Trying to blow the buzzword meter with that title...
Note of Caution!
This never made it quite 100% of the way, it was blocked largely on
account of me not being able to get the correct version of the
dependencies to install in CI. Bits and pieces of this may still be
useful for others though, so I'm putting this up in case it helps
Also, I really like the PIC bug, it tickles me how far down the stack
that ended up being. It may be the closest I ever come to being
vaguely involved (as in having stumbled across, not having
diagnosed/fixed) in something as interesting as
hardest bug ever
Feel free to ping me on the
OCaml discourse, though I'll likely just
point you at the more experienced and talented people who helped me
put this all together (in particular
Martin Lucin, an absurdly intelligent and
capable OG hacker and a driving force behing
- What are unikernels?
- Public hosting for unikernels
- Xen -> KVM (testing kernel output via QEMU)
- Bootable disk image
- Virtio problems
- DHCP lease
- TCP/IP stack
- Compiling an artifact
- Initial deploy script
- Zero-downtime instance updates
- Scaling based on CPU usage (how cool are the GCE suggestions to downsize an under-used image?)
- Custom deployment/infrastructure with Jitsu 1
Continuously Deploying Mirage Unikernels to Google Compute Engine using CircleCI
Or "Launch your unikernel-as-a-site with a zero-downtime rolling
updates, health-check monitors that'll restart an instance if it
crashes every 30 seconds, and a load balancer that'll auto-scale based
on CPU usage with every git push"
This post talks about achieving a production-like deploy pipeline for
a publicly-available service built using Mirage, specifically using
the fairly amazing Google Compute Engine infrastructure. I'll talk a
bit about the progression to the current setup, and some future
platforms that might be usable soon.
What are unikernels?
Unikernels are specialised, single-address-space machine images
constructed by using library operating systems.
The short, high-level idea is that unikernels are the equivalent of
opt-in operating systems, rather than
For example, when we build a virtual machine using a unikernel, we
only include the code necessary for our specific application. Don't
use a block-storage device for your Heroku-like application? The code
to interact with block-devices won't be run at all in your app - in
fact, it won't even be included in the final virtual machine image.
And when your app is running, it's the only thing running. No other
processes vying for resources, threatening to push your server over in
the middle of the night even though you didn't know a service was
configured to run by default.
There are a few immediately obvious advantages to this approach:
- Size: Unikernels are typically microscopic as deployable
- Efficiency: When running, unikernels only use the bare minimum
of what your code needs. Nothing else.
- Security: Removing millions of lines of code and eliminating
the inter-process protection model from your app drastically
reduces attack surface
- Simplicity: Knowing exactly what's in your application, and how
it's all running considerably simplifies the mental model for both
performance and correctness
MirageOS is a library operating system that constructs unikernels
for secure, high-performance network applications across a variety
of cloud computing and mobile platforms
Mirage (which is a very clever name once you get it) is a library to
build clean-slate unikernels using OCaml. That means to build a Mirage
unikernel, you need to write your entire app (more or less) in
OCaml. I've talked quite a bit now about why
OCaml is pretty solid,
but I understand if some of you run away screaming now. No worries,
there are other approaches to unikernels that may work better for
you2. But as for me and my house, we will use Mirage.
There are some great talks that go over some of the cool aspects of
Mirage in much more detail 13, but it's unclear if they're
actually usable in any major way. There are even companies that take
out ads against unikernels, highlighting many of the ways in which
they're (currently) unsuitable for production:
Bit weird, that.
But I suspect that bit by bit this will change, assuming sufficient
elbow grease and determination on our parts. So with that said, let's
roll up our sleeves and figure out one of the biggest hurdles to using
unikernels in production today: deploying them!
Public hosting for unikernels
Having written our app as a unikernel, how do we get it up and running
in a production-like setting? I've used AWS fairly heavily in the
past, so it was my initial go-to for this site.
AWS runs on the Xen hypervisor, which is the main non-unix target
Mirage was developed for. In theory, it should be the smoothest
option. Sadly, the primitives and API that AWS expose just don't match
well. The process is something like
- Download the AWS command line tools
- Start an instance
- Create, attach, and partition an EBS volume (we'll turn this into
an AMI once we get our unikernel on it)
- Copy the Xen unikernel over to the volume
- Create the GRUB entries... blablabla
- Create a snapshot of the volume ohmygod
- Register your AMI using the
pv-grub kernel id what was I doing again
- Start a new instance from the AMI
Unfortunately #3 means that we need to have a build machine that's
on the AWS network so that we can attach the volume, and we need to
SSH into the machine to do the heavy lifting. Also, we end up with a
lot of left over detritus - the volume, the snapshot, and the AMI. It
could be scripted at some point though.
GCE to the rescue!
GCE is Google's public computing
offering, and I currently can't recommend it highly enough. The
per-minute pricing model is a much better match for instances that
boot in less than 100ms, the interface is considerably nicer and
offers the equivalent REST API call for most actions you take, and the
primitives exposed in the API mean we can much more easily deploy a
unikernel. Win, win, win!
Xen -> KVM
There is a big potential show-stopper though: GCE uses the KVM
hypervisor instead of Xen, which is much, much nicer, but not
supported by Mirage as of the beginning of this year. Luckily, some
fairly crazy heroes (Dan Williams,
Ricardo Koller, and
Martin Lucina, specifically) stepped up and made it
happen with Solo5!
Solo5 Unikernel implements a unikernel base, or the lowest layer of
code inside a unikernel, which interacts with the hardware
abstraction exposed by the hypervisor and forms a platform for
building language runtimes and applications. Solo5 currently
interfaces with the MirageOS ecosystem, enabling Mirage unikernels
to run on either Linux KVM/QEMU
I highly recommend checking out a replay of the great webinar the
authors gave on the topic
https://developer.ibm.com/open/solo5-unikernel/ It'll give you a sense
of how much room for optimization and cleanup there is as our hosting
Now that we have KVM kernels, we can test them locally fairly easily
using QEMU, which shortens the iterations while we dealt with teething
on the new platform. The
Bootable disk image
This was just on the other side of my experience/abilities,
personally. Constructing a disk image that would boot a custom
(non-Linux) kernel isn't something I've done before, and I struggled
to remember how the pieces fit together. Once again, @mato came to the
rescue with a
lovely little script
that does exactly what we need, no muss, no fuss.
Initially we had booting unikernels that printed to the serial console
just fine, but didn't seem to get any DHCP lease. The unikernel was
DHCP discover broadcasts,
but not getting anything in return, poor lil' fella. I then tried with
a hard-coded IP literally configured at compile time, and booted an
instance on GCE with a matching IP, and still nothing. Nearly the
entire Mirage stack is in plain OCaml though, including the
TCP/IP stack, so I was able
to add in plenty of debug log statements and see
tracked everything down to problems with the Virtio implementation,
The issue was that the vring sizes were hardcoded (not the buffer
length as I mentioned above). The issue with the vring sizes is kind
of interesting, the thing is that the virtio spec allows for
different sizes, but every single qemu we tried uses the same 256
len. The QEMU in GCE must be patched as it uses 4096 as the size,
which is pretty big, I guess they do that for performance reasons. -
I tried out the fixes, and we had a booting, publicly accessible
unikernel! However, it was extremely slow, with no obvious reason
why. Looking at the logs however, I saw that I had forgotten to remove
a ton of
logging per-frame. Careful
what you wish for with accessibility, I guess!
This was a deep rabbit hole. The
bug manifested as
error: exception (Invalid_argument "equal: abstract value"), which
seemed strange since the site worked on Unix and Xen backends, so
there shouldn't have been anything logically wrong with the OCaml
types, despite what the exception message hinted at. Read
for the full, thrilling detective work and explanation, but a
simplified version seems to be that portions of the OCaml/Solo5 code
were placed in between the bootloader and the entry point of the
program, and the bootloader zero'd all the memory in-between (as it
should) before handing control over to our program. So eventually our
program did some comparison of values, and a portion of the value had
at compile/link time been relocated and destroyed, and OCaml threw the
Finally, we have a booting, non-slow, publicly-accessible Mirage
instance running on GCE! Great! However, every ~50 http requests, it
panics and dies:
 serving //18.104.22.168/stylesheets/normalize.css.
 serving //22.214.171.124/js/client.js.
 serving //126.96.36.199/stylesheets/foundation.css.
 serving //188.8.131.52/images/sofuji_black_30.png.
 serving //184.108.40.206/images/posts/riseos_error_email.png.
assertion failed: "e->len <= PKT_BUFFER_LEN"
Oh no! However, being a bit of a kludgy-hacker desperate to get a
stable unikernel I can show to some friends, I figured out a terrible
workaround: GCE offers fantastic health-check monitors that'll restart
an instance if it crashes because of a virtio (or whatever) failure
every 30 seconds. Problem solved, right? At least I don't have restart
the instance personally...
And that was an acceptable temporary fix until @ricarkol was once
again able to track down the cause of the crashes and fix things up
that had to do with some GCE/Virtio IO buffer descriptor wrinkle:
The second issue is that Virtio allows for dividing IO requests in
multiple buffer descriptors. For some reason the QEMU in GCE didn't
like that. While cleaning up stuff I simplified our Virtio layer to
send a single buffer descriptor, and GCE liked it and let our IOs go
through - @ricarkol
So now Solo5 unikernels seem fairly stable on GCE as well! Looks like
it's time to wrap everything up into a nice deploy pipeline.
With the help of the GCE support staff and the Solo5 authors, we're
now able to run Mirage apps on GCE. The process in this case looks
- Compile our unikernel
- Create a tar'd and gzipped bootable disk image locally with our unikernel
- Upload said disk image (should be ~1-10MB, depending on our contents. Right now this site is ~6.6MB)
- Create an image from the disk image
- Trigger a rolling update
Importantly, because we can simply upload bootable disk images, we
don't need any specialized build machine, and the entire process can
One time setup
We'll create two abstract pieces that'll let us continually deploy and
scale: An instance group, and a load balancer.
Creating the template and instance group
First, two quick definitions...
Managed instance groups:
A managed instance group uses an instance template to create
identical instances. You control a managed instance group as a
single entity. If you wanted to make changes to instances that are
part of a managed instance group, you would apply the change to the
whole instance group.
Instance templates define the machine type, image, zone, and other
instance properties for the instances in a managed instance group.
We'll create a template with
FINISH THIS SECTION(FIN)
Setting up the load balancer
Honestly there's not much to say here, GCE makes this trivial. We
simply say what class of instances we want (vCPU, RAM, etc.), what the
trigger/threshold to scale is (CPU usage or request amount), and the
image we want to boot as we scale out.
In this case, I'm using a fairly small instance with the instance
group we just created, and I want another instance whenever we
sustained CPU usage over 60% for more than 30 seconds:
`PUT THE BASH CODE TO CREATE THAT HERE`(FIN)
The actual cli to do everything looks like this:
mirage configure -t virtio --dhcp=true \
--show_errors=true --report_errors=true \
bin/unikernel-mkimage.sh tmp/disk.raw mir-riseos.virtio
tar -czvf mir-riseos-01.tar.gz disk.raw
# Upload the file to Google Compute Storage
# as the original filename
gsutil cp tmp/mir-riseos-01.tar.gz gs://mir-riseos
# Copy/Alias it as *-latest
gsutil cp gs://mir-riseos/mir-riseos01.tar.gz \
# Delete the image if it exists
y | gcloud compute images delete mir-riseos-latest
# Create an image from the new latest file
gcloud compute images create mir-riseos-latest \
# Updating the mir-riseos-latest *image* in place will mutate the
# *instance-template* that points to it. To then update all of
# our instances with zero downtime, we now just have to ask gcloud
# to do a rolling update to a group using said
gcloud alpha compute rolling-updates start \
--group mir-riseos-group \
--template mir-riseos-1 \
Or, after splitting this up into two scripts:
export NAME=mir-riseos-1 CANONICAL=mir-riseos GCS_FOLDER=mir-riseos
Not too shabby to - once again - launch your unikernel-as-a-site
with zero-downtime rolling updates, health-check monitors that'll
restart any crashed instance every 30 seconds, and a load balancer
that auto-scales based on CPU usage. The next step is to hook up
CircleCI so we have continuous deploy of our
unikernels on every push to master.
The biggest blocker here, and one I haven't been able to solve yet, is
the OPAM switch setup. My current docker image has (apparently) a
hand-selected list of packages and pins that is nearly impossible to