Red Hat and SUSE Leftovers

Events like Red Hat Summit fill me with excitement and, admittedly, a bit of trepidation. Thousands of people, a schedule packed with informative and useful sessions, and opportunities to meet and talk with folks doing exciting work in open source sounds great. It also, well, sounds a bit exhausting if you’re an introvert. It doesn’t have to be, though, and Red Hat wants everyone to feel welcome, comfortable, and able to fully enjoy the event. With that in mind, read on for some strategies and resources for success.

Introverts aren’t (necessarily) misanthropes, we just tend to like smaller gatherings and less noisy and intense social situations. Even those can be fun, in limited doses. The thing about a large conference like Red Hat Summit, though, is that it’s a huge helping of people and activities turned up to 11. Don’t worry, you can still go and have a great experience, it just takes a little bit of planning.

In Software engineering, a cluster resembles a group of nodes that work together to distribute the work load. Additionally clustering helps in fault tolerance, by having a cluster acting as a secondary (backup) to a primary cluster.

You may have read some of the release notes or press coverage from the recent release of OpenStack Stein, in which case you’ll know that Stein introduced multi-factor authentication receipts for Keystone. This really just completes the work that was originally begun in the Ocata release, making it easier to implement a challenge/response mechanism in your OpenStack environment. Multi-factor authentication is quickly becoming the norm in everything from free online email services, to social media sites and more – catching up with the security that most, if not all online banking services have been offering for some time now.

One of the first questions in any discussion about cluster sizing tends to be “How many containers are you running?”. While this is a good data point (especially if you are pushing the scheduler to its limit) it doesn’t show the whole story.
We tend to abstract out a container as this homogeneous building block that represents any workload.

This abstraction has a lot of value for learning how containers work and how the system treats all workloads similarly (which is hugely valuable). However, it falls down when we start looking at planning our hardware requirements.