Guide: How to Emulate a Raspberry Pi Cluster with Docker Compose

TL;DR This guide discusses everything needed to build a simple, scalable, and fully binary compatible Raspberry Pi cluster using QEMU, Docker, Docker Compose, and Ansible. Introduction The Raspberry Pi is no longer just a low-cost platform for students to learn computing, it's now a legitimate research and development platform that's used for IoT, networking, distributed systems, and software development. It's even used administratively in production environments. Not long after the first Raspberry Pi was released in 2012, several set out to build them into low-cost clusters, often for research and testing purposes. Interns at built a multi-datacenter, 32 nodes fault-tolerance demo, complete with a big red button to simulate the failure of an entire datacenter. built a that was intended to be part of his MSCE thesis. , built " ", a 120 node Raspberry Pi cluster, for scaled testing of their online platform. And on the extreme end of the spectrum, Oracle built a , which they introduced at Oracle OpenWorld 2019. DataStax Cassenda David Guill 40-node Raspberry Pi Cluster Balena The Beast 1060 node Raspberry Pi Cluster Innovation with the Raspberry Pi continues as they are turned into wi-fi extenders, security cameras, even bigger clusters, and more. While the main value of these clusters comes from their size and low cost, their popularity makes them an increasingly common development platform. Since the Raspberry Pi uses an ARM processor, this can make development problematic for those of us who work exclusively in the cloud. While commercial solutions exist, we will be building our own emulated cluster using a fully open source stack hosted on Google Compute Engine. Use Cases Other than learning from the experience, Dockerizing an emulated Raspberry Pi enables us to do three things. One, it turns into software that which would otherwise be a hardware-only device that nobody has to remember to carry around (I'm always losing the peripheral cables). Two, it enables Docker to do for the Pi what Docker does best for everything else: it makes software portable, easy to manage, and easy to replicate. And three, it takes up no physical space. If we can build one Raspberry Pi with Docker, we can build many. If we can build many, we can network them all together. While we may encounter some limitations, this build will emulate a cluster of Raspberry Pi 1s that's logically equivalent to a simple, multi-node physical cluster. Emulated Hardware Architecture While technically not identical, the emulation software we will be using, QEMU, provides an ARM-Versatile architecture that's roughly compatible with what is found on a Raspberry Pi 1. Some modifications to the kernel are necessary in order for it to work properly with Raspbian, but for our purposes, it's one of the more stable open source solutions available. pi@raspberrypi:~$ cat /proc/cpuinfo processor : 0 model name : ARMv6-compatible processor rev 7 (v6l) BogoMIPS : 577.53 Features : half thumb fastmult vfp edsp java tls CPU implementer : 0x41 CPU architecture: 7 CPU variant : 0x0 CPU part : 0xb76 CPU revision : 7 Hardware : ARM-Versatile (Device Tree Support) Revision : 0000 Serial : 0000000000000000 Compared to a Physical Raspberry Pi 1, they are nearly identical: pi@raspberrypi:~ $ cat /proc/cpuinfo processor : 0 model name : ARMv6-compatible processor rev 7 (v6l) BogoMIPS : 697.95 Features : half thumb fastmult vfp edsp java tls CPU implementer : 0x41 CPU architecture: 7 CPU variant : 0x0 CPU part : 0xb76 CPU revision : 7 Hardware : BCM2835 Revision : 000d Serial : 000000003d9a54c5 Background What is QEMU? is a processor emulator. It supports a number of different processors, but we're only interested in something that can run Raspberry Pi images natively without a lot of difficulties. In this case, we're going to be using QEMU 4.2.0, which supports an ARM11 instruction set that's compatible with the Broadcom BCM2835 (ARM1176JZFS) chip found on the Raspberry Pi 1 and Zero. We will use ARM1176 support on QEMU, which will allow us to more or less emulate a Raspberry Pi 1. I say more or less because we will still need to use a in order to boot on the emulated hardware. QEMU support for the Pi is still in development, so our approach to getting it to work here is just a clever hack that will by no means be optimal or efficient in terms of CPU utilization. QEMU customized Raspbian kernel QEMU Features QEMU supports many of the same features found in Docker, however, it can run full software emulation without a host kernel driver. This means that it can run inside Docker, or any other virtual machine, without host virtualization support. The QEMU feature list is extensive, and the learning curve is steep. However, the primary feature that we will be focused on for this build is host port forwarding so that data can be passed to the host. Dockerized QEMU One of Docker's strengths is that it doesn't handle full-fledged virtualization, but instead relies on the architecture of the host system. Since our host system will be running an Intel processor, we can't expect Docker to handle ARM operations on its own. So, we will be placing QEMU inside a Docker container. Since Docker is designed to run software at near-native performance, the operational efficiency challenge will be with QEMU itself. QEMU, on the other hand, supports the emulation of a machine's architecture completely with software. The advantage here is that it can run inside any virtualized system or container, independent of its system architecture. If patient, we could even run a Dockerized Raspberry Pi container inside another Dockerized Raspberry Pi container. The drawback to QEMU is that it has comparatively poor performance compared to other types of virtualization. But we can benefit from the best of both worlds by leveraging QEMU's ARM emulation while depending on Docker for everything else. Raspbian Based on Debian, is a popular and well-supported operating system for the Raspberry Pi. It's one of the most often recommended for the platform and the is active and well managed. Raspbian community Physical Raspberry Pi Speed Comparison The following tests are intended as a baseline for comparing our virtualized systems. Since we will be emulating a single-core, these tests are only single-core, single thread, regardless of how many physical cores are incorporated into the architecture. Raspberry Pi 1 2011,12 Test execution summary: total time: 330.5514s total number of events: 10000 total time taken by event execution: 330.5002 per-request statistics: min: 32.92ms avg: 33.05ms max: 40.94ms approx. 95 percentile: 33.24ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 330.5002/0.00 Raspberry Pi 1 A+ V1.1 2014 Test execution summary: total time: 328.7505s total number of events: 10000 total time taken by event execution: 328.6931 per-request statistics: min: 32.71ms avg: 32.87ms max: 78.93ms approx. 95 percentile: 33.03ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 328.6931/0.00 Raspberry Pi Zero W v1.1 2017 Test execution summary: total time: 228.2025s total number of events: 10000 total time taken by event execution: 228.1688 per-request statistics: min: 22.76ms avg: 22.82ms max: 35.29ms approx. 95 percentile: 22.94ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 228.1688/0.00 Raspberry Pi 2 Model B v1.1 2014 Test execution summary: total time: 224.9052s total number of events: 10000 total time taken by event execution: 224.8738 per-request statistics: min: 22.20ms avg: 22.49ms max: 32.85ms approx. 95 percentile: 22.81ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 224.8738/0.00 Raspberry Pi 3 Model B v1.2 2015 Test execution summary: total time: 139.6140s total number of events: 10000 total time taken by event execution: 139.6087 per-request statistics: min: 13.94ms avg: 13.96ms max: 34.06ms approx. 95 percentile: 13.96ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 139.6087/0.00 Raspberry Pi 4 B 2018 Test execution summary: total time: 92.6405s total number of events: 10000 total time taken by event execution: 92.6338 per-request statistics: min: 9.22ms avg: 9.26ms max: 23.50ms approx. 95 percentile: 9.27ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 92.6338/0.00 Project Requirements Single Host Specifications Historically, QEMU has been single-threaded, emulating all cores of a system's architecture on a single CPU. While that's no longer the case, we are still going to be emulating a single core Raspberry Pi. We will do some benchmarks later to compare how different CPU limits on each node impacts performance. But for now, we will use one CPU per single-core node. Since QEMU has the potential to use a lot of CPU resources due to its inherent inefficiency, our initial three-node cluster will start with a baseline of at least one CPU per node, leaving one CPU dedicated to the host to avoid performance problems. The VM specs selected for this task are as follows. Cloud Provider: Google Cloud Platform Instance Type: n1-standard-4 CPUs: 4 Memory: 15GB Disk: 100GB Operating System: Ubuntu 18.04 LTS Docker Installed on the host, we're also using the default version of Docker that is available on the default apt repository for Ubuntu 18.04 LTS. Docker version 18.09.7, build 2d0083d # docker -v Docker Compose docker-compose version 1.25.0, build 0a186604 # docker-compose -v Docker Hub Ubuntu Image 18.04, bionic-20200112, bionic, latest QEMU Installed inside the Docker container, we will be using the following version of QEMU for ARM: QEMU emulator version 4.2.0 Copyright (c) 2003-2019 Fabrice Bellard and the QEMU Project developers # qemu-system-arm --version QEMU Customized Kernel for Raspbian Loaded from QEMU inside Docker, we will use 's for Raspbian, which has been modified to be usable with QEMU. Dhruv Vyas compiled kernel Raspbian Lite Image Also booted from QEMU, we will use an unmodified version of from 9/30/2019. Raspbian Lite Expect (Tcl/Tk) Installed on the Docker container is the following version of Expect: expect version 5.45.4 # expect -v / ssh sshd will need to be enable on each Raspbian node, and should be enabled on the host. sshd ssh Ansible The following version of Ansible is also being used, along with its other dependencies: ansible 2.5.1 config file = /etc/ansible/ansible.cfg configured module search path = [u , u ] ansible python module location = /usr/lib/python2.7/dist-packages/ansible executable location = /usr/bin/ansible python version = 2.7.17 (default, Nov 7 2019, 10:07:09) [GCC 7.4.0] # ansible --version '/root/.ansible/plugins/modules' '/usr/share/ansible/plugins/modules' Building the Docker Images QEMU Build Container We will compile QEMU 4.2.0 from source. It will need all the supporting build tools, so to keep our app container as small as possible, we will create a separate build container for the QEMU build using a minimal version of Ubuntu 18.04 from Docker Hub. QEMU App Container Once the QEMU is compiled from source, we will transfer it to the app container. Also from Docker Hub, we will use the same minimal version of Ubuntu 18.04 to host the QEMU binary. Docker Configuration The Dockerfile We will be using the following Dockerfile, which may also be found updated in this guide's accompanying repository on Github. Each code snippet below makes up a segment of the Dockerfile. Thanks goes to 's for his work on . pidoc Luke Child dockerpi Build stage for : qemu-system-arm FROM ubuntu AS qemu-system-arm-builder ARG QEMU_VERSION=4.2.0 ENV QEMU_TARBALL= WORKDIR /qemu RUN apt-get update && \ apt-get -y install \ wget \ gpg \ pkg-config \ python \ build-essential \ libglib2.0-dev \ libpixman-1-dev \ libfdt-dev \ zlib1g-dev \ flex \ bison "qemu- .tar.xz" ${QEMU_VERSION} Download source. RUN wget RUN RUN wget RUN gpg --keyserver keyserver.ubuntu.com --recv-keys CEACC9E15534EBABB82D3FA03353C9CEF108B584 RUN gpg --verify "https://download.qemu.org/ " ${QEMU_TARBALL} # Verify signatures... "https://download.qemu.org/ .sig" ${QEMU_TARBALL} " .sig" ${QEMU_TARBALL} " " ${QEMU_TARBALL} Extract tarball. RUN tar xvf " " ${QEMU_TARBALL} Build source. RUN --static --target-list=arm-softmmu RUN make -j$(nproc) RUN strip "qemu- /configure" ${QEMU_VERSION} "arm-softmmu/qemu-system-arm" Build the intermediary VM app image. pidoc FROM ubuntu as pidoc-vm ARG RPI_KERNEL_URL= ARG RPI_KERNEL_CHECKSUM= "https://github.com/dhruvvyas90/qemu-rpi-kernel/archive/afe411f2c9b04730bcc6b2168cdc9adca224227c.zip" "295a22f1cd49ab51b9e7192103ee7c917624b063cc5ca2e11434164638aad5f4" Transfer binary from build container to app container. COPY --from=qemu-system-arm-builder /qemu/arm-softmmu/qemu-system-arm /usr/ /bin/qemu-system-arm local Download modified kernel and install. ADD /tmp/qemu-rpi-kernel.zip RUN apt-get update && \ apt-get -y install \ unzip \ expect RUN /tmp && \ | sha256sum -c && \ unzip qemu-rpi-kernel.zip && \ mkdir -p /root/qemu-rpi-kernel && \ cp qemu-rpi-kernel-*/kernel-qemu-4.19.50-buster /root/qemu-rpi-kernel/ && \ cp qemu-rpi-kernel-*/versatile-pb.dtb /root/qemu-rpi-kernel/ && \ rm -rf /tmp/* VOLUME /sdcard $RPI_KERNEL_URL cd echo " qemu-rpi-kernel.zip" $RPI_KERNEL_CHECKSUM Then we copy the entry point script from the host's main directory. ADD ./entrypoint.sh /entrypoint.sh ENTRYPOINT [ ] "./entrypoint.sh" Build the final app image with the Raspbian Lite filesystem loaded. pidoc FROM pidoc-vm as pidoc ARG FILESYSTEM_IMAGE_URL= ARG FILESYSTEM_IMAGE_CHECKSUM= ADD /filesystem.zip ADD pi_ssh_enable.exp /pi_ssh_enable.exp RUN | sha256sum -c "http://downloads.raspberrypi.org/raspbian_lite/images/raspbian_lite-2019-09-30/2019-09-26-raspbian-buster-lite.zip" "a50237c2f718bd8d806b96df5b9d2174ce8b789eda1f03434ed2213bbca6c6ff" $FILESYSTEM_IMAGE_URL echo " /filesystem.zip" $FILESYSTEM_IMAGE_CHECKSUM The entrypoint.sh File First, the script determines if the filesystem has been downloaded or not, and if not, it downloads and decompresses it. () { image_path= zip_path= [ ! -e ]; [ -e ]; unzip mv *.img rm 1 } #!/bin/sh raspi_fs_init "/sdcard/filesystem.img" "/filesystem.zip" if $image_path then echo "No filesystem detected at !" ${image_path} if $zip_path then echo "Extracting fresh filesystem..." $zip_path $image_path $zip_path else exit fi fi The script then checks for an empty file, which serves as a marker to determine if Expect has been launched previously to enable ssh on Raspbian. raspi-init [ ! -e /raspi-init ]; touch /raspi-init raspi_fs_init /usr/bin/expect /pi_ssh_enable.exp `hostname -I` if then echo "Initiating Expect..." echo "Expect Ended..." If Expect has already been previously enabled, then we only need to launch QEMU, without Expect. Note that we are forwarding port on Raspbian to port inside the Docker container. 22 2222 /usr/ /bin/qemu-system-arm \ --machine versatilepb \ --cpu arm1176 \ --m 256M \ --hda /sdcard/filesystem.img \ --net nic \ --net user,hostfwd=tcp:`hostname -I`:2222-:22 \ --dtb /root/qemu-rpi-kernel/versatile-pb.dtb \ --kernel /root/qemu-rpi-kernel/kernel-qemu-4.19.50-buster \ --append \ --no-reboot \ --display none \ --serial mon:stdio else local "root=/dev/sda2 panic=1" fi Enable SSHD on Raspbian (Expect Tcl/Tk Method) QEMU doesn't have a straightforward method for running configuration scripts on boot. And because Raspbian doesn't come with SSH enabled by default, we will have to turn it on ourselves. Our options are to do it manually or to use some sort of scripting tool that can interact with . stdio Another option is to customize the Raspbian image before installation. This would have to be done on the host, however, as Docker restricts the mounting of new filesystems. In any case, to make this build the most portable and host independent, the most straightforward for our purposes will be to use an script, and have it copied into our Docker image on build. Expect The pi_ssh_enable.exp File Since an unmodified Raspbian image has no accessible ports by default, we will use Expect to interface with in QEMU, log in with a default username and password, and enable the listener. stdio sshd ipaddr [lindex 0] timeout -1 spawn /usr/ /bin/qemu-system-arm \ --machine versatilepb \ --cpu arm1176 \ --m 256M \ --hda /sdcard/filesystem.img \ --net nic \ --net user,hostfwd=tcp: :2222-:22 \ --dtb /root/qemu-rpi-kernel/versatile-pb.dtb \ --kernel /root/qemu-rpi-kernel/kernel-qemu-4.19.50-buster \ --append \ --no-reboot \ --display none \ --serial mon:stdio expect send -- expect send -- expect send -- expect send -- expect expect eof #!/usr/bin/expect -f set $argv set local $ipaddr "root=/dev/sda2 panic=1" "raspberrypi login:" "pi\r" "Password:" "raspberry\r" "pi@raspberrypi:" "sudo systemctl enable ssh\r" "pi@raspberrypi:" "sudo systemctl start ssh\r" "pi@raspberrypi:" Build Image In the folder with the , we will be building our two containers. The first will be our build container that includes all the dependencies for compiling QEMU, and the other will be our app container for running QEMU. Dockerfile docker build -t pidoc . Network Forwarding and Troubleshooting Once the build is complete, bring it up detached and follow the logs. docker run -itd --name testnode pidoc docker logs testnode -f Raspbian will download and decompressed automatically, and QEMU should begin booting from the image. Once Raspbian is fully booted, Expect should automatically enable . Log into the docker container and test that SSH is reachable from inside the container on port . sshd 2222 root@d4abc2f655e6:/ 172.17.0.3 root@d4abc2f655e6:/ SSH-2.0-OpenSSH_7.9p1 Raspbian-10 # docker exec -it testnode bash # hostname -I # cat < /dev/tcp/172.17.0.3/2222 Cancel out and kill the container and remove the volume. root@d4abc2f655e6:/ testnode testnode # exit exit # docker kill testnode # docker container rm testnode Testing the Docker Container Start/Test Container We will need to start the container for testing. This is primarily to gain some understanding of the performance of QEMU so that we can better make design decisions regarding our cluster. The system should come up clean with maybe a few benign warnings related to differences between the somewhat more generalized emulated hardware and the expected physical raspberry Pi hardware. I found it necessary to make sure port forwarding was working properly between QEMU and the Docker image so that I could further verify that port forwarding between the Docker image and host was working properly. Our first goal is to double forward SSH so that QEMU is accessible directly from the host. docker run -itd -p 127.0.0.1:2222:2222 --name testnode pidoc docker logs testnode -f Once the system again comes online, test for on port of the host by using to log into Raspbian: sshd 2222 ssh The authenticity of host can [localhost]:2222 s password: Linux raspberrypi 4.19.50+ The programs included with the Debian GNU/Linux system are free software; the exact distribution terms each program are described the individual files /usr/share/doc/*/copyright. Debian GNU/Linux comes with ABSOLUTELY NO WARRANTY, to the extent permitted by applicable law. Last login: Tue Jan 21 12:24:59 2020 SSH is enabled and the default password the user has not been changed. This is a security risk - please login as the user and to a new password. pi@raspberrypi:~ $ # ssh pi@localhost -p 2222 '[localhost]:2222 ([127.0.0.1]:2222)' 't be established. ECDSA key fingerprint is SHA256:N0oRF23lpDOFjlgYAbml+4v2xnYdyrTmBgaNUjpxnFM. Are you sure you want to continue connecting (yes/no)? yes Warning: Permanently added ' ' (ECDSA) to the list of known hosts. pi@localhost' #1 Tue Nov 26 01:49:16 CET 2019 armv6l for in in for 'pi' 'pi' type 'passwd' set Testing Fractional CPU Utilization To run this cluster, we're using a GCP n1-standard-4 instance (a 4x15) running Ubuntu 18.04 LTS. But we now notice how inefficient QEMU is once Raspbian begins doing anything. Multiple Raspberry Pi instances might stack fine if their idle, but if we want to keep the system viable, we will need to restrict CPU utilization on each instance, or else the system could be rendered unusable once more than a few nodes are put under load. Fortunately, Docker can handle this for us. We have 15GB of ram on this instance, so let's see what happens if we are slightly more ambitious and squeezed 6 Raspberry Pi containers onto our VM. We will have a whole core left for the host to manage other tasks without much risk of a failure. We can scale this at some point later with Docker Compose. We will run two test containers at 50% and 100% for benchmark testing. docker run -itd --cpus= -p 127.0.0.1:2250:2222 --name pidoc_50_test pidoc docker run -itd --cpus= -p 127.0.0.1:2200:2222 --name pidoc_00_test pidoc "0.50" "1.00" At this point, we technically already have a cluster. We just don't have a method to manage them, except by hand. Performance While a full core allocation performs at near Physical Raspberry Pi speeds, an instance running at 50% runs rightly at half that speed. This might be manageable under certain circumstances, but it's not the most desirable. The overall efficiency of the cluster may increase, depending on the task at hand. But for now, we will continue with our original full core allocation of 3 nodes, and then later it tests with 6 nodes. Single Thread Benchmarks Testing can be done by using the following simple benchmark tests. CPU Prime Test sysbench -- =cpu --cpu-max-prime=9999 run test CPU Integer Test time $(i=0; ((i<9999999)); ((i++)); ) while do done HDD Read Test dd bs=16K count=102400 iflag=direct =test_data of=/dev/null if HDD Write Test dd bs=16k count=102400 oflag=direct =/dev/zero of=test_data if Results (Single Thread) For this guide, we will only focus on the CPU Prime Test using sysbench Host General statistics: total time: 10.0009s total number of events: 9417 Latency (ms): min: 1.04 avg: 1.06 max: 1.63 95th percentile: 1.10 sum: 9992.36 Threads fairness: events (avg/stddev): 9417.0000/0.00 execution time (avg/stddev): 9.9924/0.00 Virtual Raspberry Pi - Limit: 100% Test execution summary: total time: 397.8781s total number of events: 10000 total time taken by event execution: 397.4056 per-request statistics: min: 38.61ms avg: 39.74ms max: 57.15ms approx. 95 percentile: 40.92ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 397.4056/0.00 Virtual Raspberry Pi - Limit: 50% Test execution summary: total time: 823.8272s total number of events: 10000 total time taken by event execution: 822.9329 per-request statistics: min: 38.68ms avg: 82.29ms max: 184.02ms approx. 95 percentile: 94.65ms Threads fairness: events (avg/stddev): 10000.0000/0.00 execution time (avg/stddev): 822.9329/0.00 Compose the Cluster Create docker-compose.yml File We will use Docker Compose for cluster creation. Initially, we will keep this at three nodes to keep it easy to manage. Once we have a proof of concept cluster, we can then scale it out. The most straightforward way to handle this is to map separate ports to localhost for each container. We can specify a range of ports to be used in the file, as noted below. docker-compose.yml version: services: node: image: pidoc ports: - '3' "2201-2203:2222" Bring Up Cluster To bring up three nodes with , use the option. docker-compose --scale docker-compose up --scale node=3 Ansible Configuration Now that we have all the infrastructure in place for a cluster, we need to manage it. We could use Docker to double attach to the QEMU monitor, but ssh is much more robust. Since we are using , we can use Ansible. A few basic operations are provided here: , , , and . These can be expanded as needed to develop a more robust system. ssh update upgrade reboot shutdown hosts File Please note of the ports we specified in the file earlier, and edit your inventory accordingly. docker-compose.yml hosts [all:vars] ansible_user=pi ansible_ssh_pass=raspberry ansible_ssh_extra_args= [pidoc-cluster] node_1.localhost:2201 node_2.localhost:2202 node_3.localhost:2203 '-o StrictHostKeyChecking=no' For a more comprehensive walkthrough of Ansible, please read . How to Install and Configure Ansible on Ubuntu update.yml File --- - name: Apt update Pi... hosts: pidoc-cluster tasks: - name: Update apt cache... become: yes apt: update_cache=yes Usage: ansible-playbook playbooks/update.yml -i hosts upgrade.yml File --- - name: Upgrade Pi... hosts: pidoc-cluster gather_facts: no tasks: - name: Update and upgrade apt packages... become: apt: upgrade: yes update_cache: yes cache_valid_time: 86400 true Usage: ansible-playbook playbooks/upgrade.yml -i hosts reboot.yml File --- - name: Reboot Pi... hosts: pidoc-cluster gather_facts: no tasks: - name: Reboot Pi... shell: shutdown -r now async: 0 poll: 0 ignore_errors: become: - name: Wait reboot... local_action: wait_for host={{ ansible_host }}state=started delay=10 become: true true for false Usage: ansible-playbook playbooks/reboot.yml -i hosts shutdown.yml File --- - name: Shutdown Pi... hosts: pidoc-cluster gather_facts: no tasks: - name: shell: shutdown -h now async: 0 poll: 0 ignore_errors: become: - name: local_action: wait_for host={{ ansible_host }} state=stopped become: 'Shutdown Pi' true true "Wait for shutdown..." false Usage: ansible-playbook playbooks/shutdown.yml -i hosts Scaling Up Docker Compose makes scaling Raspberry Pi containers on the same host near trivial. By using Ansible for cluster management, it also becomes incredibly easy to scale horizontally to other hosts by changing the port binding from localhost to an IP address that's routable. Here is our example with 6 nodes instead of 3. docker-compose.yml File version: services: node: image: pidoc ports: - deploy: resources: limits: cpus: '3' "2201-2212:2222" "0.5" Bring Up Cluster We should stop containers from our previous cluster, and prune all volumes before scaling up our revised cluster. To bring up all 6 nodes with , use the option again. docker-compose --scale docker-compose up --scale node=5 Future Work Raspberry Pi emulation is still under development for QEMU. While the configuration for this project is relatively stable, there's a lot of room for improvement. Attempting a migration to Raspberry Pi 3 emulation would be an ambitious next step. Docker Compose, though designed for single-host builds, is already easy enough to replicate to other hosts manually or through Ansible. But it could just as easily be scaled out with or k8s, enabling us to build an emulated Raspberry Pi cluster of any size. Swarm Additionally, with one or more port redirects, other systems of control can be put into place, including various node endpoints, depending on purpose and application. This article was originally published on https://appfleet.com/blog/raspberry-pi-cluster-emulation-with-docker-compose/ .