ANZ Pied Piper

In the previous article I provided details on VeeFarm which was one of the best projects we saw in ANZ Pied Piper 2019 edition and one of the best projects in the history of the program. The program inspired me and others to work together to showcase a great idea and the Pied Piper program itself during our presales conference. An idea I suggested to enhance VeeFarm was an electronic nose that could be used to detect the optimal ripening of the produce to advise the owner that it is the right time to pick it up the produce. This is an idea I had in the backburner for a while but never found the time to work on. Vee gave me the perfect excuse. The electronic nose, or eNose for short, is a custom PCB that hosts a range of gas sensors. For the proof of concept, I used the cheap MQ sensors. These are designed mostly for hobbyists and makers and they barely cost $1 per sensor. As one could expect, tweaking and calibrating these sensors it is even harder than the most expensive counter...

2019 has been another very hectic year and part of that has been the Pied Piper program again. This year I have run the program at Australia first and then in Japan. In both locations there was a phenomenal vibe and great feedback. During the Australian session we changed the curriculum to learn the new skills required to develop the ASDAC Service Dog app  as a team. We postponed the remaining topics that were not relevant to the app for a month and only then kicked off the traditional personal project competition. The consequence was that that we saw less projects than usual as participants found it hard to remain engaged in spite of their normal commitments. But the projects we got were some of the most mature projects ever, given that at that stage the surviving participants were seasoned in many areas For example, we saw Jonas Werner’s project, which was the best project of all time. He completed a project so vast that he had to break it down into 4 loosely related discret...

I have recently published the following repo in GitHub https://cermegno.github.io/ServiceDogsApp/ This repo contains the code produced by the students of the Pied Piper program that took place in Sydney in June 2019. A total of 14 students from Australia, New Zealand and Japan participated in the program and contributed their code to this project The Pied Piper program The Pied Piper program goal is to educate DellEMC pre-sales across APJ and Greater China regions in the various technologies that are fuelling the digital transformation such as Cloud Native apps, Agile, DevOps, IoT and analytics/AI. What makes this program different is that engineers learn by doing (approximately 85% of the 5-day workshop is hands-on). By focusing on doing instead of just listening or reading the learning outcomes are much greater The program gets its name from the Sillicon Valley TV series that portraits a group of young guys in California that found a start-up called Pied Piper. In order to...

Lately I have been working with Kubernetes during the preparation of a new course. In the past, when I needed a Kubernetes cluster I used one of the cloud providers. GCP is specially good for Kubernetes but my trial account run out. Besides, this course requires me to do some things with VMware, so I had to create my own environment a few times in the lab on top of vSphere. During this time, I couldn’t find any other references that worked for me 100% so I decided to write this article with the few tricks that I have learnt A word of caution, during this process you will be doing things like lowering the security of your virtual machines so that the cluster installs more easily. So please do use this procedure only for development environments and at your own risk To understand what you are doing it helps to be a little bit familiar with the Kubernetes architecture. You are going to need one Virtual Machine for every not you want in your cluster. There are two types of nodes: M...

In recent years, as cloud operating models have become more pervasive, organisations have started to adopt DevOps culture and processes to break previously existing organisational silos such as Development, Operations and QA. A key element for this transition is to treat Infrastructure as Code and to employ specialised automation tools. This is reporting benefits such as: Improved agility by eliminating manual or siloed tools which translates in significant reduction of provisioning times Minimise provisioning errors       Ensure consistency Ability to manage larger environments typically associated with scale-out microservices architectures Lower operational cost  The right choice of tool is essential to achieve these outcomes. Instead of leveraging element-specific scripting tools organisations need to move towards automation tools that can: address the configuration of large parts of the infrastructure so that multiple teams can “speak” the same la...

In a previous post we saw the basic usage of " cf push " to bring your Python script to Pivotal Cloud Foundry and running it. The only parameter we used at the time was the application name. If for example we did: cf push pretty_app1 This meant that our app would be accessible with " http://pretty_app1.cfapps.io ". Not to be confused with the name of the actual Python script, ex: " app.py " When we run this we got an instance with a certain default characteristics, ie  1GB RAM and 1GB of disk. Given that Pivotal bills you based on the memory used by your apps, you might want to be more specific about that, specially in our "hello world" app which requires little resources. You can see the health of your app as follows. In my case we can see it only requires 17MB of RAM, so 1GB is a huge waste. Luckily the " cf " cli tool has lots of options. You can explore them by simply typing " cf --help " or to see the opt...

Nowadays there are so many hot new technologies that is getting hard to sleep at night. One of those technologies I have been recently looking into is Deep Learning. During the process I have come across some pretty good resources which are worth sharing. If DL is something you want to explore tune in. What I am recommending here can be done over a weekend. That investment will certainly not turn you into a seasoned Data Scientist but you will get enough to be dangerous. From the outside it looks like a harsh topic but what I have found is that when explained right it is not the "mission impossible" that looks from the outside Deep Learning refers to the use of Neural Networks with several hidden layers. That's what make it "deep". So for me the logical place to start is Neural Networks, in particular try to understand the concepts. While trying to do just that I have come across this amazing channel in Youtube called “3Blue1Brown”. I don't know how els...