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Docker Containerization and Kubernetes Orchestration Guide

mariela profile image Mariela Originally published at tech.forums.softwareag.com on ・16 min read

Using Containers

A container is a lightweight, standalone, executable package of software that includes everything needed to run an application; that is, source code and all dependencies, such as the runtime, system tools, system libraries, and configurations.

Because containers are self-sustained, they ensure that an application is decoupled from any environment specifics. If a container image gets distributed to developers, every one of them will run the exact same application with all its dependencies. When this image gets promoted to a test or production environment, the technology ensures that it is the same piece of software the developers created and tested on their machines. This holds true regardless of whether those environments are in a local data center, a cloud provider, or a hybrid of the two. Since configurations for resources such as databases, identity providers, or systems hosts vary in different environments, configurations are externalized so they can be passed to the container as part of the promotion process.

Unlike VMs, which include their own operating systems and require a hypervisor to run, containers reuse much of the host operating system, include the minimum run time requirements of the application, and do not require a hypervisor. VMs are full-size virtualized computers that run everything a computer runs, while containers run a single application mapped to a single process; you will never encounter two servers running in the same container. (Note: While many processes can run in containers, it is not considered a good practice.)

You can easily spin up container instances from a container image and just as easily bring them down. You can deploy container instances quickly, stack many applications on a host, and run the applications simultaneously. Since container instances are designed to run in large numbers, they do not save their state inside the container. As a result, everything that happens during run time that is not preserved outside of the container (for example, in a database or storage) is not retained.

You can use a remote repository to share your container images with others, or you can configure your own private repository. Like a source code repository, the registry can contain different versions of a container image.

Using Containers with Software AG Products

Software AG uses Docker as its container image creation tooling, but you can use any Open Container Initiative (OCI) compliant tooling. With Docker, you can develop an application in the traditional webMethods way, then package it in a solution image. You can then test this image and promote it to other environments to run as container without any additional code changes.

Product Images

A product image is a default installation of a single runtime, such as a Microservices Runtime, a Universal Messaging server, or an API Gateway. The product image contains the product and its fixes but does not contain any licenses, configurations, or assets. A product image can be compared to a default installation with the latest fixes.

You can create a product image for a Software AG product from the Software AG Installer or from an on-prem installation and out-of-the-box Docker scripts. Alternatively, you can use pre-built container images provided on DockerHub by Software AG.

create Docker image 2

Create a Product Image from Software AG Installer (10.7 and Later)

You can create a product image with fixes using the Software AG Installer that is released with webMethods 10.7.

When you want to update to a new fix level or upgrade to a new Software AG release, you will need to create a new product image. You can fully automate this process.

At the time webMethods 10.7 was released, you could use the installer to create a container image of Microservices Runtime with selected layered products or a container image of API Gateway. Support for other Software AG products will be added gradually.

Create a Product Image from an On-Prem Installation (10.5 and Earlier)

You can create a product image with fixes from an on-prem product installation and the out-of-the-box Docker scripts. Follow these steps:

  1. Install Docker on the target machine.
  2. Use the Software AG Installer to install a product such as Microservices Runtime on the machine.
  3. Trigger the Docker creation scripts that come with the product to create a product image.
  4. Use the Docker CLI to push the image to a container repository.

When you want to update to a new fix level or upgrade to a new Software AG release, you will need to create a new product image.

Additional Information

Use a Software AG-Provided Product Images from Docker Hub

Software AG provides product images on its official organization in Docker Hub. You can download and use these images.

Each image includes a single product. For Microservices Runtime, the image does not include any layered products.

Some product images include fixes. Such images are labeled with a minor release number (for example, Microservices Runtime 10.3.4).

Creation of Solution Images - Deployment

A solution image is the result of a CI/CD build process based on a previously defined product image (that is, product installation and fixes) plus developed assets. This creates a working piece of software that can go through unit and integration tests and eventually be deployed into production.

You can create solution images using the file copy functionality of the Docker multi-stage build process. Below is an example for Microservices Runtime.

  • Inject package assets into the solution image by copying the packages to the IntegrationServer/packages directory. When the container starts, it will load the packages onto Microservices Runtime.
  • Inject configurations by copying the configuration.properties template into the solution image. Define the configurations for one environment, such as the dev environment. When you promote to a different environment, such as test or prod, you will be able to change the configurations in the solution image similarly to the way you use webMethods Deployer’s variable substitution to change configurations in on-prem deployment (see the Container Lifecycle section, below).
  • If there are configurations with external dependencies, like keystore or truststore certificates, or SAP or SQL drivers, you must copy them into the solution image, so they will be available to the container.

Rebuild your solution images after you or Software AG creates a new product image or whenever you produce new assets. The latter might be as often as daily in active development when using a properly set up CI.

Important! Do not start a container, then use a runtime deployment tool such as webMethod Deployer to deploy the container, and then commit back to an image. Although possible, such a procedure is against best practice.

Additional Information

Container Life-cycle Supported by Software AG

If you already use a Software AG Local Development Environment and a version control system such as Git to store your assets and configuration, you must not adapt your development setup when moving towards container deployment.

However, you will need to set up a CI process that creates an immutable solution image out of the product image, the licenses, the latest configurations, and your assets.

The Software AG asset and container life cycle is shown below.

create Docker image

The CD promotion process differs from promotion in on-prem environments. In traditional on-prem development, only the source code is promoted, using webMethods Deployer. In container development, the entire solution container, including the dependencies needed for the application, is promoted via container registry. When a new version of the solution is created, it results in a new container image that is pushed to the container registry. You can then reference the new container registry when you deploy to an orchestration environment like Kubernetes, Open Shift, or Docker Swarm.

Different environments (for example, dev, test, prod) typically require different configurations for resources such as databases, identity providers, licenses, and so on. In containerization this challenge is handled using these approaches:

  • The configurations refer to environment variables, which are set appropriately for each environment.
  • The configurations are passed to the container in a runtime configuration file, and the file configures the container on startup. This approach is similar to the variable substitution approach used in webMethods Deployer. For Microservices Runtime, starting with 10.5 plus latest fix, the configuration file can both change existing configurations in the container and create new configurations.

Orchestration

Orchestration is not a new concept for webMethods. webMethods on-premise installations typically orchestrate multiple products to build a solution. For example:

  • A standalone Integration Server working with a database component.
  • Multiple Integration Servers clustered over a Terracotta service array and a database.
  • A BPMS solution consisting of an Integration Server layered with Process Engine and Monitor, connected to a Universal Messaging and a My webMethods Server with Task Engine, all storing runtime data in a Process Audit database component.

webMethods has been leveraging the power of orchestration for decades, because a single product rarely can cover a use case on its own.

Using Kubernetes to Orchestrate Containers

You can combine individual solution containers to build a solution by orchestrating those in the same way on-premise installations are orchestrated and wired like:

  • Integration Servers or Microservices Runtimes that use messaging need to be configured to access the Universal Messaging service.
  • A Universal Messaging container that requires persistence needs to be configured to use a persistent volume.
  • Integrations Servers or Microservices Runtimes that leverage an internal database need to be configured to connect to a prepared database.

Software AG uses the open-source platform Kubernetes to orchestrate container deployments. With Kubernetes, you can deploy, monitor, scale, and upgrade complete solutions more easily than you can using on-premise installations because you are orchestrating containers rather than physical machines or VMs. Below are some of the key strengths of container orchestration.

Feature Description
Storage orchestration Kubernetes can automatically mount the storage system of your choice, whether from local storage; a public cloud provider such as GCP or AWS; or a network storage system such as NFS, iSCSI, Gluster, Ceph, Cinder, or Flocker.
Service discovery and load balancing Kubernetes gives Pods their own IP addresses and a single DNS name for a set of Pods, and can load-balance across them. You don’t have to modify your application to use an unfamiliar service discovery mechanism.
Self-healing Kubernetes restarts containers that fail, replaces and reschedules containers when nodes die, kills containers that don’t respond to your user-defined health check, and only advertises containers to clients when they are ready to serve.
Secret and configuration management With Kubernetes, you can deploy and update secrets and application configurations without rebuilding your image and without exposing secrets in your stack configuration.
Horizontal scaling With Kubernetes, you can scale your application up and down using a simple command or UI, or you can configure Kubernetes to scale your application automatically based on CPU usage.
Automated roll-outs and rollbacks Kubernetes progressively rolls out changes to your application or its configuration, while monitoring application health to ensure it doesn’t kill all your instances at the same time. If something goes wrong, Kubernetes rolls back the change for you. This enables you to take advantage of a growing ecosystem of deployment solutions.

Kubernetes Flavors

Hyperscalers such as Amazon, Microsoft, and Google have customized Kubernetes as part of their serverless offerings (for example, Amazon EKS, Azure AKS, and Google GKE). Software AG products that are certified for Kubernetes can run on all flavors certified by the Cloud Native Computing Foundation. However, many of those, such as AKS and EKS, offer custom services like databases, specific network storage, secrets managers, and identity providers. To determine whether a Software AG product can run with specific service components, see System Requirements for Software AG Products .

Additional Information

Deploying a Solution in Kubernetes

A full solution deployed in an orchestrated environment will consist of a set of solution images made available in a container image repository. There are several ways to deploy these images:

  • Manually deploy each container by pulling it from a container registry via the kubectl CLI. Provide configuration parameters on the command line. Manually define the replica sets and create services on top of those deployments if they are going to expose internal or external network interfaces. Repeat for every solution image you want to deploy.
  • Use Kubernetes manifest files that describe the deployment, networking, scaling and configuration and apply it via the kubectl CLI.
  • Install and use the Helm package manager that will deploy and configure multiple images with their configuration onto Kubernetes. Software AG currently provides a limited set of scenarios as Helm charts on GitHub. Download the charts and modify them (for example, to point to custom solution images), and then deploy them into the orchestration environment.

Additional Information

Observability of the Kubernetes Infrastructure

To monitor the health of the Kubernetes cluster itself, or the pods and services that run your application, you can use either the kubectl CLI, the standard Kubernetes dashboard application, or some of the custom UIs delivered with specific Kubernetes flavors. Those built-in mechanisms will report the status of the components that make up your application (for example, ready, started, failed).

Additional Information

Monitoring a Solution in Kubernetes

Every Software AG container provides a REST API that returns metrics for the system at the current moment. The metrics provided by the products are quite similar to the ones provided for Software AG’s Optimize for Infrastructure product. These metrics are “pulled” from the containers by Prometheus and aggregated. Prometheus should be installed in the Kubernetes cluster as an application and set up to pull the data from the solution containers based on the Kubernetes service discovery mechanism. The aggregated data will be stored on a non-volatile storage and can be displayed on a custom Grafana dashboard. Prometheus can also send alerts, based on the rules over the collected metrics. This can help administrators proactively perform actions on the application. The following figure gives a good overview of the monitoring architecture of an orchestrated solution.

Prometheus Architecture

Additional Information

Logging

Logging in containers and orchestration environments differs significantly from the on-premise world. This is due to the ephemeral nature of containers and their scaling capabilities. Logging to a file is not useful because when the container restarts, it just resets the state of the file system and any logging information would be lost, along with the ability to troubleshoot any problem that was present. The scalability of the container means that there isn’t a fixed number of runtimes at a given time, so getting their logs one by one is not a workable solution.

The solution to this is to produce logs only as event streams. The logs from every container should be written to its std.out and std.err streams. This gives other services in an orchestration environment the ability to collect and aggregate those streams for analysis. The pattern is emphasized as factor 11 Logs of the The Twelve Factors App methodology.

The service stack that enables the pattern typically comprises three components: ElasticSearch for persistence, Fluentd to collect the log streams, and Kibana to display and analyze them. This is commonly referred as EFK. Sometimes the stack uses Fluent Bit, which has similar functionality to Fluend but is lighter in size and feature set. A variation may also use Logstash for the log aggregation (ELK). The following diagram gives an overview of the EFK architecture.

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To deploy the stack, all components must be downloaded and running in the Kubernetes server. By default, the stack will gather and aggregate all log streams from all solutions. The UI layer, Kibana, can query the logs based on patterns. As the log streams are queried from multiple runtimes and from multiple components, the usage of correlation IDs is highly recommended for troubleshooting.

Additional Information

Backup and Recovery

Similar to the other capabilities discussed above for the orchestration environment, backup and recovery are covered by third-party tools. Those should be installed in the environment to give access to all pods, services and configurations. Possible solutions include Portworx, Velero, OpenEBS, and Rancher Longhorn.

Additional Information

High Availability

High availability is something that comes out of the box with Kubernetes. Every runtime aiming to run in K8s has implemented HTTP endpoints for liveness and readiness. If either does return 200 OK, K8S will automatically restart it and make sure it runs again. The same will happen if there is a Kubernetes node failure. Image the hardware, where your solution was currently running fails; Kubernetes will automatically recognize that one of its nodes are down and will start the containers on different nodes, to make sure they are operational in minimal time.

If the downtime in this scenario does not guarantee the needed SLA, the deployment can be scaled behind a load balancer with more instances. However, this should be allowed by the software itself; for example, Universal Messaging does not allow this in some of its use cases, such as when it is used a JMS provider.

Additional Information

Upgrade

Upgrading a solution in an orchestrated environment is related to updating the underlying images. The images might be updated in the following cases:

  • The assets need to be updated (for example, a new Integration Server package, a new Universal Messaging channel or queue).
  • A new fix was released for a product.
  • A new major release of the product has been deployed.

In any of those cases, a solution image has to be produced via the CI/CD container life cycle described above. The resulting new solution image has to be stored in a container registry that is accessible from the orchestration environment.

When deploying a new solution image to an orchestrated environment, one must consider all dependencies:

  • Does the new fix require a fix in another component (for example, an update in the database schema or messaging provider).
  • Does the new product version work with the other components in the solution (for example, a product database, Integration Server - Universal Messaging version, or My webMethods Server version).

If the dependencies are satisfied, you can deploy the new image. In certain cases, this deployment will have zero downtime

  • Upgrade of stateless application with many replicas
  • A typical Microservices Runtime microservice application scenario without a database. The container instances will be gradually replaced by Kubernetes and the requests towards those will be routed to all running pods.
  • A Microservices Runtime scenario with messaging. The Microservices Runtimes can be updated one by one and continue to communicate to Universal Messaging.

An upgrade of a stateful application will require downtime. Known limitations are:

  • The database has to be separately migrated. Old and new instances of Integration Server and My webMethods Server currently can’t work together against the same version of the db.
  • The Universal Messaging storage (data directory) can’t be use simultaneously from different instances as it will become corrupted.

Additional Information

Terminology

Term Definition
Base image Operating system for the container, as well as basic tools such as compilers. Can be shared by multiple container images.
CI/CD Continuous integration/ continuous delivery. CI (Continuous Integration) is the process of continuously integrating developed assets into a solution while ensuring their quality. CD (Continuous Delivery) is the process of automatically promoting qualitative assets up to production.
Container Lightweight, standalone, executable package of software that includes everything needed to run an application: the source code and all dependencies, such as the runtime, system tools, system libraries, and settings. Includes a writable layer.
Container image Immutable blueprint for a container runtime.
Container instance Runtime instance of a container.
CR Container registry used to version container images across users and systems. The same image might have multiple versions stored in the CR.
Product image Default installation of a single runtime, such as a Microservices Runtime, a Universal Messaging server, or an API Gateway. The product image contains the product and its fixes but does not contain any licenses, configurations, or assets. A product image can be compared to a default installation with the latest fixes applied.
Solution image Product image to which you have added a layer of licenses, configurations, and assets.

Product Support for Containers/Kubernetes Deployments

Containerization

Product Can run in container Produce Docker image via Software AG Installer 10.7 or later Configurable via environment vars or config template Logging on std.out for single log support fluentd/fluentbit Prometheus monitoring State management
ActiveTransfer No No No No No Database
API Gateway Yes Yes Yes Yes Yes Elastic Search
API Portal No No No No No No
BPMS Yes No Yes Yes No Database
webMethods Broker No No No No No n/a
Integration Server (with Microservices licens) Yes Yes Yes Yes Yes Database when stateful
Microservices Runtime Yes Yes Yes Yes Yes Database when stateful
My webMethods Server Yes No Yes No Yes Database
Optimize for Process No No No No No n/a
Optimize for Infrastructure No No No No No n/a
Rules Yes No Yes No No Database
Terracotta Yes No Yes Yes Yes Storage
Trading Networks No No No No No Database
Universal Messaging Yes No Yes Yes Yes Storage
SAP Adapter Yes (on Microservices Runtime) Yes partial - connections only No No n/a
JDBC Adapter Yes (on Microservices Runtime) Yes partial - connections only No No n/a
IBM WebSphere MQ Adapter Yes (on Microservices Runtime) Yes partial - connections only No No n/a
MSMQ Adapter Yes (on Microservices Runtime) Yes partial - connections only No No n/a
Kafka Adapter Yes (on Microservices Runtime) Yes partial - connections only No No n/a
AS/400 Adapter Yes (on Microservices Runtime) Yes partial - connections only No No n/a

Kubernetes Support

See Orchestration, above, for information about Kubernetes flavors.

Product Run in Kubernetes Helm 3 chart for deployment to Kubernetes High availability Scaling Upgrade strategy Minimum Kubernetes version
ActiveTransfer No No No No n/a
API Gateway Yes Yes Yes Yes Rolling (for fixes only) Green-blue for major versions
API Portal No No n/a n/a n/a
BPMS No No No No n/a
webMethods Broker No No No No n/a
Microservices Runtime Yes Yes Yes Yes Rolling for stateless With possible downtime when using a db
My webMethods Server No No No No With downtime when using a db
Rules No No No No n/a
Terracotta Yes Yes Yes No With downtime for stateful scenarios
Trading Networks No No No No n/a
Universal Messaging Yes Yes Yes No for stateful Yes for stateless scenarios Green-blue for stateful scenarios Rolling for stateless

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