Products

Customizing an OpenShift Ansible Playbook Bundle

Today I want to talk about Ansible Service Broker and Ansible Playbook Bundle. These components are relatively new in the Red Hat OpenShift ecosystem, but they are now fully supported features available in the Service Catalog component of OpenShift 3.9.

Before getting deep into the technology, I want to give you some basic information (quoted below from the product documentation) about all the components and their features:

  • Ansible Service Broker is an implementation of the Open Service Broker API that manages applications defined in Ansible Playbook Bundles.
  • Ansible Playbook Bundles (APB) are a method of defining applications via a collection of Ansible Playbooks built into a container with an Ansible runtime with the playbooks corresponding to a type of request specified in the Open Service Broker API specification.
  • Playbooks are Ansible’s configuration, deployment, and orchestration language. They can describe a policy you want your remote systems to enforce, or a set of steps in a general IT process.

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Using Ansible Galaxy Roles in Ansible Playbook Bundles

[In case you aren’t following the OpenShift blog, I’m cross posting my article here because I think it will be of interest to the Red Hat Developer commnity.]

The Open Service Broker API standard aims to standardize how services (cloud, third-party, on-premise, legacy, etc) are delivered to applications running on cloud platforms like OpenShift. This allows applications to consume services the exact same way no matter on which cloud platform they are deployed. The service broker pluggable architecture enables admins to add third-party brokers to the platform in order to make third-party and cloud services available to the application developers directly from the OpenShift service catalog. As an example AWS Service Broker created jointly by Amazon and Red Hat, Azure Service Broker created by Microsoft and Helm Service Broker created by Google to allow consumption of AWS services, Azure services and Helm charts on Kubernetes and OpenShift. Furthermore, admins can create their own brokers in order to make custom services like provisioning an Oracle database on their internal Oracle RAC available to the developers through the service catalog.

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Container Testing in OpenShift with Meta Test Family

Without proper testing, we should not ship any container. We should guarantee that a given service in a container works properly. Meta Test Family (MTF) was designed for this very purpose.

Containers can be tested as “standalone” containers and as “orchestrated” containers. Let’s look at how to test containers with the Red Hat OpenShift environment. This article describes how to do that and what actions are needed.

MTF is a minimalistic library built on the existing Avocado and behave testing frameworks, assisting developers in quickly enabling test automation and requirements. MTF adds basic support and abstraction for testing various module artifact types: RPM-based, Docker images, and more. For detailed information about the framework and how to use it check out the MTF documentation.

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Apache Camel URI completion: easy installation for Eclipse, VS Code, and OpenShift.io

Discoverability and ease of installation of Apache Camel tooling based on the Language Server Protocol has been improved. Manual download and installation of binaries is no longer necessary!  For the Eclipse desktop IDE and the VS Code environment you can now find and install the Camel tooling directly from the marketplaces for each development environment.

Camel Language Server is now also available in Red Hat OpenShift.io!

In this article, I will show you how you can install Camel tooling via the marketplaces for Eclipse and VS Code.  I will also show how to enable Camel tooling in your OpenShift.io workspace.

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Scaling AMQ 7 Brokers with AMQ Interconnect

Red Hat JBoss AMQ Interconnect provides flexible routing of messages between AMQP-enabled endpoints, including clients, brokers, and standalone services. With a single connection to a network of AMQ Interconnect routers, a client can exchange messages with any other endpoint connected to the network.

AMQ Interconnect can create various topologies to manage a high volume of traffic or define an elastic network in front of AMQ 7 brokers. This article shows a sample AMQ Interconnect topology for scaling AMQ 7 brokers easily.

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Signage for the Red Hat Summit at Moscone West in San Francisco

Red Hat Summit: Functions as a Service with OpenWhisk and OpenShift

Serverless computing (often called Functions-as-a-Service, or FaaS) is one of the hottest emerging technologies today. The OpenWhisk project, currently in incubation at Apache, is an open-source implementation of FaaS that lets you create functions that are invoked in response to events. Our own Brendan McAdams gave a presentation and demo that explained the basics of serverless, how the OpenWhisk project works, and how to run OpenWhisk in OpenShift.

Brendan outlined the three properties of a serverless / FaaS platform:

  1. It responds to events by invoking functions
  2. Functions are loaded and executed on demand
  3. Functions can be chained together with triggered events from outside the FaaS platform itself.

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How to Debug Your Node.js Application on OpenShift with Chrome DevTools

Recently, I wrote a post called Zero to Express on OpenShift in Three Commands, which shows how to get started using Node.js, Express, and OpenShift together as fast as possible using the Node.js s2i (source-to-image) images that were recently released as part of Red Hat OpenShift Application Runtimes (RHOAR).

This post will add to the last one and show how we can start to debug and inspect our running code using the Chrome Developer Tools (DevTools) inspector.

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Making the Operation of Code More Transparent and Obvious

You can study source code and manually instrument functions as described in the “Use the dynamic tracing tools, Luke” blog article, but why not make it easier to find key points in the software by adding user-space markers to the application code? User-space markers have been available in Linux for quite some time (since 2009). The inactive user-space markers do not significantly slow down the code. Having them available allows you to get a more accurate picture of what the software is doing internally when unexpected issues occur. The diagnostic instrumentation can be more portable with the user-space markers, because the instrumentation does not need to rely on instrumenting particular function names or lines numbers in source code. The naming of the instrumentation points can also make clearer what event is associated with a particular instrumentation point.

For example, Ruby MRI on Red Hat Enterprise Linux 7 has a number of different instrumentation points made available as a SystemTap tapset. If SystemTap is installed on the system, as described by What is SystemTap and how to use it?, the installed Ruby MRI instrumentation points can be listed with the stap -L” command shown below. These events show the start and end of various operations in the Ruby runtime, such as the start and end of garbage collection (GC) marking and sweeping.

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“Use the dynamic tracing tools, Luke”

A common refrain for tracking down issues on computer systems running open source software is “Use the source, Luke.” Reviewing the source code can be helpful in understanding how the code works, but the static view may not give you a complete picture of how things work (or are broken) in the code. The paths taken through code are heavily data dependent. Without knowledge about specific values at key locations in code, you can easily miss what is happening. Dynamic instrumentation tools, such as SystemTap, that trace and instrument the software can help provide a more complete understanding of what the code is actually doing

I have wanted to better understand how the Ruby interpreter works. This is an opportunity to use SystemTap to investigate Ruby MRI internals on Red Hat Enterprise Linux 7. The article What is SystemTap and how to use it? has more information about installing SystemTap. The x86_64 RHEL 7 machine has ruby-2.0.0648-33.el7_4.x86_64.rpm installed, so the matching debuginfo RPM is installed to provide SystemTap with information about function parameters and to provide me with human-readable source code. The debuginfo RPM is installed by running the following command as root:

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A Red Hat Summit sign on the streets of San Francisco

Red Hat Summit: An introduction to OpenShift.io

Red Hat OpenShift.io is an innovative online service for development teams. Installing and configuring IDEs, libraries, and various tools is a major time sink. OpenShift.io is a cloud-native set of zero-install tools for editing and debugging code, agile planning, and managing CI/CD pipelines. It also features package analytics (an unbelievably cool feature we’ll discuss more in a minute), and has various quick starts for common frameworks. Because everyone on the team uses the exact same tools, “It works on my machine” becomes a thing of the past.

Product Manager Todd Mancini started the session with a brief overview of the product. There’s so much more here than just the ability to develop code online. Today’s best practices include complex deployment pipelines. With OpenShift.io, you get a Maven repository and a Jenkins pipeline automatically. You can select from several pipeline templates. If you need an approval stage, for example, that’s built in to the product. In short, all the tools you need to create a virtuous circle of analyze, plan, and create are here, with no installation or configuration needed.

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