using that API,
even after the feature
goes stable.
Note: Although Kubernetes also aims to maintain compatibility for alpha APIs versions, in
some
circumstances this is not possible. If you use any alpha API versions, check the
release notes
for Kubernetes when upgrading your cluster, in case the API did change.
Refer to API versions reference

for more details on the API version level definitions.
API Extension
The Kubernetes API can be extended in one of two ways:
1. Custom resources
let you declaratively define how the API server should provide your
chosen resource API.
2. You can also extend the Kubernetes API by implementing an
aggregation layer.
What's next
Learn how to extend the Kubernetes API by adding your own
CustomResourceDefinition.
Controlling Access To The Kubernetes API describes
how the cluster manages
authentication and authorization for API access.
Learn about API endpoints, resource types and samples by reading
API Reference.
Learn about what constitutes a compatible change, and how to change the API, from
API
changes.
4 - Working with Kubernetes Objects

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.
4.1 - Understanding Kubernetes

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 running. 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 a .yaml file. kubectl converts the information to JSON when
making the API
request.
Here's an example .yaml file 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: nginx
spec:
containers:
- name: nginx
image: nginx:1.14.2
ports:
- containerPort: 80
One way to create a Deployment using a .yaml 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 .yaml 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.
What's next
Learn about the most important basic Kubernetes objects, such as Pod.
Learn about controllers in Kubernetes.
Using the Kubernetes API explains some more API concepts.
4.2 - 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 Operates Recommended Supported Learning

technique on environment writers curve
Imperative Live objects Development 1+ Lowest

commands projects
Imperative object Individual Production projects 1 Moderate

configuration files
Declarative object Directories Production projects 1+ Highest

configuration of files
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 compared 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 from 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 Kubernetes 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
4.3 - 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.
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 more 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.
contain at most 63 characters

contain only lowercase alphanumeric characters or '-'
start 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.
contain at most 63 characters

contain only lowercase alphanumeric characters or '-'
start with an alphabetic character
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 in Kubernetes.
See the Identifiers and Names in Kubernetes design document.
4.4 - 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. StorageClass, 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.
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 namespaces in a cluster using:
kubectl get namespace
NAME STATUS AGE
default Active 1d
kube-node-lease Active 1d
kube-public Active 1d
kube-system Active 1d
Kubernetes starts with four initial namespaces:
default The default namespace for objects with no other namespace

kube-system The namespace for objects created by the Kubernetes system
kube-public This namespace is created automatically and is readable by all users

(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-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.
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 configuration 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 themselves 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 1.21 [beta]
The Kubernetes control plane sets an immutable label kubernetes.io/metadata.name on all

namespaces, provided that the NamespaceDefaultLabelName feature gate is enabled.
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.
4.5 - Labels and Selectors

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 the configuration file 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 the 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 frontend 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: "k8s.gcr.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.
Similarly 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 exists 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.
Labels 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.
4.6 - 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
permitted by labels.
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.
Syntax 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 the configuration file for a Pod that has the annotation imageregistry:
https://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.
4.7 - Field Selectors

Field selectors let you select Kubernetes resources 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 get ingress --field-selector foo.bar=baz
Error from server (BadRequest): Unable to find "ingresses" that match label selector "",
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
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!=d
4.8 - 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 complete, 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 resources 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 request 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 its metadata.finalizers field is empty.
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.
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 the 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.
4.9 - 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 objects 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 from 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-selector=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 policy, 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.
4.10 - 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
aren'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 The name of the application mysql strin

.io/name g
app.kubernetes A unique name identifying the instance of an mysql- strin

.io/instance application abcxzy g
app.kubernetes The current version of the application (e.g., a 5.7.21 strin

.io/version semantic version, revision hash, etc.) g
app.kubernetes The component within the architecture database strin

.io/component g
app.kubernetes The name of a higher level application this wordpres strin

.io/part-of one is part of s g
app.kubernetes The tool being used to manage the operation helm strin
.io/managed-by of an application g
app.kubernetes The controller/user who created this controlle strin

.io/created-by resource r-manager g
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/managed-by: helm
app.kubernetes.io/created-by: controller-manager
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
form.
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/component: server
...
The Service is used to expose WordPress:
apiVersion: v1
kind: Service
metadata:
labels:
app.kubernetes.io/name: wordpress
app.kubernetes.io/instance: wordpress-abcxzy
app.kubernetes.io/component: server
...
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:
...
The Service is used to expose MySQL as part of WordPress:
apiVersion: v1
kind: Service
metadata:
labels:
...
With the MySQL StatefulSet and Service you'll notice information about both MySQL and
WordPress, the broader application, are included.

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8/12/22, 2:55 PM Overview | Kubernetes

This page is an overview of Kubernetes.

Kubernetes is a portable, extensible, open source platform for managing containerized

Going back in time

Traditional deployment era:

Why you need Kubernetes and what it can do

Kubernetes provides you with:

Service discovery and load balancing

What Kubernetes is not

defined workflow: first do A, then B, then C. In contrast, Kubernetes comprises a set of

When you deploy Kubernetes, you get a cluster.

A Kubernetes cluster consists of a set of worker machines, called nodes,

The worker node(s) host the Pods that are

control plane manages the worker

kubelet kubelet kubelet kube-proxy

Control Plane k-proxy k-proxy k-proxy

The components of a Kubernetes cluster

Control Plane Components

The main implementation of a Kubernetes API server is kube-apiserver.

Factors taken into account for scheduling decisions include:

Some types of these controllers are:

As with the kube-controller-manager, the cloud-controller-manager combines several logically

The following controllers can have cloud provider dependencies:

Kubernetes supports container runtimes such as

Container Resource Monitoring

3 - The Kubernetes API

The core of Kubernetes' control plane

Most operations can be performed through the

Consider using one of the client libraries

Header Possible values Notes

Accept- gzip not supplying this header is

Accept application/com.github.proto- mainly for intra-cluster use

Kubernetes implements an alternative Protobuf based serialization format that

A discovery endpoint /openapi/v3 is provided to see a list of all

The relative URLs are pointing to immutable OpenAPI descriptions, in

The Kubernetes API server publishes an OpenAPI v3 spec per Kubernetes

Refer to the table below for accepted request headers.

Header Possible values Notes

Accept- gzip not supplying this header is

Accept application/com.github.proto- mainly for intra-cluster use

API groups and versioning

To make it easier to evolve and to extend its API, Kubernetes implements

Kubernetes makes a strong commitment to maintain compatibility for official Kubernetes

Refer to API versions reference

4 - Working with Kubernetes Objects

4.1 - Understanding Kubernetes

Understanding Kubernetes objects

What containerized applications are running (and on which nodes)

To work with Kubernetes objects--whether to create, modify, or delete them--you'll need to

Object Spec and Status

For example: in Kubernetes, a Deployment is an object that can represent an

Describing a Kubernetes object

replicas: 2 # tells deployment to run 2 pods matching the template

kubectl apply -f https://k8s.io/examples/application/deployment.yaml

The output is similar to this:

For example, see the spec field

Within the .spec of a StatefulSet is a template

4.2 - Kubernetes Object Management