labels: promotion-group: <application_name>
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Application promotion means moving an application through various runtime environments, typically with an increasing level of maturity. For example, an application might start out in a development environment, then be promoted to a stage environment for further testing, before finally being promoted into a production environment. As changes are introduced in the application, again the changes will start in development and be promoted through stage and production.
The "application" today is more than just the source code written in Java, Perl, Python, etc. It is more now than the static web content, the integration scripts, or the associated configuration for the language specific runtimes for the application. It is more than the application specific archives consumed by those language specific runtimes.
In the context of Azure Red Hat OpenShift and its combined foundation of Kubernetes and Docker, additional application artifacts include:
Container images with their rich set of metadata and associated tooling.
Environment variables that are injected into containers for application use.
API objects (also known as resource definitions; see Core Concepts) of Azure Red Hat OpenShift, which:
are injected into containers for application use.
dictate how Azure Red Hat OpenShift manages containers and pods.
In examining how to promote applications in Azure Red Hat OpenShift, this topic will:
Elaborate on these new artifacts introduced to the application definition.
Describe how you can demarcate the different environments for your application promotion pipeline.
Discuss methodologies and tools for managing these new artifacts.
Provide examples that apply the various concepts, constructs, methodologies, and tools to application promotion.
With regard to Azure Red Hat OpenShift and Kubernetes resource definitions (the items newly introduced to the application inventory), there are a couple of key design points for these API objects that are relevant to revisit when considering the topic of application promotion.
First, as highlighted throughout Azure Red Hat OpenShift documentation, every API object can be expressed via either JSON or YAML, making it easy to manage these resource definitions via traditional source control and scripting.
Also, the API objects are designed such that there are portions of the object which specify the desired state of the system, and other portions which reflect the status or current state of the system. This can be thought of as inputs and outputs. The input portions, when expressed in JSON or YAML, in particular are items that fit naturally as source control managed (SCM) artifacts.
Remember, the input or specification portions of the API objects can be totally static or dynamic in the sense that variable substitution via template processing is possible on instantiation.
The result of these points with respect to API objects is that with their expression as JSON or YAML files, you can treat the configuration of the application as code.
Conceivably, almost any of the API objects may be considered an application artifact by your organization. Listed below are the objects most commonly associated with deploying and managing an application:
This is a special case resource in the context of application
promotion. While a
BuildConfig is certainly a part of the application,
especially from a developer’s perspective, typically the
BuildConfig is not
promoted through the pipeline. It produces the
Image that is promoted (along
with other items) through the pipeline.
In terms of application promotion,
Templates can serve as the
starting point for setting up resources in a given staging environment,
especially with the parameterization capabilities. Additional post-instantiation
modifications are very conceivable though when applications move through a
promotion pipeline. See
Scenarios and Examples for more
These are the most typical resources that differ stage to stage in the
application promotion pipeline, as tests against different stages of an
application access that application via its
Route. Also, remember that you have
options with regard to manual specification or auto-generation of host names, as
well as the HTTP-level security of the
If reasons exist to avoid
Routes at given application
promotion stages (perhaps for simplicity’s sake for individual developers at
early stages), an application can be accessed via the
Cluster IP address and
port. If used, some management of the address and port between stages could be
Certain application-level services (e.g., database instances in many
enterprises) may not be managed by Azure Red Hat OpenShift. If so, then creating those
Endpoints yourself, along with the necessary modifications to the associated
Service (omitting the selector field on the
Service) are activities that are
either duplicated or shared between stages (based on how you delineate your
The sensitive information encapsulated by
Secrets are shared between
staging environments when the corresponding entity (either a
by Azure Red Hat OpenShift or an external service managed outside of Azure Red Hat OpenShift)
the information pertains to is shared. If there are different versions of the
said entity in different stages of your application promotion pipeline, it may
be necessary to maintain a distinct
Secret in each stage of the pipeline or to
make modifications to it as it traverses through the pipeline. Also, take care
that if you are storing the
Secret as JSON or YAML in an SCM, some form of
encryption to protect the sensitive information may be warranted.
This object is the primary resource for defining and scoping the environment for a given application promotion pipeline stage; it controls how your application starts up. While there are aspects of it that will be common across all the different stage, undoubtedly there will be modifications to this object as it progresses through your application promotion pipeline to reflect differences in the environments for each stage, or changes in behavior of the system to facilitate testing of the different scenarios your application must support.
Detailed in the Images and Image Streams sections, these objects are central to the Azure Red Hat OpenShift additions around managing container images.
Management of permissions to other API
objects within Azure Red Hat OpenShift, as well as the external services, are intrinsic
to managing your application. Similar to
RoleBindings objects can vary in how they are shared between the different
stages of your application promotion pipeline based on your needs to share or
isolate those different environments.
Relevant to stateful services like databases, how much these are shared between your different application promotion stages directly correlates to how your organization shares or isolates the copies of your application data.
A useful decoupling of
Pod configuration from the
(think of an environment variable style configuration), these can either be
shared by the various staging environments when consistent
Pod behavior is
desired. They can also be modified between stages to alter
(usually as different aspects of the application are vetted at different
As noted earlier, container images are now artifacts of your application. In fact, of the new applications artifacts, images and the management of images are the key pieces with respect to application promotion. In some cases, an image might encapsulate the entirety of your application, and the application promotion flow consists solely of managing the image.
Images are not typically managed in a SCM system, just as application binaries were not in previous systems. However, just as with binaries, installable artifacts and corresponding repositories (such as RPMs, RPM repositories, or Nexus) arose with similar semantics to SCMs. Therefore, constructs and terminology around image management that are similar to SCMs have emerged:
Image registry == SCM server
Image repository == SCM repository
As images reside in registries, application promotion is concerned with ensuring the appropriate image exists in a registry that can be accessed from the environment that needs to run the application represented by that image.
Rather than reference images directly, application definitions typically abstract the reference into an image stream. This means the image stream will be another API object that makes up the application components. For more details on image streams, see Core Concepts.
A deployment environment, in this context, describes a distinct space for an application to run during a particular stage of a CI/CD pipeline. Typical environments include development, test, stage, and production, for example. The boundaries of an environment can be defined in different ways, such as:
Via labels and unique naming within a single project.
Via distinct projects within a cluster.
Via distinct clusters.
And it is conceivable that your organization leverages all three.
Typically, you will consider the following heuristics in how you structure the deployment environments:
How much resource sharing the various stages of your promotion flow allow
How much isolation the various stages of your promotion flow require
How centrally located (or geographically dispersed) the various stages of your promotion flow are
Also, some important reminders on how Azure Red Hat OpenShift clusters and projects relate to image registries:
Multiple project in the same cluster can access the same image streams.
Multiple clusters can access the same external registries.
Clusters can only share a registry if the Azure Red Hat OpenShift internal image registry is exposed via a route.
Fundamentally, application promotion is a process of moving the aforementioned application components from one environment to another. The following subsections outline tools that can be used to move the various components by hand, before advancing to discuss holistic solutions for automating application promotion.
There are a number of insertion points available during both the build and
deployment processes. They are defined within
Therefore, it is possible to use these hooks to perform component management operations that effectively move applications between environments, for example by performing an image tag operation from within a hook. However, the various hook points are best suited to managing an application’s lifecycle within a given environment (for example, using them to perform database schema migrations when a new version of the application is deployed), rather than to move application components between environments.
Resources, as defined in one environment, will be exported as JSON or YAML file
content in preparation for importing it into a new environment. Therefore, the
expression of API objects as JSON or YAML serves as the unit of work as you
promote API objects through your application pipeline. The
oc CLI is used to
export and import this content.
While not required for promotion flows with Azure Red Hat OpenShift, with the JSON or YAML stored in files, you can consider storing and retrieving the content from a SCM system. This allows you to leverage the versioning related capabilities of the SCM, including the creation of branches, and the assignment of and query on various labels or tags associated to versions.
API object specifications should be captured with
oc get --export. This operation
removes environment specific data from the object definitions (e.g., current
namespace or assigned IP addresses), allowing them to be recreated in different
oc get operations, which output an unfiltered state of
oc label, which allows for adding, modifying, or removing labels on API
objects, can prove useful as you organize the set of object collected for
promotion flows, because labels allow for selection and management of groups of
pods in a single operation. This makes it easier to export the correct set of
objects and, because the labels will carry forward when the objects are created
in a new environment, they also make for easier management of the application
components in each environment.
API objects often contain references such as a
Similarly, API objects such as a
The first time an application is being introduced into a new environment, it is
sufficient to take the JSON or YAML expressing the specifications of your API
objects and run
oc create to create them in the appropriate environment. When
oc create, keep the
--save-config option in mind. Saving configuration
elements on the object in its annotation list facilitates the later use of
apply to modify the object.
After the various staging environments are initially established, as promotion cycles commence and the application moves from stage to stage, the updates to your application can include modification of the API objects that are part of the application. Changes in these API objects are conceivable since they represent the configuration for the Azure Red Hat OpenShift system. Motivations for such changes include:
Accounting for environmental differences between staging environments.
Verifying various scenarios your application supports.
Transfer of the API objects to the next stage’s environment is accomplished via
use of the
oc CLI. While a rich set of
oc commands which modify API objects
exist, this topic focuses on
oc apply, which computes and applies differences
Specifically, you can view
oc apply as a three-way merge that takes in files or stdin as the input along with an existing object definition. It performs a three-way merge between:
the input into the command,
the current version of the object, and
the most recent user specified object definition stored as an annotation in the current object.
The existing object is then updated with the result.
If further customization of the API objects is necessary, as in the case when
the objects are not expected to be identical between the source and target
oc commands such as
oc set can be used to modify the object
after applying the latest object definitions from the upstream environment.
Some specific usages are cited in Scenarios and Examples.
Images in Azure Red Hat OpenShift are managed via a series of API objects as well. However, managing images are so central to application promotion that discussion of the tools and API objects most directly tied to images warrant separate discussion. Both manual and automated forms exist to assist you in managing image promotion (the propagation of images through your pipeline).
For all the detailed caveats around managing images, refer to the Managing Images topic.
When your staging environments share the same Azure Red Hat OpenShift registry, for example if they are all on the same Azure Red Hat OpenShift cluster, there are two operations that are the basic means of moving your images between the stages of your application promotion pipeline:
First, analogous to
docker tag and
git tag, the
oc tag command allows you
to update an Azure Red Hat OpenShift image stream with a reference to a specific image.
It also allows you to copy references to specific versions of an image from one
image stream to another, even across different projects in a cluster.
oc import-image serves as a bridge between external registries and
image streams. It imports the metadata for a given image from the registry and
stores it into the image stream as an
stream tag. Various
DeploymentConfigs in your project can
reference those specific images.
More advanced usage occurs when your staging environments leverage different Azure Red Hat OpenShift registries.
docker command in conjunction which obtaining the Azure Red Hat OpenShift
access token to supply into your
docker login command.
After being logged into the Azure Red Hat OpenShift registry, use
docker push to transfer the image.
After the image is available in the registry of the next environment of your
oc tag as needed to populate any image streams.
Whether changing the underlying application image or the API objects that
configure the application, a deployment is typically necessary to pick up the
promoted changes. If the images for your application change (for example, due to
oc tag operation or a
docker push as part of promoting an image from an
ImageChangeTriggers on your
trigger the new deployment. Similarly, if the
DeploymentConfig API object
itself is being changed, a
ConfigChangeTrigger can initiate a deployment when
the API object is updated by the promotion step (for example,
oc commands that facilitate manual deployment include:
oc rollout: The new approach to manage deployments, including pause and resume semantics and richer features around managing history.
oc rollback: Allows for reversion to a previous deployment; in the promotion scenario, if testing of a new version encounters issues, confirming it still works with the previous version could be warranted.
After you understand the components of your application that need to be moved between environments when promoting it and the steps required to move the components, you can start to orchestrate and automate the workflow. Azure Red Hat OpenShift provides a Jenkins image and plug-ins to help with this process.
The Azure Red Hat OpenShift Jenkins image is detailed in Using Images, including the set of Azure Red Hat OpenShift-centric plug-ins that facilitate the integration of Jenkins, and Jenkins Pipelines. Also, the Pipeline build strategy facilitates the integration between Jenkins Pipelines and Azure Red Hat OpenShift. All of these focus on enabling various aspects of CI/CD, including application promotion.
When moving beyond manual execution of application promotion steps, the Jenkins-related features provided by Azure Red Hat OpenShift should be kept in mind:
Azure Red Hat OpenShift provides a Jenkins image that is heavily customized to greatly ease deployment in an Azure Red Hat OpenShift cluster.
The Jenkins image contains the OpenShift Pipeline plug-in, which provides building blocks for implementing promotion workflows. These building blocks include the triggering of Jenkins jobs as image streams change, as well as the triggering of builds and deployments within those jobs.
BuildConfigs employing the Azure Red Hat OpenShift Jenkins Pipeline build strategy
enable execution of Jenkinsfile-based Jenkins Pipeline jobs. Pipeline jobs are
the strategic direction within Jenkins for complex promotion flows and can
leverage the steps provided by the OpenShift Pipeline Plug-in.
API objects can reference other objects. A common use for this is to have a
DeploymentConfig that references an image stream, but other reference
relationships may also exist.
When copying an API object from one environment to another, it is critical that all references can still be resolved in the target environment. There are a few reference scenarios to consider:
The reference is "local" to the project. In this case, the referenced object resides in the same project as the object that references it. Typically the correct thing to do is to ensure that you copy the referenced object into the target environment in the same project as the object referencing it.
The reference is to an object in another project. This is typical when an image stream in a shared project is used by multiple application projects. In this case, when copying the referencing object to the new environment, you must update the reference as needed so it can be resolved in the target environment. That may mean:
Changing the project the reference points to, if the shared project has a different name in the target environment.
Moving the referenced object from the shared project into the local project in the target environment and updating the reference to point to the local project when moving the primary object into the target environment.
Some other combination of copying the referenced object into the target environment and updating references to it.
In general, the guidance is to consider objects referenced by the objects being copied to a new environment and ensure the references are resolvable in the target environment. If not, take appropriate action to fix the references and make the referenced objects available in the target environment.
Image streams point to image repositories to indicate the source of the image they represent. When an image stream is moved from one environment to another, it is important to consider whether the registry and repository reference should also change:
If different image registries are used to assert isolation between a test environment and a production environment.
If different image repositories are used to separate test and production-ready images.
If either of these are the case, the image stream must be modified when it is copied from the source environment to the target environment so that it resolves to the correct image. This is in addition to performing the steps described in Scenarios and Examples to copy the image from one registry and repository to another.
At this point, the following have been defined:
New application artifacts that make up a deployed application.
Correlation of application promotion activities to tools and concepts provided by Azure Red Hat OpenShift.
Integration between Azure Red Hat OpenShift and the CI/CD pipeline engine Jenkins.
Putting together examples of application promotion flows within Azure Red Hat OpenShift is the final step for this topic.
Having defined the new application artifact components introduced by the Docker, Kubernetes, and Azure Red Hat OpenShift ecosystems, this section covers how to promote those components between environments using the mechanisms and tools provided by Azure Red Hat OpenShift.
Of the components making up an application, the image is the primary artifact of note. Taking that premise and extending it to application promotion, the core, fundamental application promotion pattern is image promotion, where the unit of work is the image. The vast majority of application promotion scenarios entails management and propagation of the image through the promotion pipeline.
Simpler scenarios solely deal with managing and propagating the image through the pipeline. As the promotion scenarios broaden in scope, the other application artifacts, most notably the API objects, are included in the inventory of items managed and propagated through the pipeline.
This topic lays out some specific examples around promoting images as well as API objects, using both manual and automated approaches. But first, note the following on setting up the environment(s) for your application promotion pipeline.
After you have completed development of the initial revision of your application, the next logical step is to package up the contents of the application so that you can transfer to the subsequent staging environments of your promotion pipeline.
First, group all the API objects you view as transferable and apply a common
label to them:
labels: promotion-group: <application_name>
As previously described, the
oc label command facilitates the management of
labels with your various API objects.
If you initially define your API objects in a Azure Red Hat OpenShift template, you can easily ensure all related objects have the common label you will use to query on when exporting in preparation for a promotion.
You can leverage that label on subsequent queries. For example, consider the
following set of
oc command invocations that would then achieve the transfer
of your application’s API objects:
$ oc login <source_environment> $ oc project <source_project> $ oc get -o yaml --export dc,is,svc,route,secret,sa -l promotion-group=<application_name> > export.yaml $ oc login <target_environment> $ oc new-project <target_project> (1) $ oc create -f export.yaml
You must also get any tokens necessary to operate against each registry used in the different staging environments in your promotion pipeline. For each environment:
Log in to the environment:
$ oc login <each_environment_with_a_unique_registry>
Get the access token with:
$ oc whoami -t
Copy and paste the token value for later use.
After the initial setup of the different staging environments for your pipeline, a set of repeatable steps to validate each iteration of your application through the promotion pipeline can commence. These basic steps are taken each time the image or API objects in the source environment are changed:
Move updated images → Move updated API objects → Apply environment specific customizations
Typically, the first step is promoting any updates to the image(s) associated with your application to the next stage in the pipeline. As noted above, the key differentiator in promoting images is whether the Azure Red Hat OpenShift registry is shared or not between staging environments.
If the registry is shared, simply leverage
$ oc tag <project_for_stage_N>/<imagestream_name_for_stage_N>:<tag_for_stage_N> <project_for_stage_N+1>/<imagestream_name_for_stage_N+1>:<tag_for_stage_N+1>
If the registry is not shared, you can leverage the access tokens for each of your promotion pipeline registries as you log in to both the source and destination registries, pulling, tagging, and pushing your application images accordingly:
Log in to the source environment registry:
$ docker login -u <username> -e <any_email_address> -p <token_value> <src_env_registry_ip>:<port>
Pull your application’s image:
$ docker pull <src_env_registry_ip>:<port>/<namespace>/<image name>:<tag>
Tag your application’s image to the destination registry’s location, updating namespace, name, and tag as needed to conform to the destination staging environment:
$ docker tag <src_env_registry_ip>:<port>/<namespace>/<image name>:<tag> <dest_env_registry_ip>:<port>/<namespace>/<image name>:<tag>
Log in to the destination staging environment registry:
$ docker login -u <username> -e <any_email_address> -p <token_value> <dest_env_registry_ip>:<port>
Push the image to its destination:
$ docker push <dest_env_registry_ip>:<port>/<namespace>/<image name>:<tag>
To automatically import new versions of an image from an external registry, the
Next, there are the cases where the evolution of your application necessitates fundamental changes to your API objects or additions and deletions from the set of API objects that make up the application. When such evolution in your application’s API objects occurs, the Azure Red Hat OpenShift CLI provides a broad range of options to transfer to changes from one staging environment to the next.
Start in the same fashion as you did when you initially set up your promotion pipeline:
$ oc login <source_environment> $ oc project <source_project> $ oc get -o yaml --export dc,is,svc,route,secret,sa -l promotion-group=<application_name> > export.yaml $ oc login <target_environment> $ oc <target_project>
Rather than simply creating the resources in the new environment, update them. You can do this a few different ways:
The more conservative approach is to leverage
oc apply and merge the new
changes to each API object in the target environment. In doing so, you can
--dry-run=true option and examine the resulting objects prior to actually
changing the objects:
$ oc apply -f export.yaml --dry-run=true
If satisfied, actually run the
$ oc apply -f export.yaml
apply command optionally takes additional arguments that help with more
complicated scenarios. See
oc apply --help for more details.
Alternatively, the simpler but more aggressive approach is to leverage
replace. There is no dry run with this update and replace. In the most basic
form, this involves executing:
$ oc replace -f export.yaml
replace optionally takes additional arguments for more
sophisticated behavior. See
oc replace --help for more details.
The previous steps automatically handle new API objects that were introduced,
but if API objects were deleted from the source environment, they must be
manually deleted from the target environment using
Tuning of the environment variables cited on any of the API objects may be
necessary as the desired values for those may differ between staging
environments. For this, use
oc set env:
$ oc set env <api_object_type>/<api_object_ID> <env_var_name>=<env_var_value>
Finally, trigger a new deployment of the updated application using the
rollout command or one of the other mechanisms discussed in the
Deployments section above.
The OpenShift Sample job defined in the Jenkins Docker Image for Azure Red Hat OpenShift is an example of image promotion within Azure Red Hat OpenShift within the constructs of Jenkins. Setup for this sample is located in the OpenShift Origin source repository.
This sample includes:
Use of Jenkins as the CI/CD engine.
Use of the OpenShift Pipeline plug-in for Jenkins. This plug-in provides a
subset of the functionality provided by the
oc CLI for Azure Red Hat OpenShift
packaged as Jenkins Freestyle and DSL Job steps. Note that the
oc binary is
also included in the Jenkins Docker Image for Azure Red Hat OpenShift, and can also be
used to interact with Azure Red Hat OpenShift in Jenkins jobs.
The Azure Red Hat OpenShift-provided templates for Jenkins. There is a template for both ephemeral and persistent storage.
A sample application: defined in the
Origin source repository, this application leverages
BuildConfigs, and separate
Services corresponding to different stages in the
The following examines the various pieces of the OpenShift Sample job in more detail:
The first step is the equivalent of an
oc scale dc frontend --replicas=0
call. This step is intended to bring down any previous versions of the
application image that may be running.
The second step is the equivalent of an
oc start-build frontend call.
The third step is the equivalent of an
oc rollout latest dc/frontend call.
The fourth step is the "test" for this sample. It ensures that the associated service for this application is in fact accessible from a network perspective. Under the covers, a socket connection is attempted against the IP address and port associated with the Azure Red Hat OpenShift service. Of course, additional tests can be added (if not via OpenShift Pipepline plug-in steps, then via use of the Jenkins Shell step to leverage OS-level commands and scripts to test your application).
The fifth step commences under that assumption that the testing of your application
passed and hence intends to mark the image as "ready". In this step, a new
prod tag is created for the application image off of the latest image. With
DeploymentConfig having an
defined for that tag, the corresponding "production" deployment is launched.
The sixth and last step is a verification step, where the plug-in confirms that Azure Red Hat OpenShift launched the desired number of replicas for the "production" deployment.