We’re excited to see and be part of the community progress towards enterprise-ready Kubernetes operations on both cloud and on-premises. The RackN team is excited to be part of multiple groups establishing patterns with shareable/reusable automation. I strongly recommend watching (or, better, collaborating in) these efforts if you are deploying Kubernetes even at experimental scale.
We’ve worked hard to make shared community ops work accessible, repeatable and multi-platform without compromising scale or security.
The RackN team has been enthusiastic supporters of Kubernetes since the 1.0 launch with our first deployments going back to June 2015 with updates for 1.2, 1.3 and now 1.5. I’m excited to report that fully converged the composable Digital Rebar approach with the Kubernetes Kargo Ansible. Our 1.2 efforts leveraged the Kargo predecessor “Kubespray.” This integration brings the parallel hybrid operation and node-by-node function of Digital Rebar with the Ansible community efforts around Kargo.
Composable design is a key element the RackN focus on SRE automation because it allows ecosystem
That allows a fully integrated deploy where Digital Rebar stages the environment and then use Kargo directly from upsteam to install Kubernetes. Post-deployment, Digital Rebar is able to extend the cluster with packages like Helm, Deis, Dashboard and others.
Since Digital Rebar supports parallel deployments, it’s possible to fully exercise the options enabled by Kargo simultaneously for development and testing. Benefits????
For example, you can built-test-destroy coordinated Kubernetes installs on Centos, Redhat and Ubuntu as part of an automation pipeline. Unlike client side approaches like Terraform or Ansible, our infrastructure allows transparent monitoring of the deployments including Slack integration.
Flexibility is also important between users because Ops variation is both a benefit and a cost.
A key Digital Rebar design goal is for users to explore useful variation and still share operational best practices. We are proving that shared community automation can support many different scenarios including variation between between clouds, physical, operating system, networking and container engine.
If we cannot manage this variation in a consistent way then we’re doomed to operational fragmentation (like OpenStack has endured).
We’re inviting you to check out our open work supporting the Kubernetes Ops community. As Rob Hirschfeld says, looking for “Day 2” minded operators who want to make sure that we are always able to share Kubernetes best practices.