The Rise of Pico: At the Grace Hopper Celebration India

The Grace Hopper Celebration of Women in Computing (GHC) is a series of conferences designed to bring the research and career interests of women in computing to the forefront. It is the world’s largest gathering of women in computing. The celebration, named after computer scientist Grace Hopper, is organized every year by the Anita Borg Institute for Women and Technology and the Association for Computing Machinery.

This year, the conference took place in Bangalore International Exhibition Center( the third consecutive year at this venue) from November 6-8, 2019. The conference accommodated around 5000+ attendees. It was a combination of technical sessions and workshops. It included career sessions, expos, poster session, career fair, awards ceremony, and much more.

What’s Pico all about??

Pico is an open source project which helps in implementing object detection & analytics(Deep Learning) using Docker on IoT devices like Raspberry Pi & Jetson Nano in just simple 3 steps. Imagine you are able to capture live video streams, identify objects using deep learning, and then trigger actions or notifications based on the identified objects – all using Docker containers. With Pico, you will be able to setup and run a live video capture, analysis, and alerting solution prototype. A camera surveils a particular area, streaming video over the network to a video capture client. The client samples video frames and sends them over to AWS, where they are analyzed and stored along with metadata. If certain objects are detected in the analyzed video frames, SMS alerts are sent out. Once a person receives an SMS alert, they will likely want to know what caused it. For that, sampled video frames can be monitored with low latency using a web-based user interface.

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The Pico framework uses Kafka cluster to acquire data in real-time. Kafka is a message-based distributed publish-subscribe system, which has the advantages of high throughput and perfect fault-tolerant mechanism. The type of data source is the video that generated by the cameras attached to Raspberry Pi.

This year I submitted proposal for workshop on Pico during June-July along with 3 other DellEMC Engineers. The submission was selected for GHCI conference during the initial week of August 2019. This was our first workshop submission and we were super happy about the news. We confirmed our participation during the early week for September. There were multiple submissions for final Program Material during 2nd week of September. The final Program Materials was submitted on Linklings. This included the profiles and headshots of all the speakers in the session.

During the mid-September, I started building workshop material for Pico. The workshop consisted of 4 separate modules:

  • Installing Docker on Raspberry Pi 4
  • Setting up Apache Kafka on Cloud
  • Setting up Pico
  • Testing Object Detection

You can get access to this workshop under

Finally… It’s Pico Day

The workshop was scheduled on 8th November and around 80+ attendees attended this workshop. Over 8 Raspberry Pis were arranged per table and it helped attendees to try out CLIs to install Docker on Raspberry Pi. Apache Kafka was pre-installed on AWS Cloud along with Image Processor and consumer scripts. I showcased a LIVE demo where camera module attached to Raspberry Pi was able to detect the audience as “Boxes of People”.

Overall, it was an amazing experience being part of GHCI and running workshop for such a huge audience. It was great to receive loads of positive feedback from the organizers too. Representing DellEMC in such a BIG conference made us feel proud and we went back home collecting lots of appreciation to prepare ourself for the forthcoming events in the near future.


Thanks to Prashant Ksr, Priti Parate & Varalakshmi for all the support for making this happen. Thanks to GHCI organizer for this opportunity and believing on this promising project work. Thank you.

Want to learn more about Pico?

Head over to

If you want to collaborate around Pico project, visit and join 1600+ community Slack members to discuss further. Looking forward to see you there.

Installing Docker Engine 19.03 on Raspberry Pi 3 in 2 Minutes

Docker is officially supported both on Raspberry Pi 3 and 4. Installing Docker is just a matter of single-liner command. All you need to do is a simple curl command:

curl -sSL | sh

to get Docker binaries installed flawlessly. Isn’t it damn simple?

Raspbian is a free operating system based on Debian optimized for the Raspberry Pi hardware. An operating system is the set of basic programs and utilities that make your Raspberry Pi run. However, Raspbian provides more than a pure OS: it comes with over 35,000 packages, pre-compiled software bundled in a nice format for easy installation on your Raspberry Pi.

Docker today support the latest Raspbian Buster release. If you really want to play around with stable release of Docker for Raspbian Buster, then head over to this link.

Under this blog post, I will showcase how to install latest Docker Engine 19.03.1 on Raspbian OS Buster release flawlessly.

Tested Infrastructure

PlatformNumber of InstanceReading Time
Raspberry Pi 3 Model B15 min

Preparing Your Environment

Raspberry Pi 3 Model BBuy

Waveshare-LCD 5-inch TFT Resistive
Touch Screen Display Module

Geauxrobot Raspberry Pi 3 Model B 7-Layer
Dog Bone Stack Clear Case Box 


  • Flash Raspbian OS on SD card

If you are in Mac, you might need to install Etcher tool. If on Windows, install SDFormatter to format SD card as well as Win32installer to flash Raspbian ISO image onto the SD card. You will need SD card reader to achieve this.

Booting up Raspbian OS

Just use the same charger which you use for your mobile to power on Raspberry Pi box. Connect HDMI port to your TV or display. Let it boot up.

The default username is pi and password is raspberry.

Enable SSH to perform remote login

To login via your laptop, you need to allow SSH service running. You can verify IP address command via ifconfig command.

[Captains-Bay]🚩 >  ssh pi@
pi@'s password:
Linux raspberrypi 4.14.98-v7+ #1200 SMP Tue Feb 12 20:27:48 GMT 2019 armv7l

The programs included with the Debian GNU/Linux system are free software;
the exact distribution terms for each program are described in the
individual files in /usr/share/doc/*/copyright.

Debian GNU/Linux comes with ABSOLUTELY NO WARRANTY, to the extent
permitted by applicable law.
Last login: Tue Feb 26 12:30:00 2019 from
pi@raspberrypi:~ $ sudo su
root@raspberrypi:/home/pi# cd

Verifying Raspbian OS Version

root@raspberrypi:~# cat /etc/os-release
PRETTY_NAME="Raspbian GNU/Linux 9 (stretch)"
NAME="Raspbian GNU/Linux"
VERSION="9 (stretch)"

Installing Docker 19.03.1

Its a single liner command. -L means location, -s means silent and -S means show error.

root@raspberrypi:~# curl -sSL | sh

Deploying Nginx App

root@raspberrypi:~# docker run -d -p 80:80 nginx
Unable to find image 'nginx:latest' locally
latest: Pulling from library/nginx
9c38b5a8a4d5: Pull complete
1c9b1b3e1e0d: Pull complete
258951b5612f: Pull complete
Digest: sha256:dd2d0ac3fff2f007d99e033b64854be0941e19a2ad51f174d9240dda20d9f534
Status: Downloaded newer image for nginx:latest
root@raspberrypi:~# curl localhost:80
<!DOCTYPE html>
<title>Welcome to nginx!</title>
    body {
        width: 35em;
        margin: 0 auto;
        font-family: Tahoma, Verdana, Arial, sans-serif;
<h1>Welcome to nginx!</h1>
<p>If you see this page, the nginx web server is successfully installed and
working. Further configuration is required.</p>

<p>For online documentation and support please refer to
<a href=""></a>.<br/>
Commercial support is available at
<a href=""></a>.</p>

<p><em>Thank you for using nginx.</em></p>
root@raspberrypi:~# docker info
Containers: 1
 Running: 1
 Paused: 0
 Stopped: 0
Images: 1
Server Version: 19.03.1
Storage Driver: overlay2
 Backing Filesystem: extfs
 Supports d_type: true
 Native Overlay Diff: true
Logging Driver: json-file
Cgroup Driver: cgroupfs
 Volume: local
 Network: bridge host macvlan null overlay
 Log: awslogs fluentd gcplogs gelf journald json-file local logentries splunk syslog
Swarm: inactive
Runtimes: runc
Default Runtime: runc
Init Binary: docker-init
containerd version: 9754871865f7fe2f4e74d43e2fc7ccd237edcbce
runc version: 09c8266bf2fcf9519a651b04ae54c967b9ab86ec
init version: fec3683
Security Options:
  Profile: default
Kernel Version: 4.14.98-v7+
Operating System: Raspbian GNU/Linux 9 (stretch)
OSType: linux
Architecture: armv7l
CPUs: 4
Total Memory: 927.2MiB
Name: raspberrypi
Docker Root Dir: /var/lib/docker
Debug Mode (client): false
Debug Mode (server): false
Experimental: false
Insecure Registries:
Live Restore Enabled: false
Product License: Community Engine

WARNING: No memory limit support
WARNING: No swap limit support
WARNING: No kernel memory limit support
WARNING: No oom kill disable support
WARNING: No cpu cfs quota support
WARNING: No cpu cfs period support

BuildKit on Raspberry Pi

root@raspberrypi:~# export DOCKER_BUILDKIT=1
root@raspberrypi:~# git clone
Cloning into 'hellowhale'...
remote: Enumerating objects: 28, done.
remote: Total 28 (delta 0), reused 0 (delta 0), pack-reused 28
Unpacking objects: 100% (28/28), done.
root@raspberrypi:~# cd hellowhale/
root@raspberrypi:~/hellowhale# ls
Dockerfile  html
root@raspberrypi:~/hellowhale# docker build -t ajeetraina/hellowhalecom .
[+] Building 7.9s (5/8)                                                         
 => [internal] load build definition from Dockerfile                       0.1s
 => => transferring dockerfile: 129B                                       0.0s
 => [internal] load .dockerignore                                          0.2s
 => => transferring context: 2B                                            0.0s
 => [internal] load metadata for            0.0s
 => [1/3] FROM                              0.0s
 => => resolve                              0.0s
 => [internal] helper image for file operations                            0.1s
 => => resolve  7.5s
 => => sha256:b13ecc473b58ad8d80fba73ae6de690f6fcbe341bdaca42 736B / 736B  0.0s
 => => sha256:fabe16b757ee155dfd7210795199962d1b35e22b3437d06 767B / 767B  0.0s
 => [internal] load build context                                          0.1s
 => => transferring context: 34.39kB                                       0.0s

root@raspberrypi:~/hellowhale# time docker build -t ajeetraina/hellowhale .
[+] Building 0.4s (9/9) FINISHED                                                
 => [internal] load build definition from Dockerfile                       0.1s
 => => transferring dockerfile: 31B                                        0.0s
 => [internal] load .dockerignore                                          0.1s
 => => transferring context: 2B                                            0.0s
 => [internal] load metadata for            0.0s
 => [internal] helper image for file operations                            0.0s
 => [1/3] FROM                              0.0s
 => [internal] load build context                                          0.0s
 => => transferring context: 317B                                          0.0s
 => CACHED [2/3] COPY /                                         0.0s
 => CACHED [3/3] COPY html /usr/share/nginx/html                           0.0s
 => exporting to image                                                     0.1s
 => => exporting layers                                                    0.0s
 => => writing image sha256:5aee990f7e24e7c0f486ed01b4c1f8696ff307f836af1  0.0s
 => => naming to                           0.0s

real	0m0.615s
user	0m0.204s
sys	0m0.082s

Verifying Dockerd

root@raspberrypi:~/hellowhale# systemctl status docker
● docker.service - Docker Application Container Engine
   Loaded: loaded (/lib/systemd/system/docker.service; enabled; vendor preset: e
   Active: active (running) since Tue 2019-02-26 13:01:04 IST; 38min ago
 Main PID: 2437 (dockerd)
      CPU: 1min 46.174s
   CGroup: /system.slice/docker.service
           ├─2437 /usr/bin/dockerd -H unix://
           ├─2705 /usr/bin/docker-proxy -proto tcp -host-ip -host-port 8
           └─4186 /usr/bin/docker-proxy -proto tcp -host-ip -host-port 8

Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.400368104+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.402012958+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.402634316+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.403005881+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.408358205+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.810154786+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.810334839+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.811462659+0
Feb 26 13:37:06 raspberrypi dockerd[2437]: time="2019-02-26T13:37:06.811768546+0
Feb 26 13:37:07 raspberrypi dockerd[2437]: time="2019-02-26T13:37:07.402282796+0

Verifying if armv7 hello-world image is available or not

docker run --rm mplatform/mquery hello-world
Unable to find image 'mplatform/mquery:latest' locally
latest: Pulling from mplatform/mquery
db6020507de3: Pull complete
5107afd39b7f: Pull complete
Digest: sha256:e15189e3d6fbcee8a6ad2ef04c1ec80420ab0fdcf0d70408c0e914af80dfb107
Status: Downloaded newer image for mplatform/mquery:latest
Image: hello-world
 * Manifest List: Yes
 * Supported platforms:
   - linux/amd64
   - linux/arm/v5
   - linux/arm/v7
   - linux/arm64
   - linux/386
   - linux/ppc64le
   - linux/s390x
   - windows/amd64:10.0.14393.2551
   - windows/amd64:10.0.16299.846
   - windows/amd64:10.0.17134.469
   - windows/amd64:10.0.17763.194

Verifying Hellowhale Image

root@raspberrypi:~# docker run --rm mplatform/mquery ajeetraina/hellowhale
Image: ajeetraina/hellowhale
 * Manifest List: No
 * Supports: amd64/linux

Verifying Random Images

root@raspberrypi:~# docker run --rm mplatform/mquery rycus86/prometheus
Image: rycus86/prometheus
 * Manifest List: Yes
 * Supported platforms:
   - linux/amd64
   - linux/arm/v7
   - linux/arm64

In my next blog post, I will showcase how to setup Docker Swarm on bunch of Raspberry Pi 3 nodes.

Test-Drive Docker 1.12 on first 64-bit ARM OpenSUSE running on Raspberry Pi 3

Raspberry Pi 3 Model B is the first 64 bit version and the third generation Pi box which runs on 1.2GHz 64 bit quad-core ARMv8 CPU.(Broadcom BCM2837 A53 ARM processor). Despite its processor upgrade, there wasn’t an official 64-bit OS available for it till the first week of Jan 2017. Kudos to SUSE Team, they came up providing first commercial enterprise Linux distribution optimized for ARM AARCH64 servers. This is definitely a BIG news. Reason –  To build a solution to meet specific market needs while maintaining a common code base. Enterprise vendors & customers demanding workload-optimized server platforms can now radically expand it for their modern data centers.


In the last couple of months, Docker enthusiasts have been working hard to get Docker running on ARM 32bit systems (like Raspberry Pi). With Docker Engine 1.12.1, a FIRST ARM Debian package was officially made available by Docker Inc. which happened late last year. This year, SUSE Team did a great job in bringing capabilities of SUSE Linux(a.k.a SLES for ARM) to the ARM AArch64 hardware platform. This is BIG news for Docker community too as more innovation and development is expected to grow building containers which will run across the  AARCH64 platform.

Under this blog, I am going to test drive Docker 1.12.3 on first 64-bit ARM Open SUSE distribution running on Raspberry Pi 3 box.


  1. Raspberry Pi 3 ( You can order it from Amazon in case you are in India for $35)
  2. Micro-SD card reader ( I got it from here )
  3. Any Windows or Linux Desktop or Laptop
  4. HDMI cable ( I used the HDMI cable of my plasma TV)
  5. Internet Connectivity(WiFi/Broadband/Tethering using Mobile) – to download Docker 1.12.3 package
  6. Keyboard & mouse connected to Pi’s USB ports




  1. SD-Formatter – to format microSD card
  2. Rufus(in case you have Windows OS running on your laptop) – to burn OpenSUSE Leap 42.2 ARM XZ format directly into microSD card.(No need to extract XZ using any tool)


  1. Format the microSD card using SD Formatter as shown below:


2. Download OpenSUSE Leap 42.2 ARM  OS from here and use Win32 imager(in case you are on Windows OS  running on your laptop) to burn it on microSD card.


3. Insert the microSD card into your Pi box. Now connect the HDMI cable  from one end of Pi’s HDMI slot to your TV or display unit and mobile charger(recommended 5.1V@1.5A) as shown:


4.You will see the fancy GUI coming up on your display:


5. To enable VNC, run the below command:

linux:~ # zypper install xorg-x11-Xvnc

linux:~# vncserver

Installing Docker 1.12.3 on first 64-bit ARM OpenSUSE

6. Run the below command:

$curl -sSLk | sh


7. Verify the docker version:


8. Let us try searching for Docker images present in Dockerhub based on aarch64:


Please be aware that the usual Docker containers are not going to work for this architecture. You need to pick up AARCH64 bit Docker images to run containers.

linux:~ # docker run busybox
Unable to find image ‘busybox:latest’ locally
latest: Pulling from library/busybox

557a0c95bfcd: Pull complete
Digest: sha256:ae007bdb45fc0d56e3d705b97640ac24844bcc9ce4c8b8493f216a57ab6af0d5
Status: Downloaded newer image for busybox:latest
panic: standard_init_linux.go:175: exec user process caused “exec format error” [recovered]
panic: standard_init_linux.go:175: exec user process caused “exec format error”

goroutine 1 [running, locked to thread]:
panic(0x7bcaa0, 0x4820161ce0)


Installing Docker 1.13 on 64-bit ARM OS:

Docker doesn’t officially support AARCH64 system. You can’t use one-liner command to install Engine 1.13 as shown below:

Untitled picture

If you really want to try 1.13, the easier way is downloading it from the below link:


Installing docker-compose

linux:~ # zypper install python-pip

linux:~ # pip install docker-compose

Tested docker-compose v2.0 functionality by bringing up microservices and it went fine.


Testing Swarm Mode:



linux:~/collabnix # docker service ls
ID            NAME        REPLICAS  IMAGE          COMMAND
0x7dlmr4pjm7  backend-db  1/1       aarch64/redis

linux:~/collabnix # docker service ps backend-db
ID                         NAME          IMAGE          NODE   DESIRED STATE  CURRENT STATE                 ERROR
7jmkwcbzq8wix3umfkcqc92rw  backend-db.1  aarch64/redis  linux  Running        Preparing about a minute ago