Containerizing open-vm-tools – Part 1: The Dockerfile and constructing a systemd unit file

While validating OpenShift Container Platform on a VMware platform the usage of Atomic OS was also a requirement. In the initial reference architecture, the decision was made to use Red Hat Enterprise Linux as the platform. This platform was then customized and the same packages as in Atomic were installed via Ansible and Red Hat Network.

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Container Images Compliance – what we built at ManageIQ to remove a security pain point – part 2

Part 2 of 2

In part one of this blog post, we mentioned a pain point in Container based environments. We introduced SCAP as a means to measure compliance in computer systems and introduced ManageIQ as a means of automating Cloud & Container based workflows.

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Container Images Compliance – what we built at ManageIQ to remove a security pain point – part 1

Part 1 of 2

“Docker is about running random crap from the Internet as root on your host”  – Dan Walsh

Continue reading “Container Images Compliance – what we built at ManageIQ to remove a security pain point – part 1”


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For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.

Microservices Deployments Evolution

Microservices Are Here, to Stay

A few years back, most software systems had a monolithic architecture and slow release cycle. In the recent years, there is a clear move towards Microservices architecture, which is optimized for scalability, elasticity, failure, and speed of change. This trend has been further enforced by the adoption of cloud and containers, which also enabled practices such as DevOps.

Trends in the IT Industry

All these changes have resulted in a growing number of services to develop and an even bigger number of deployments to do. It soon became clear that the explosion in the number of deployments cannot be controlled using pre-microservices tools and techniques, and new ways have been born. In this article, we will see how Cloud Native platforms such as Kubernetes allow deployment of Microservices in high scale with minimal human intervention.

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Automate integration CI/CD process

Red Hat Fuse Integration Service 2.0 tech preview was released a few weeks ago and as it’s based on Red Hat OpenShift 3.3, which has pipeline capability on top of it (tech preview on OpenShift as well), you are able to get one step closer to a more automated and agile continuous integration. As well as, a deployment one-stop platform for us, the integration developer.

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Migrating my iptables setup to nftables

Wanting to become familiar with nftables, I decided to jump in at the deep end and just use it on my local workstation. The goal was to replace the existing iptables setup, ideally without any drawbacks. The following essay will guide you through what I have done in order to achieve that.

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Using the Kubernetes Client for Go

The Kubernetes client package for Go provides developers with a vast range of functions to access data and resources in a cluster. Taking advantage of its capabilities can allow the opportunity to build powerful controllers, monitoring and managing your cluster, beyond the scope of what is offered by stock OpenShift or Kubernetes setups.

For example, the PodInterface allows you to list, update, delete, or get specific pods either by namespace or across all namespaces. This interface is complemented by similar implementations for many other cluster resource types such as ReplicationControllers and ResourceQuotas.

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Automating microservices deployment with Ansible

One of the main principles of microservices is to be independently deployable. As a consequence, Microservices development and operation tend to be much more complex than a Monolith because of their distributed nature — if your IT team has not moved out yet from its silos and has adopted DevOps practices, the operations team will not really understand why they have to deploy hundreds of independent software pieces in opposite to the “good old monolith”.

“You need a mature operations team to manage lots of services, which are being redeployed regularly”  (Microservices trade-offs by Martin Fowler).

The operations team and the software development team should work together adopting DevOps practices to avoid silos and deployment process where the software team throws the software over the wall.

Screenshot 2016-11-18 13.46.37.png

Ideally, each Microservices team is multifunctional and own the software artifact from conception to production. Given the multifunctional nature of these teams, “infrastructure as code (IaC)” and automation are now a necessity. DevOps teams share the knowledge of server provisioning, configuration management and deployment. There are several tools and approaches for IaC. As an example, I can mention Kubernetes, that allows you to define its objects as yaml or json files.

screenshot-2016-11-16-10-53-00

A couple months ago, I published a blog post that shows how to have your own (no-cost) microservices playground.  The focus of this material is educational. It provides instructions on how to deploy each microservice independently. However, some people would like to see all of them running running in few minutes.

To show how you can run this microservices playground environment in less than 20 minutes, I decided to record the following screencast that shows how to create an OpenShift cluster using “oc cluster up” (Check out “Four creative ways to create an OpenShift/Kubernetes dev environment“), and deploy all of them using Ansible.

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Container Orchestration Specification for better DevOps

The world is moving to microservices, where applications are composed of a complex topology of components, orchestrated into a coordinated topology.

Microservices have become increasingly popular as they increase business agility and reduce the time for changes to be made. On top of this, containers make it easier for organizations to adopt microservices.

Increasingly, containers are the runtimes used for composition, and many excellent solutions have been developed to handle container orchestration such as: Kubernetes/OpenShift; Mesos and its many frameworks like Marathon; and even Docker Compose, Swarm and SwarmKit are trying to address these issues.

But at what cost?

We’ve all experienced that moment when we’ve been working long hours and think “yes, that feature is ready to ship”. We release it into our staging environment and bang, nothing works, and we don’t really know why. What if you could consistently take the same topology you ran in your development workspace, and run it in other, enterprise grade, environments such as your staging or production, and expect it to always JUST WORK?

Continue reading “Container Orchestration Specification for better DevOps”


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For more information about Red Hat OpenShift and other related topics, visit: OpenShift, OpenShift Online.