This is the Compute Blade, and I'm test driving it in a four-node cluster.
This is the dev version, and Ivan from Uptime Lab sent four of these, a 4-bay 1U case, and
two fan modules.
He's been testing 40 of these in a rack at Jetbrains for months, and they're about to
go live on Kickstarter.
But what are these for?
[RSJ goes wild] Besides wielding them like Leonardo in the Teenage Mutant Ninja Turtles,
of course.
But why build a cluster with these Blades?
And what good are they if you can't even buy a Compute Module 4 from Raspberry Pi?
Do any alternative compute modules work?
I'll get to ALL those questions in this video.
Last year I posted a video on an early alpha version of the board.
Ivan redesigned almost everything since then, and came up with this.
And it looks gorgeous!
The blade has an M.2 slot and is powered through this Ethernet connection up front.
The Dev model has extras like a TPM module, USB and HDMI ports, and physical switches
for WiFi and bluetooth.
At the front there are a bunch of LEDs, a button, and a couple neopixels.
We'll get to those later.
On the opposite end there's a fan header.
There's this basic fan board that just holds a 40mm fan in place, or... if you're lucky
like me, you have this one-of-a-kind 'overengineered edition' fan controller.
This thing has another Raspberry Pi on it—in this case the tiny RP2040 microcontroller—and
it measures airflow temperatures and adjusts the fan speeds accordingly.
It also has more neopixels on it.
As far as just getting air to flow over the Pi goes, yeah... this is definitely overkill.
But you don't need all the fancy magic—this other fan module works just fine too.
Both these fan modules slide into the back of the custom 1U blade chassis, and the Compute
Blades slide in the front.
And sliding one out while looking at the back, there's a fancy limited edition signature,
straight from the Compute Blade's creator.
Nice!
But turning it back around, you see these custom red heatsinks?
Well, they work amazing, but take a look underneath.
They're probably a nightmare to machine.
I'm not sure if these'll make it to mass production but they work and look great; The Pis stayed
under 42 degrees no matter what workload I threw at 'em.
Even without heatsinks, these blades supply plenty of power and cooling for stable overclocking.
Ivan's been running forty of them for months in the lab where he works, and even running
overclocked, there's no downtime.
But the Compute Blade packs in some extra features.
The TPM and Dev versions both come with an integrated Infineon TPM 2.0 module.
TPM stands for Trusted Platform Module, and it can be used for secure embedded computing—especially
paired with a Zymbit which I'll get to later.
This chip stores encryption keys and secure passwords so someone couldn't steal a blade
and get your data.
Ivan went a step further and placed the chip under the Compute Module for better security.
Even if someone got physical access to the blade, they couldn't break into the TPM without
unplugging the Compute Module.
That'd turn off power to the chip and ideally lock all your data.
Secure Computing is a little more complicated than I can get into here, and the Raspberry
Pi isn't perfect, but the Compute Module does offer some improvements for trusted boot and
TPM that I'll touch on more in a future video.
Continuing the theme of turning the Raspberry Pi enterprise-grade, these blades also have
two features that fit right in with other racked equipment.
This pull tab at the front is hinged so it can press this front button.
And these LEDs indicate SSD activity, power, and Pi activity, plus there's a front-and-top-mounted
neopixel you can program to do whatever you want.
And you can also turn off all the LEDs in software if you want.
This demo Python script uses the neopixels to display CPU temperature using color, and
it also allows the LED to be used for locating the blade.
If you have a bunch of these in a rack somewhere, finding a particular Blade might be tricky.
So you can trigger the neopixel, then when you find the right Blade, press the button
to dismiss it.
So there's more to this board than meets the eye, but... why?
What would you use these things for?
Well, Ivan's original motivation was to get a bunch of ARM computers running for Continuous
Integration testing at Jetbrains.
They build tons of software for developers, and they need to test them on Macs, PCs, and
yes, even Raspberry Pis!
And he's running forty Blades in 2U.
That's 160 ARM cores, 320 GB of RAM, and up to 320 terabytes of flash storage in 1U of
rackspace.
That's actually useful for some people.
Like if you want a relatively low-power ARM cluster for testing or research.
Considering they're only burning a few watts each, you could have 160 ARM cores under 200
watts in 2U, with 40 NVMe drives!
Beat that, monster Ampere server from a few videos ago!
And another advantage of running multiple smaller machines instead of a few large ones
is resource isolation.
If you host lots of small apps, there's a lot more security isolating them on their
own servers.
Many modern security problems are due to people running more and more services on one system,
sharing the same memory and CPU.
But in my case, these blades make learning easier.
I test open source projects like Kubernetes and Drupal.
K3s, in particular, runs great on Pi clusters, and I have a whole open source pi-cluster
setup that I've been working on for years.
It has built-in monitoring so you can see your cluster health in real-time, and there
example Drupal and database deployments built-in.
I've also tested clustering software like Ceph, which I also have in that pi-cluster
project, so go check that out on GitHub even if you just have regular old Pis.
It's just more fun to do this stuff with physical computers, running right next to me on my
desk.
And sure, I could run some VMs on a PC, but that doesn't give me bare metal control and
physical networking.
And performance per watt isn't bad at all if you're running certain workloads like web
services.
My cluster uses less than 30 watts running four NVMe drives under 100% load, and it's
quietly sitting here on my desk.
But just running a bunch of Pis in a cluster is old news.
Tons of people are running Pi clusters.
The Blade, though?
It takes Pi clustering up a notch.
Ivan sent over some other accessories he's been testing.
This is a ZYMKEY 4, which is an additional hardware security module that plugs into this
header on the blade.
It has encrypted storage, tamper sensors, and a real-time clock built in, and it turns
the Blade into a fully secure compute node.
Ivan also made a custom board using Zymbit's HSM4 security module.
Using that, he made this demo where if you pull out the Blade, it can react to that by
doing things like automatically destroying sensitive data.
And if you're drooling over the idea of secure computing on the Pi, well, make sure you're
subscribed.
You're not gonna wanna miss my video on this thing!
Not even Red Shirt Jeff can hack it!
The rest of the world isn't standing still, though.
Pine64 launched their own blade, too.
I haven't had time to fully test it out yet, but I did throw both the SOQuartz and a Compute
Module 4 on it to see how it performs.
The integrated PoE circuit had a bit of coil whine sometimes, and none of the images I
downloaded for the SOQuartz would give me working HDMI or NVMe yet, so I swapped over
to a Compute Module 4.
My eMMC version worked fine, with HDMI, networking, and NVMe all present.
But a Lite CM4 didn't work, it would just go to the rainbow screen when it started booting
up.
So Pine64's Blade seems functional, but it's definitely more barebones and doesn't seem
to be fully supported yet.
If the Compute Blade gives you a slice of Pi, the SOQuartz blade feels like it came
out a little...
half-baked.
And I know how hard it is to find a Raspberry Pi right now.
I get it.
Just looking at rpilocator.com, it's pretty bleak.
But there are four other Compute Module clones you can buy now.
All of them say they're pin-compatible with the Compute Module 4.
And I have three of them to test.
I actually ordered a BPI CM4, too, but it's still stuck somewhere between China and my
house.
But I do have these other clones: BigTreeTech's CB1, Pine64's SOQuartz, and Radxa's CM3.
They're all meant to be drop-in replacements, though the CB1 doesn't support PCI Express,
so I didn't test it on this board.
Check out my Live stream from October, where I tested out the CB1 and talked more about
the Pi shortage.
But the SOQuartz does have PCI Express, so I tested it.
I actually did a whole video on it and the CM3 over a year ago!
Back then, it was hard to even get the boards to boot!
Have things improved since then?
Well... a little.
A lotta Raspberry Pi clones take the approach of 'throw hardware at the wall, and see what
sticks.'
But if spec sheets were everything, Raspberry Pi would've been just a tiny footnote in computing
history.
The big difference is in support, and Raspberry Pi has that in spades, especially with their
Raspberry Pi OS.
Heck, even Orange Pi started getting in that game with their own custom OS last year.
If I head over to Pine64's download page for the SOQuartz, it's a mess.
There are six different OSes listed, and the page doesn't recommend any of 'em.
In fact, it even says right on the page the first three images don't even work!
I get that Pine64 is community-based, but anyone besides a developer who comes into
the Pine64 ecosystem and expects to be productive is in for a rough ride.
That said, after reading this blog post, it looked like I might have the best experience
with Armbian.
So I looked on Armbian's website, and to my surprise, the SOQuartz wasn't even listed.
So I kept searching and found that for some reason the recommended Armbian download was
hosted on a forum that wasn't even related to either Pine64 or Armbian.
It's not even apparent how that image was built!
It felt sketchy but I downloaded the image anyway.
And...
it wouldn't download.
It got to 250 megabytes, and got stuck.
I tried it a few times but couldn't get that to work.
So I switched gears and tested Plebian Linux instead.
Plebian's goal is to get vanilla Linux running without any hacky RockChip patches.
This time the download worked, and it actually booted right up, which was a nice surprise
at this point.
But it doesn't support HDMI or WiFi yet.
And even though I could see my NVMe drive with lspci, it seems like the OS can't use
it, it got this error message and didn't show up when I tried to use it.
So it's a bit of a mess, but at least I can say the SOQuartz does run on the Compute Blade,
it's just a matter of software support.
The Radxa CM3 is still giving me trouble flashing an OS, so I couldn't test it out yet.
Maybe I'm just unlucky, but it's definitely not all rainbows and butterflies with these
CM4 clones.
If you do still wanna use one, splurge on the Dev version of the Compute Blade, though,
because you might need access to microSD and HDMI for debugging.
So for production use, I don't recommend clones yet.
They're slower, and they just don't work out of the box like a Pi does.
Even though it pains me to say this, hold out for Compute Module 4s.
Raspberry Pi said stock should improve through 2023—let's hope that's true.
And I asked Ivan if there was any way he could get a batch of CM4s to sell on Kickstarter
for early backers, but he said it would be months, even with a bulk order.
But regardless, the Compute Blade is a great way to run Pis in clusters; in fact it's my
favorite way so far.
It's just so satisfying sliding these things in and watching them run in a rack.
Ivan's working on a metal 1U rackmount enclosure too, but I couldn't convince him to ship me
16 more blades just yet.
The price is a little steep if you're just tinkering with some Raspberry Pis.
But if you have specific needs for dense ARM compute nodes, or you just want the coolest
Pi board on the market, the Compute Blade is worth a look.
It's been fun watching the design of these blades from this first proof of concept version
all the way to production, watching Ivan tweak every single part of this board until it became
what it is today.
It'll launch on Kickstarter this week, with three models, a basic version for $60, a TPM
version for $69, and the Dev version for $90, though those prices weren't a hundred percent
final when I recorded this video.
Check out all the details on the Kickstarter linked below, and until next time, I'm Jeff
Geerling.