CloudStack on Raspberry Pi 5s: A Learning Experience

Like many tech enthusiasts, we were excited to experiment with CloudStack on some affordable hardware. Our journey began with four shiny new Raspberry Pi 5s and a dream of creating a mini cloud infrastructure. Here’s how it went.

Setting Up the Pi Cluster (Bramble)

Our first step was to create a cluster using my Raspberry Pis, commonly known as a “bramble” in the Pi community. Following the excellent guide on the official Raspberry Pi website, we set up the cluster with one Pi designated as the head node. The initial clustering process went smoothly, and we were thrilled to see all four Pis working together as one unit.

Overcoming Hardware Issues

During the setup, we encountered an interesting challenge — one of our Raspberry Pis had a bricked WiFi module. Rather than letting this derail our progress, we came up with a simple yet effective solution: we took the SD card from the problematic Pi and moved it to a working Pi. This quick thinking allowed us to continue building our bramble without having to wait for replacement hardware. It’s a good reminder that sometimes the simplest solutions are the most effective!

Attempting CloudStack Implementation

With our bramble up and running, We moved on to the next challenge: installing CloudStack. We followed Rohit Yadav’s comprehensive guide on setting up CloudStack with ARM64 KVM. The installation was successful, and we were initially optimistic about our mini-cloud setup.

The Reality Check

However, We soon hit a significant roadblock. While trying to instantiate virtual machines, We encountered capacity issues. The Raspberry Pi 5, despite having a capable ARM Cortex-A76 processor that theoretically supports virtualization, proved challenging to configure properly for our CloudStack implementation. While KVM support is possible on the Pi 5’s hardware, getting it to work correctly with CloudStack in our specific setup presented unexpected hurdles.

The Solution: Moving to Standard Hardware

After troubleshooting and attempting various configurations, we pivoted to a more conventional approach. we migrated the entire setup to a modern laptop, where the virtualization stack was better documented and supported. The VMs created smoothly, and we finally had a working CloudStack environment.

Lessons Learned

This experience taught us valuable lessons about setting up cloud infrastructure. While the Raspberry Pi 5 is a powerful and capable device, implementing enterprise-grade software like CloudStack requires careful consideration of hardware compatibility, system configurations, and virtualization requirements. Sometimes, choosing more conventional hardware, where there’s extensive documentation and community support, can save considerable time and effort in achieving your goals. thus

Next Steps

While the laptop setup serves as a great proof of concept, our next step is to scale up to dedicated servers with substantial computational resources. We’re in the process of acquiring high-performance servers that will provide the necessary CPU, memory, and storage capabilities for a robust CloudStack deployment. This will allow us to move beyond experimentation and create a more production-ready environment capable of handling more demanding workloads and a larger number of virtual machines.

Technical Note

For those interested in attempting a similar setup, it’s worth noting that the Raspberry Pi 5’s ARM Cortex-A76 cores do support hardware virtualization. However, successful KVM implementation depends on multiple factors including:

• The Linux kernel version being used
• Proper enabling of virtualization modules
• The specific OS distribution running on the Pi
• System configuration settings
  

You can check your Pi’s virtualization support using commands like:

lscpu | grep Virtualization

or

ls /dev/kvm