At RackN, we’ve been shrinking our scale deployment platform down to run faithfully on a desktop class system. Since we abstract the network and hardware complexity, you can build automation that scales to physical from as little as 16 Gb of RAM (the same size as Packet’s smaller server). That allows the exact same logic we use for an 80 node Ceph or Kubernetes cluster work on my 14” laptop.
In fact, we’ve been getting a bit obsessed with making a clean restart small and fast using containers, VMs and bootstrapping scripts.
Creating a remote test lab is part of this obsession because many rehearsals make great performances. We wanted to eliminate the setup time and process for users who just want to experiment with a production grade deployment. Using Packet.net hosted metal and some Ansible scripts, we can build a complete HA Kubernetes cluster in about 15 minutes using VMs. This lets us iterate on Kubernetes best practices virtually since the “setup metal part” is handled abstractly by Digital Rebar.
Yawn. You could do the same in AWS. Why is that exciting?
The process for the lab system we build in Packet.net can then be used to provision a complete private infrastructure on metal including RAID, BIOS and server networking. Even though the lab uses VMs, we still do real networking, storage and configuration. For example, we can iterate building real software defined networking (SDN) overlays in this environment and then scale the work up to physical gear.
The provision and deploy time is so fast (generally, under 15 minutes) that we are using it as a clean environment for Dev and QA cycles on new automation. It’s also a very practical demo environment for these platforms because of the fidelity between this environment and an actual pilot. For me, that means spending $0.40 so I don’t have to sweat losing my work in process, battery life or my wifi connection to crank out a demo.
BTW… Packet.net servers are SUPER FAST. Even the small 16 Gb RAM machine is packed with SSDs and great connectivity.
If you are exploring any of the several workloads that we’ve been building (Docker Swarm, Kubernetes, Mesos, CloudFoundry, Ceph and OpenStack) or just playing around with API driven physical provisioning, we just made that work a little easier and a lot faster.