To fully leverage the capability of containers when developing and running enterprise-quality applications, ensure your environment is supported by tools that allow containers to be:
Created as discrete microservices that can be connected to other containerized, and non-containerized, services. For example, you might want to join your application with a database or attach a monitoring application to it.
Resilient, so if a server crashes or needs to go down for maintenance or to be decommissioned, containers can start on another machine.
Automated to pick up code changes automatically and then start and deploy new versions of themselves.
Scaled up, or replicated, to have more instances serving clients as demand increases and then spun down to fewer instances as demand declines.
Run in different ways, depending on the type of application. For example, one application might run once a month to produce a report and then exit. Another application might need to run constantly and be highly available to clients.
Managed so you can watch the state of your application and react when something goes wrong.
Containers’ widespread acceptance, and the resulting requirements for tools and methods to make them enterprise-ready, resulted in many options for them.
The rest of this section explains options for assets you can create when you build and deploy containerized Kubernetes applications in Azure Red Hat OpenShift. It also describes which approaches you might use for different kinds of applications and development requirements.
You can approach application development with containers in many ways, and different approaches might be more appropriate for different situations. To illustrate some of this variety, the series of approaches that is presented starts with developing a single container and ultimately deploys that container as a mission-critical application for a large enterprise. These approaches show different tools, formats, and methods that you can employ with containerized application development. This topic describes:
Building a simple container and storing it in a registry
Creating a Kubernetes manifest and saving it to a Git repository
Making an Operator to share your application with others
You have an idea for an application and you want to containerize it.
First you require a tool for building a container, like buildah or docker, and a file that describes what goes in your container, which is typically a Dockerfile.
Next, you require a location to push the resulting container image so you can pull it to run anywhere you want it to run. This location is a container registry.
Some examples of each of these components are installed by default on most Linux operating systems, except for the Dockerfile, which you provide yourself.
The following diagram displays the process of building and pushing an image:
If you use a computer that runs Red Hat Enterprise Linux (RHEL) as the operating system, the process of creating a containerized application requires the following steps:
Install container build tools: RHEL contains a set of tools that includes podman, buildah, and skopeo that you use to build and manage containers.
Create a Dockerfile to combine base image and software: Information about
building your container goes into a file that is named
Dockerfile. In that
file, you identify the base image you build from, the software packages you
install, and the software you copy into the container. You also identify
parameter values like network ports that you expose outside the container and
volumes that you mount inside the container. Put your Dockerfile and the
software you want to containerized in a directory on your RHEL system.
Run buildah or docker build: Run the
buildah build-using-dockerfile or
docker build command to pull you chosen base image to the local system and
creates a container image that is stored locally. You can also build container
without a Dockerfile by using buildah.
Tag and push to a registry: Add a tag to your new container image that
identifies the location of the registry in which you want to store and share
your container. Then push that image to the registry by running the
podman push or
docker push command.
Pull and run the image: From any system that has a container client tool,
such as podman or docker, run a command that identifies your new image.
For example, run the
podman run <image_name> or
docker run <image_name>
<image_name> is the name of your new container image, which
quay.io/myrepo/myapp:latest. The registry might require credentials
to push and pull images.
While the Docker Container Engine and
docker command are popular tools
to work with containers, with RHEL and many other Linux systems, you can
instead choose a different set of container tools that includes podman, skopeo,
and buildah. You can still use Docker Container Engine tools to create
containers that will run in Azure Red Hat OpenShift and any other container platform.
Building and managing containers with buildah, podman, and skopeo results in industry standard container images that include features tuned specifically for ultimately deploying those containers in Azure Red Hat OpenShift or other Kubernetes environments. These tools are daemonless and can be run without root privileges, so there is less overhead in running them.
When you ultimately run your containers in Azure Red Hat OpenShift, you use the CRI-O container engine. CRI-O runs on every worker and master machine in an Azure Red Hat OpenShift cluster, but CRI-O is not yet supported as a standalone runtime outside of Azure Red Hat OpenShift.
The base image you choose to build your application on contains a set of software that resembles a Linux system to your application. When you build your own image, your software is placed into that file system and sees that file system as though it were looking at its operating system. Choosing this base image has major impact on how secure, efficient and upgradeable your container is in the future.
Red Hat provides a new set of base images referred to as Red Hat Universal Base Images (UBI). These images are based on Red Hat Enterprise Linux and are similar to base images that Red Hat has offered in the past, with one major difference: they are freely redistributable without a Red Hat subscription. As a result, you can build your application on UBI images without having to worry about how they are shared or the need to create different images for different environments.
These UBI images have standard, init, and minimal versions. You can also use the Red Hat Software Collections images as a foundation for applications that rely on specific runtime environments such as Node.js, Perl, or Python. Special versions of some of these runtime base images referred to as Source-to-image (S2I) images. With S2I images, you can insert your code into a base image environment that is ready to run that code.
S2I images are available for you to use directly from the Azure Red Hat OpenShift web UI by selecting Catalog → Developer Catalog, as shown in the following figure:
Container Registries are where you store container images so you can share them with others and make them available to the platform where they ultimately run. You can select large, public container registries that offer free accounts or a premium version that offer more storage and special features. You can also install your own registry that can be exclusive to your organization or selectively shared with others.
To get Red Hat images and certified partner images, you can draw from the
Red Hat Registry. The Red Hat Registry is represented by two locations:
registry.access.redhat.com, which is unauthenticated and deprecated, and
registry.redhat.io, which requires authentication. You can learn about the Red
Hat and partner images in the Red Hat Registry from the
Red Hat Container Catalog.
Besides listing Red Hat container images, it also shows extensive information
about the contents and quality of those images, including health scores that are
based on applied security updates.
Large, public registries include Docker Hub and Quay.io. The Quay.io registry is owned and managed by Red Hat. Many of the components used in Azure Red Hat OpenShift are stored in Quay.io, including container images and the Operators that are used to deploy Azure Red Hat OpenShift itself. Quay.io also offers the means of storing other types of content, including Helm Charts.
If you want your own, private container registry, Azure Red Hat OpenShift itself includes a private container registry that is installed with Azure Red Hat OpenShift and runs on its cluster. Red Hat also offers a private version of the Quay.io registry called Red Hat Quay. Red Hat Quay includes geo replication, Git build triggers, Clair image scanning, and many other features.
All of the registries mentioned here can require credentials to download images from those registries. Some of those credentials are presented on a cluster-wide basis from Azure Red Hat OpenShift, while other credentials can be assigned to individuals.
While the container image is the basic building block for a containerized application, more information is required to manage and deploy that application in a Kubernetes environment such as Azure Red Hat OpenShift. The typical next steps after you create an image are to:
Understand the different resources you work with in Kubernetes manifests
Make some decisions about what kind of an application you are running
Gather supporting components
Create a manifest and store that manifest in a Git repository so you can store it in a source versioning system, audit it, track it, promote and deploy it to the next environment, roll it back to earlier versions, if necessary, and share it with others
While the container image is the basic unit with docker, the basic units that Kubernetes works with are called Pods. Pods represent the next step in building out an application. A Pod can contain one or more than one container. The key is that the Pod is the single unit that you deploy, scale, and manage.
Scalability and namespaces are probably the main items to consider when determining what goes in a Pod. For ease of deployment, you might want to deploy a container in a Pod and include its own logging and monitoring container in the Pod. Later, when you run the Pod and need to scale up an additional instance, those other containers are scaled up with it. For namespaces, containers in a Pod share the same network interfaces, shared storage volumes, and resource limitations, such as memory and CPU, which makes it easier to manage the contents of the Pod as a single unit. Containers in a Pod can also communicate with each other by using standard inter-process communications, such as System V semaphores or POSIX shared memory.
While individual Pods represent a scalable unit in Kubernetes, a service provides a means of grouping together a set of Pods to create a complete, stable application that can complete tasks such as load balancing. A service is also more permanent than a Pod because the service remains available from the same IP address until you delete it. When the service is in use, it is requested by name and the Azure Red Hat OpenShift cluster resolves that name into the IP addresses and ports where you can reach the Pods that compose the service.
By their nature, containerized applications are separated from the operating systems where they run and, by extension, their users. Part of your Kubernetes manifest describes how to expose the application to internal and external networks by defining network policies that allow fine-grained control over communication with your containerized applications. To connect incoming requests for HTTP, HTTPS, and other services from outside your cluster to services inside your cluster, you can use an Ingress resource.
If your container requires on-disk storage instead of database storage, which might be provided through a service, you can add volumes to your manifests to make that storage available to your Pods. You can configure the manifests to create persistent volumes (PVs) or dynamically create volumes that are added to your Pod definitions.
Next, consider how your application type influences how to run it.
Kubernetes defines different types of workloads that are appropriate for different kinds of applications. To determine the appropriate workload for your application, consider if the application is:
Meant to run to completion and be done. An example is an application that starts up to produce a report and exits when the report is complete. The application might not run again then for a month. Suitable Azure Red Hat OpenShift objects for these types of applications include Jobs and CronJob objects.
Required to be highly available. If your application requires high availability, then you want to size your deployment to have more than one instance. A Deployment or DeploymentConfig can incorporate a ReplicaSet for that type of application. With ReplicaSets, Pods run across multiple nodes to make sure the application is always available, even if a worker goes down.
Need to run on every node. Some types of Kubernetes applications are intended to run in the cluster itself on every master or worker node. DNS and monitoring applications are examples of applications that need to run continuously on every node. You can run this type of application as a DaemonSet. You can also run a DaemonSet on a subset of nodes, based on node labels.
Require life-cycle management. When you want to hand off your application so that others can use it, consider creating an Operator. Operators let you build in intelligence, so it can handle things like backups and upgrades automatically. Coupled with the Operator Lifecycle Manager (OLM), cluster managers can expose Operators to selected namespaces so that users in the cluster can run them.
Have identity or numbering requirements. An application might have identity
requirements or numbering requirements. For example, you might be
required to run exactly three instances of the application and to name the
is suitable for this application. StatefulSets are most useful for applications
that require independent storage, such as databases and zookeeper clusters.
The application you write might need supporting components, like a database or a logging component. To fulfill that need, you might be able to obtain the required component from the following Catalogs that are available in the Azure Red Hat OpenShift web console:
OperatorHub, which is available in each Azure Red Hat OpenShift 4 cluster. The OperatorHub makes Operators available from Red Hat, certified Red Hat partners, and community members to the cluster operator. The cluster operator can make those Operators available in all or selected namespaces in the cluster, so developers can launch them and configure them with their applications.
Service Catalog, which offers alternatives to Operators. While deploying Operators is the preferred method of getting packaged applications in Azure Red Hat OpenShift, there are some reasons why you might want to use the Service Catalog to get supporting applications for your own application. You might want to use the Service Catalog if you are an existing Azure Red Hat OpenShift 3 customer and are invested in Service Catalog applications or if you already have a Cloud Foundry environment from which you are interested in consuming brokers from other ecosystems.
Templates, which are useful for a one-off type of application, where the lifecycle of a component is not important after it is installed. A template provides an easy way to get started developing a Kubernetes application with minimal overhead. A template can be a list of resource definitions, which could be deployments, services, routes, or other objects. If you want to change names or resources, you can set these values as parameters in the template. The Template Service Broker Operator is a service broker that you can use to instantiate your own templates. You can also install templates directly from the command line.
You can configure the supporting Operators, Service Catalog applications, and
templates to the specific needs of your development team and then make them
available in the namespaces in which your developers work. Many people add
shared templates to the
openshift namespace because it is accessible from all
Kubernetes manifests let you create a more complete picture of the components
that make up your Kubernetes applications. You write these manifests as YAML
files and deploy them by applying them to the cluster, for example, by running
oc apply command.
At this point, consider ways to automate your container development process. Ideally, you have some sort of CI pipeline that builds the images and pushes them to a registry. In particular, a GitOps pipeline integrates your container development with the Git repositories that you use to store the software that is required to build your applications.
The workflow to this point might look like:
Day 1: You write some YAML. You then run the
oc apply command to apply that
YAML to the cluster and test that it works.
Day 2: You put your YAML container configuration file into your own Git repository. From there, people who want to install that app, or help you improve it, can pull down the YAML and apply it to their cluster to run the app.
Day 3: Consider writing an Operator for your application.
Packaging and deploying your application as an Operator might be preferred if you make your application available for others to run. As noted earlier, Operators add a lifecycle component to your application that acknowledges that the job of running an application is not complete as soon as it is installed.
When you create an application as an Operator, you can build in your own knowledge of how to run and maintain the application. You can build in features for upgrading the application, backing it up, scaling it, or keeping track of its state. If you configure the application correctly, maintenance tasks, like updating the Operator, can happen automatically and invisibly to the Operator’s users.
An example of a useful Operator is one that is set up to automatically back up data at particular times. Having an Operator manage an application’s backup at set times can save a system administrator from remembering to do it.
Any application maintenance that has traditionally been completed manually, like backing up data or rotating certificates, can be completed automatically with an Operator.