Provisioning with Red Hat Satellite 6

Satellite is Red Hat’s content management, provisioning, configuration management, and lifecycle management solution to help keep your infrastructure running efficiently and more securely while reducing costs and overall complexity. Regardless of your what your environment looks like, you can benefit from the configuration management capabilities that Satellite provides.

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CloudForms: Manage your IT and Hybrid Cloud through a single platform

Before I start talking about IT and how you can manage, control, and optimize your Hybrid IT infrastructure, I propose that we reflect directly on your living room, where you usually watch TV,  movies, listen to music, play video games, etc. Even if you do not enjoy this type of entertainment, you know that for each of these devices, it is common to use a remote control allowing you to switch between them, manage them, and control all of your favorite programming. While these devices are converging to an all-in-one architecture, they are truly multi-functional. We’ve learned how to handle remote controls at a very young age and it’s the reality we live in. In this case, you are faced with heterogeneous devices and various remote controls, where the number of controls increases as you acquire new devices. It is difficult to have to manage the complexity of a simple task that is to manage your schedule, operating multiple devices, through different controls, with numerous features, and different vendors. Products and vendors bring specific features, use different nomenclature, and provide some features which may or may not be compatible with each other. Going beyond, some of these features made available by vendors, will not even be used throughout the lifetime of these devices, a real waste!

Picture 1 – Managing many devices with many remote controls

Considering this scenario, you might be wondering: What is the relationship of the complexity of having to deal with various entertainment devices and remote controls with your IT infrastructure? And what does this have to do with cloud computing or Hybrid IT?

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Guide to starting to use AWX, the upstream of Red Hat Ansible Tower, on top of OpenShift

Introduction

This is the first post in a series that shows how to use the new release of the community version of Red Hat Ansible Tower. In this post, we will start with the installation of AWX on top of OpenShift. In the next post, I’ll show how to set a dynamic inventory to access the servers from AWS (EC2) and how to run a playbook to access our AWS EC2 inventory.

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Entropy in RHEL based cloud instances

According to Wikipedia, entropy is the randomness collected by an operating system or application for use in cryptography or other uses that require random data.

Entropy is often overlooked, misconfigured or forgotten and it can originate in sporadic errors whether it can be timeouts, refused connections, etc. Such errors are difficult to debug as the errors happen only when there is not enough entropy available.

This article tries to explain briefly how to check if this can be a problem in a RHEL system and how to fix it.

NOTE: This article is meant to provide some helpful hints about entropy. It is not meant to be exhaustive or definitive. There are hundreds of information sources on the Internet such as KCS articles; https://access.redhat.com/articles/221583 and https://access.redhat.com/solutions/19866 where this article is based. Check the bibliography section for more information.

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Gluster for OpenShift – Part 1: Container-Ready Storage

OpenShift Container Platform (OCP) offers many different types of persistent storage. Persistent storage ensures that data should be insistent between builds and container migrations. When choosing a persistent storage backend to ensure that the backend supports the scaling, speed, dynamic provisioning, RWX/RWO support and redundancy that the project requires. Container-Ready Storage (CRS), or native Gluster for OCP, is defined by the concept of persistent volumes, which are OCP created objects that allow storage to be defined and then used by pods to allow for data persistence.

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