Group items tagged

Pod-to-Service communications

External-to-Service communications

sharing machines requires ensuring that two applications do not try to use the same ports.

Dynamic port allocation brings a lot of complications to the system

do not need to explicitly create links between Pods

almost never need to deal with mapping container ports to host ports.

pods on a node can communicate with all pods on all nodes without NAT

agents on a node (e.g. system daemons, kubelet) can communicate with all pods on that node

pods in the host network of a node can communicate with all pods on all nodes without NAT

containers within a Pod share their network namespaces - including their IP address

containers within a Pod must coordinate port usage

“IP-per-pod” model.

request ports on the Node itself which forward to your Pod (called host ports), but this is a very niche operation

The Pod itself is blind to the existence or non-existence of host ports.

AOS is an Intent-Based Networking system that creates and manages complex datacenter environments from a simple integrated platform.

Cisco Application Centric Infrastructure offers an integrated overlay and underlay SDN solution that supports containers, virtual machines, and bare metal servers.

AOS Reference Design currently supports Layer-3 connected hosts that eliminate legacy Layer-2 switching problems.

The AWS VPC CNI offers integrated AWS Virtual Private Cloud (VPC) networking for Kubernetes clusters.

users can apply existing AWS VPC networking and security best practices for building Kubernetes clusters.

Using this CNI plugin allows Kubernetes pods to have the same IP address inside the pod as they do on the VPC network.

The CNI allocates AWS Elastic Networking Interfaces (ENIs) to each Kubernetes node and using the secondary IP range from each ENI for pods on the node.

Big Cloud Fabric is a cloud native networking architecture, designed to run Kubernetes in private cloud/on-premises environments.

Cilium is L7/HTTP aware and can enforce network policies on L3-L7 using an identity based security model that is decoupled from network addressing.

CNI-Genie is a CNI plugin that enables Kubernetes to simultaneously have access to different implementations of the Kubernetes network model in runtime.

CNI-Genie also supports assigning multiple IP addresses to a pod, each from a different CNI plugin.

cni-ipvlan-vpc-k8s contains a set of CNI and IPAM plugins to provide a simple, host-local, low latency, high throughput, and compliant networking stack for Kubernetes within Amazon Virtual Private Cloud (VPC) environments by making use of Amazon Elastic Network Interfaces (ENI) and binding AWS-managed IPs into Pods using the Linux kernel’s IPvlan driver in L2 mode.

to be straightforward to configure and deploy within a VPC

Contiv provides configurable networking

Contrail, based on Tungsten Fabric, is a truly open, multi-cloud network virtualization and policy management platform.

DANM is a networking solution for telco workloads running in a Kubernetes cluster.

Flannel is a very simple overlay network that satisfies the Kubernetes requirements.

Any traffic bound for that subnet will be routed directly to the VM by the GCE network fabric.

sysctl net.ipv4.ip_forward=1

Jaguar provides overlay network using vxlan and Jaguar CNIPlugin provides one IP address per pod.

Knitter is a network solution which supports multiple networking in Kubernetes.

Kube-OVN is an OVN-based kubernetes network fabric for enterprises.

Kube-router provides a Linux LVS/IPVS-based service proxy, a Linux kernel forwarding-based pod-to-pod networking solution with no overlays, and iptables/ipset-based network policy enforcer.

If you have a “dumb” L2 network, such as a simple switch in a “bare-metal” environment, you should be able to do something similar to the above GCE setup.

Multus is a Multi CNI plugin to support the Multi Networking feature in Kubernetes using CRD based network objects in Kubernetes.

NSX-T can provide network virtualization for a multi-cloud and multi-hypervisor environment and is focused on emerging application frameworks and architectures that have heterogeneous endpoints and technology stacks.

NSX-T Container Plug-in (NCP) provides integration between NSX-T and container orchestrators such as Kubernetes

Nuage uses the open source Open vSwitch for the data plane along with a feature rich SDN Controller built on open standards.

OpenVSwitch is a somewhat more mature but also complicated way to build an overlay network

OVN is an opensource network virtualization solution developed by the Open vSwitch community.

Project Calico is an open source container networking provider and network policy engine.

Calico provides a highly scalable networking and network policy solution for connecting Kubernetes pods based on the same IP networking principles as the internet

Calico can be deployed without encapsulation or overlays to provide high-performance, high-scale data center networking.

Romana is an open source network and security automation solution that lets you deploy Kubernetes without an overlay network

Weave Net runs as a CNI plug-in or stand-alone. In either version, it doesn’t require any configuration or extra code to run, and in both cases, the network provides one IP address per pod - as is standard for Kubernetes.

The network model is implemented by the container runtime on each node.

Auto DevOps works with any Kubernetes cluster;

using the Docker or Kubernetes executor, with privileged mode enabled.

Base domain (needed for Auto Review Apps and Auto Deploy)

Kubernetes (needed for Auto Review Apps, Auto Deploy, and Auto Monitoring)

Prometheus (needed for Auto Monitoring)

scrape your Kubernetes cluster.

project level as a variable: KUBE_INGRESS_BASE_DOMAIN

A wildcard DNS A record matching the base domain(s) is required

Once set up, all requests will hit the load balancer, which in turn will route them to the Kubernetes pods that run your application(s).

review/ (every environment starting with review/)

staging

production

need to define a separate KUBE_INGRESS_BASE_DOMAIN variable for all the above based on the environment.

Continuous deployment to production: Enables Auto Deploy with master branch directly deployed to production.

Continuous deployment to production using timed incremental rollout

Automatic deployment to staging, manual deployment to production

Auto Build creates a build of the application using an existing Dockerfile or Heroku buildpacks.

If a project’s repository contains a Dockerfile, Auto Build will use docker build to create a Docker image.

Each buildpack requires certain files to be in your project’s repository for Auto Build to successfully build your application.

Auto Test automatically runs the appropriate tests for your application using Herokuish and Heroku buildpacks by analyzing your project to detect the language and framework.

Auto Code Quality uses the Code Quality image to run static analysis and other code checks on the current code.

Static Application Security Testing (SAST) uses the SAST Docker image to run static analysis on the current code and checks for potential security issues.

Dependency Scanning uses the Dependency Scanning Docker image to run analysis on the project dependencies and checks for potential security issues.

License Management uses the License Management Docker image to search the project dependencies for their license.

Vulnerability Static Analysis for containers uses Clair to run static analysis on a Docker image and checks for potential security issues.

Review Apps are temporary application environments based on the branch’s code so developers, designers, QA, product managers, and other reviewers can actually see and interact with code changes as part of the review process. Auto Review Apps create a Review App for each branch. Auto Review Apps will deploy your app to your Kubernetes cluster only. When no cluster is available, no deployment will occur.

The Review App will have a unique URL based on the project ID, the branch or tag name, and a unique number, combined with the Auto DevOps base domain.

Your apps should not be manipulated outside of Helm (using Kubernetes directly).

Dynamic Application Security Testing (DAST) uses the popular open source tool OWASP ZAProxy to perform an analysis on the current code and checks for potential security issues.

Auto Browser Performance Testing utilizes the Sitespeed.io container to measure the performance of a web page.

add the paths to a file named .gitlab-urls.txt in the root directory, one per line.

After a branch or merge request is merged into the project’s default branch (usually master), Auto Deploy deploys the application to a production environment in the Kubernetes cluster, with a namespace based on the project name and unique project ID

Auto Deploy doesn’t include deployments to staging or canary by default, but the Auto DevOps template contains job definitions for these tasks if you want to enable them.

For internal and private projects a GitLab Deploy Token will be automatically created, when Auto DevOps is enabled and the Auto DevOps settings are saved.

If the GitLab Deploy Token cannot be found, CI_REGISTRY_PASSWORD is used. Note that CI_REGISTRY_PASSWORD is only valid during deployment.

If present, DB_INITIALIZE will be run as a shell command within an application pod as a helm post-install hook.

a post-install hook means that if any deploy succeeds, DB_INITIALIZE will not be processed thereafter.

DB_MIGRATE will be run as a shell command within an application pod as a helm pre-upgrade hook.

Once your application is deployed, Auto Monitoring makes it possible to monitor your application’s server and response metrics right out of the box.

annotate the NGINX Ingress deployment to be scraped by Prometheus using prometheus.io/scrape: "true" and prometheus.io/port: "10254"

While Auto DevOps provides great defaults to get you started, you can customize almost everything to fit your needs; from custom buildpacks, to Dockerfiles, Helm charts, or even copying the complete CI/CD configuration into your project to enable staging and canary deployments, and more.

Auto DevOps uses Helm to deploy your application to Kubernetes.

make use of the HELM_UPGRADE_EXTRA_ARGS environment variable to override the default values in the values.yaml file in the default Helm chart.

specify the use of a custom Helm chart per environment by scoping the environment variable to the desired environment.

Your additions will be merged with the Auto DevOps template using the behaviour described for include

copy and paste the contents of the Auto DevOps template into your project and edit this as needed.

In order to support applications that require a database, PostgreSQL is provisioned by default.

Set up the replica variables using a project variable and scale your application by just redeploying it!

You should not scale your application using Kubernetes directly.

Some applications need to define secret variables that are accessible by the deployed application.

Auto DevOps pipelines will take your application secret variables to populate a Kubernetes secret.

Environment variables are generally considered immutable in a Kubernetes pod.

If STAGING_ENABLED is defined in your project (e.g., set STAGING_ENABLED to 1 as a CI/CD variable), then the application will be automatically deployed to a staging environment, and a production_manual job will be created for you when you’re ready to manually deploy to production.

If CANARY_ENABLED is defined in your project (e.g., set CANARY_ENABLED to 1 as a CI/CD variable) then two manual jobs will be created: canary which will deploy the application to the canary environment production_manual which is to be used by you when you’re ready to manually deploy to production.

If INCREMENTAL_ROLLOUT_MODE is set to manual in your project, then instead of the standard production job, 4 different manual jobs will be created: rollout 10% rollout 25% rollout 50% rollout 100%

To start a job, click on the play icon next to the job’s name.

not all buildpacks support Auto Test yet

When a project has been marked as private, GitLab’s Container Registry requires authentication when downloading containers.

Authentication credentials will be valid while the pipeline is running, allowing for a successful initial deployment.

We strongly advise using GitLab Container Registry with Auto DevOps in order to simplify configuration and prevent any unforeseen issues.

Kubernetes is fully controlled through this API

the main job of kubectl is to carry out HTTP requests to the Kubernetes API

Kubernetes maintains an internal state of resources, and all Kubernetes operations are CRUD operations on these resources.

Kubernetes is a fully resource-centred system

Kubernetes API reference is organised as a list of resource types with their associated operations.

This is how kubectl works for all commands that interact with the Kubernetes cluster.

kubectl simply makes HTTP requests to the appropriate Kubernetes API endpoints.

it's totally possible to control Kubernetes with a tool like curl by manually issuing HTTP requests to the Kubernetes API.

Kubernetes consists of a set of independent components that run as separate processes on the nodes of a cluster.

components on the master nodes

Storage backend: stores resource definitions (usually etcd is used)

API server: provides Kubernetes API and manages storage backend

Controller manager: ensures resource statuses match specifications

Scheduler: schedules Pods to worker nodes

component on the worker nodes

Kubelet: manages execution of containers on a worker node

triggers the ReplicaSet controller, which is a sub-process of the controller manager.

the scheduler, who watches for Pod definitions that are not yet scheduled to a worker node.

creating and updating resources in the storage backend on the master node.

However, these components do not access the storage backend directly, but only through the Kubernetes API.

All other Kubernetes components and users read, watch, and manipulate the state (i.e. resources) of Kubernetes through the Kubernetes API

The storage backend stores the state (i.e. resources) of Kubernetes.

command completion is a shell feature that works by the means of a completion script.

A completion script is a shell script that defines the completion behaviour for a specific command. Sourcing a completion script enables completion for the corresponding command.

kubectl completion zsh

/etc/bash_completion.d directory (create it, if it doesn't exist)

source <(kubectl completion bash)

source <(kubectl completion zsh)

autoload -Uz compinit compinit

the API reference, which contains the full specifications of all resources.

kubectl api-resources

displays the resource names in their plural form (e.g. deployments instead of deployment). It also displays the shortname (e.g. deploy) for those resources that have one. Don't worry about these differences. All of these name variants are equivalent for kubectl.

.spec

custom columns output format comes in. It lets you freely define the columns and the data to display in them. You can choose any field of a resource to be displayed as a separate column in the output

kubectl get pods -o custom-columns='NAME:metadata.name,NODE:spec.nodeName'

kubectl explain pod.spec.

kubectl explain pod.metadata.

browse the resource specifications and try it out with any fields you like!

with kubectl explain, only a subset of the JSONPath capabilities is supported

Many fields of Kubernetes resources are lists, and this operator allows you to select items of these lists. It is often used with a wildcard as [*] to select all items of the list.

kubectl get pods -o custom-columns='NAME:metadata.name,IMAGES:spec.containers[*].image'

a Pod may contain more than one container.

The availability zones for each node are obtained through the special failure-domain.beta.kubernetes.io/zone label.

kubectl get nodes -o yaml kubectl get nodes -o json

The default kubeconfig file is ~/.kube/config

with multiple clusters, then you have connection parameters for multiple clusters configured in your kubeconfig file.

overwrite the default kubeconfig file with the --kubeconfig option for every kubectl command.

Namespace: the namespace to use when connecting to the cluster

a one-to-one mapping between clusters and contexts.

When kubectl reads a kubeconfig file, it always uses the information from the current context.

just change the current context in the kubeconfig file

kubectl also provides the --cluster, --user, --namespace, and --context options that allow you to overwrite individual elements and the current context itself, regardless of what is set in the kubeconfig file.

for switching between clusters and namespaces is kubectx.

kubectl config get-contexts

just have to download the shell scripts named kubectl-ctx and kubectl-ns to any directory in your PATH and make them executable (for example, with chmod +x)

kubectl proxy

kubectl get roles

kubectl get pod

Kubectl plugins are distributed as simple executable files with a name of the form kubectl-x. The prefix kubectl- is mandatory,

To install a plugin, you just have to copy the kubectl-x file to any directory in your PATH and make it executable (for example, with chmod +x)

krew itself is a kubectl plugin

check out the kubectl-plugins GitHub topic

The executable can be of any type, a Bash script, a compiled Go program, a Python script, it really doesn't matter. The only requirement is that it can be directly executed by the operating system.

kubectl plugins can be written in any programming or scripting language.

you can write more sophisticated plugins with real programming languages, for example, using a Kubernetes client library. If you use Go, you can also use the cli-runtime library, which exists specifically for writing kubectl plugins.

a kubeconfig file consists of a set of contexts

changing the current context means changing the cluster, if you have only a single context per cluster.

A chart is organized as a collection of files inside of a directory.

values.yaml # The default configuration values for this chart

charts/ # A directory containing any charts upon which this chart depends.

version: A SemVer 2 version (required)

apiVersion: The chart API version, always "v1" (required)

Every chart must have a version number. A version must follow the SemVer 2 standard.

When generating a package, the helm package command will use the version that it finds in the Chart.yaml as a token in the package name.

the appVersion field is not related to the version field. It is a way of specifying the version of the application.

appVersion: The version of the app that this contains (optional). This needn't be SemVer.

If the latest version of a chart in the repository is marked as deprecated, then the chart as a whole is considered to be deprecated.

deprecated: Whether this chart is deprecated (optional, boolean)

one chart may depend on any number of other charts.

the preferred method of declaring dependencies is by using a requirements.yaml file inside of your chart.

A requirements.yaml file is a simple file for listing your dependencies.

The repository field is the full URL to the chart repository.

helm dependency update and it will use your dependency file to download all the specified charts into your charts/ directory for you.

When helm dependency update retrieves charts, it will store them as chart archives in the charts/ directory.

All charts are loaded by default.

The condition field holds one or more YAML paths (delimited by commas). If this path exists in the top parent’s values and resolves to a boolean value, the chart will be enabled or disabled based on that boolean value.

The tags field is a YAML list of labels to associate with this chart.

all charts with tags can be enabled or disabled by specifying the tag and a boolean value.

The --set parameter can be used as usual to alter tag and condition values.

The first condition path that exists wins and subsequent ones for that chart are ignored.

The keys containing the values to be imported can be specified in the parent chart’s requirements.yaml file using a YAML list. Each item in the list is a key which is imported from the child chart’s exports field.

specifying the key data in our import list, Helm looks in the exports field of the child chart for data key and imports its contents.

To access values that are not contained in the exports key of the child chart’s values, you will need to specify the source key of the values to be imported (child) and the destination path in the parent chart’s values (parent).

To drop a dependency into your charts/ directory, use the helm fetch command

A dependency can be either a chart archive (foo-1.2.3.tgz) or an unpacked chart directory.

a single release is created with all the objects for the chart and its dependencies.

When Helm renders the charts, it will pass every file in that directory through the template engine.

Chart users may supply a YAML file that contains values. This can be provided on the command line with helm install.

Template files follow the standard conventions for writing Go templates

{{default "minio" .Values.storage}}

Values that are supplied via a values.yaml file (or via the --set flag) are accessible from the .Values object in a template.

Release.Name: The name of the release (not the chart)

Release.IsUpgrade: This is set to true if the current operation is an upgrade or rollback.

Chart: The contents of the Chart.yaml

Files: A map-like object containing all non-special files in the chart.

Files can be accessed using {{index .Files "file.name"}} or using the {{.Files.Get name}} or {{.Files.GetString name}} functions.

access the contents of the file as []byte using {{.Files.GetBytes}}

Any unknown Chart.yaml fields will be dropped

Chart.yaml cannot be used to pass arbitrarily structured data into the template.

A values file is formatted in YAML.

A chart may include a default values.yaml file

accessible inside of templates using the .Values object

Values files can declare values for the top-level chart, as well as for any of the charts that are included in that chart’s charts/ directory.

Charts at a higher level have access to all of the variables defined beneath.

lower level charts cannot access things in parent charts

Values are namespaced, but namespaces are pruned.

Helm supports special “global” value.

a way of sharing one top-level variable with all subcharts, which is useful for things like setting metadata properties like labels.

global variables of parent charts take precedence over the global variables from subcharts.

helm lint

A chart repository is an HTTP server that houses one or more packaged charts

Any HTTP server that can serve YAML files and tar files and can answer GET requests can be used as a repository server.

Helm does not provide tools for uploading charts to remote repository servers.

the only way to add a chart to $HELM_HOME/starters is to manually copy it there.

Helm provides a hook mechanism to allow chart developers to intervene at certain points in a release’s life cycle.

Hooks are declared as an annotation in the metadata section of a manifest

pre-install

post-install: Executes after all resources are loaded into Kubernetes

pre-delete

post-delete: Executes on a deletion request after all of the release’s resources have been deleted.

pre-upgrade

post-upgrade

pre-rollback

post-rollback: Executes on a rollback request after all resources have been modified.

crd-install

test-success: Executes when running helm test and expects the pod to return successfully (return code == 0).

test-failure: Executes when running helm test and expects the pod to fail (return code != 0).

Hooks allow you, the chart developer, an opportunity to perform operations at strategic points in a release lifecycle

Tiller then loads the hook with the lowest weight first (negative to positive)

Tiller returns the release name (and other data) to the client

If the resources is a Job kind, Tiller will wait until the job successfully runs to completion.

good practice to add a hook weight, and set it to 0 if weight is not important.

leave the hook resource alone.

To destroy such resources, you need to either write code to perform this operation in a pre-delete or post-delete hook or add "helm.sh/hook-delete-policy" annotation to the hook template file.

Hooks are just Kubernetes manifest files with special annotations in the metadata section

One resource can implement multiple hooks

no limit to the number of different resources that may implement a given hook.

Hook weights can be positive or negative numbers but must be represented as strings.

sort those hooks in ascending order.

Hook deletion policies

"before-hook-creation" specifies Tiller should delete the previous hook before the new hook is launched.

By default Tiller will wait for 60 seconds for a deleted hook to no longer exist in the API server before timing out.

Custom Resource Definitions (CRDs) are a special kind in Kubernetes.

The crd-install hook is executed very early during an installation, before the rest of the manifests are verified.

A common reason why the hook resource might already exist is that it was not deleted following use on a previous install/upgrade.

Helm uses Go templates for templating your resource files.

two special template functions: include and required

include function allows you to bring in another template, and then pass the results to other template functions.

The required function allows you to declare a particular values entry as required for template rendering.

Quote Strings, Don’t Quote Integers

when working with integers do not quote the values

env variables values which are expected to be string

to include a template, and then perform an operation on that template’s output, Helm has a special include function

The above includes a template called toYaml, passes it $value, and then passes the output of that template to the nindent function.

Go provides a way for setting template options to control behavior when a map is indexed with a key that’s not present in the map

The required function gives developers the ability to declare a value entry as required for template rendering.

The tpl function allows developers to evaluate strings as templates inside a template.

Rendering a external configuration file

(.Files.Get "conf/app.conf")

Image pull secrets are essentially a combination of registry, username, and password.

Automatically Roll Deployments When ConfigMaps or Secrets change

configmaps or secrets are injected as configuration files in containers

a restart may be required should those be updated with a subsequent helm upgrade

The sha256sum function can be used to ensure a deployment’s annotation section is updated if another file changes

helm upgrade --recreate-pods

"helm.sh/resource-policy": keep

resources that should not be deleted when Helm runs a helm delete

create some reusable parts in your chart

In the templates/ directory, any file that begins with an underscore(_) is not expected to output a Kubernetes manifest file.

The current best practice for composing a complex application from discrete parts is to create a top-level umbrella chart that exposes the global configurations, and then use the charts/ subdirectory to embed each of the components.

SAP’s Converged charts: These charts install SAP Converged Cloud a full OpenStack IaaS on Kubernetes. All of the charts are collected together in one GitHub repository, except for a few submodules.

Deis’s Workflow: This chart exposes the entire Deis PaaS system with one chart. But it’s different from the SAP chart in that this umbrella chart is built from each component, and each component is tracked in a different Git repository.

YAML is a superset of JSON

any valid JSON structure ought to be valid in YAML.

As a best practice, templates should follow a YAML-like syntax unless the JSON syntax substantially reduces the risk of a formatting issue.

There are functions in Helm that allow you to generate random data, cryptographic keys, and so on.

a chart repository is a location where packaged charts can be stored and shared.

A chart repository is an HTTP server that houses an index.yaml file and optionally some packaged charts.

Because a chart repository can be any HTTP server that can serve YAML and tar files and can answer GET requests, you have a plethora of options when it comes down to hosting your own chart repository.

It is not required that a chart package be located on the same server as the index.yaml file.

A valid chart repository must have an index file. The index file contains information about each chart in the chart repository.

The Helm project provides an open-source Helm repository server called ChartMuseum that you can host yourself.

$ helm repo index fantastic-charts --url https://fantastic-charts.storage.googleapis.com

A repository will not be added if it does not contain a valid index.yaml

add the repository to their helm client via the helm repo add [NAME] [URL] command with any name they would like to use to reference the repository.

Helm has provenance tools which help chart users verify the integrity and origin of a package.

Integrity is established by comparing a chart to a provenance record

The provenance file contains a chart’s YAML file plus several pieces of verification information

Chart repositories serve as a centralized collection of Helm charts.

Chart repositories must make it possible to serve provenance files over HTTP via a specific request, and must make them available at the same URI path as the chart.

We don’t want to be “the certificate authority” for all chart signers. Instead, we strongly favor a decentralized model, which is part of the reason we chose OpenPGP as our foundational technology.

The Keybase platform provides a public centralized repository for trust information.

A chart contains a number of Kubernetes resources and components that work together.

A test in a helm chart lives under the templates/ directory and is a pod definition that specifies a container with a given command to run.

The pod definition must contain one of the helm test hook annotations: helm.sh/hook: test-success or helm.sh/hook: test-failure

helm test

nest your test suite under a tests/ directory like <chart-name>/templates/tests/

name-based virtual hosting

Edge routerA router that enforces the firewall policy for your cluster.

A Kubernetes ServiceA way to expose an application running on a set of Pods as a network service. that identifies a set of Pods using labelTags objects with identifying attributes that are meaningful and relevant to users. selectors.

Ingress exposes HTTP and HTTPS routes from outside the cluster to services within the cluster.

An Ingress can be configured to give Services externally-reachable URLs, load balance traffic, terminate SSL / TLS, and offer name based virtual hosting.

Exposing services other than HTTP and HTTPS to the internet typically uses a service of type Service.Type=NodePort or Service.Type=LoadBalancer.

Ingress frequently uses annotations to configure some options depending on the Ingress controller,

An optional host.

A list of paths

A backend is a combination of Service and port names

has an associated backend

Both the host and path must match the content of an incoming request before the load balancer directs traffic to the referenced Service.

HTTP (and HTTPS) requests to the Ingress that matches the host and path of the rule are sent to the listed backend.

An Ingress with no rules sends all traffic to a single default backend.

Ingress controllers and load balancers may take a minute or two to allocate an IP address.

A fanout configuration routes traffic from a single IP address to more than one Service, based on the HTTP URI being requested.

nginx.ingress.kubernetes.io/rewrite-target: /

describe ingress

get ingress

Name-based virtual hosts support routing HTTP traffic to multiple host names at the same IP address.

an Ingress resource without any hosts defined in the rules, then any web traffic to the IP address of your Ingress controller can be matched without a name based virtual host being required.

secure an Ingress by specifying a SecretStores sensitive information, such as passwords, OAuth tokens, and ssh keys. that contains a TLS private key and certificate.