You have programmed for a few years and have cluttered up your sandbox, your local development machine, with downloads of many different libraries, frameworks, and maybe a virus or two.
The above described my life in 2008. The arduous tasks below detail the giant PIA (you are on your own to resolve the acronym) in my life at the time:
As part of the AI 1.0 surge (1983–1987), I felt that AI, to be of practical use, had to be distributed. Since then, I have been building distributed operating systems.
I admit I stopped when I encountered Kubernetes in 2016 because from a Software Architect and Engineer viewpoint, there was little I could add, and what I could add would be minor.
Yes, I think Kubernetes is a great distributed operating system architecture for a cloud of virtual machines (VMs) to a hive of Rasberry Pis.
I returned to Machine Learning about nine years ago during the AI 2.0 …
I was taught to transform a complex problem into a simpler problem, by dividing the problem into smaller sub-problems.
I made the process paradigm of Machine Learning Operations (MLOps) simpler by dividing it into five different, but overlapping process groups or Operations (Ops) groups.
MLOps is automating the Machine Learning product life cycle.
In 1990, we had 80%+ IT projects that were never rolled out. Failure rate dropped because of standardized developer tools, repeatable process iteration, death of the Waterfall method, a rise of the Agile method, and unit testing — to list some of the code development advances.
I plan to increase stability and performance and to decrease the cost of maintenance in the Photonai code base. I add clustering functionality to the original code base and change the architecture.
A small code refactoring task is usually fixing bugs. Some consider that it is not refactoring if the bug-fixing occurs before releasing to test.
A significant code refactoring project example is causing a program to be Y2K-compliant but not changing functionality. Y2K compliance is enabling code to operate correctly with dates at or beyond January 1, 2000. (Yes, this was a thing!)
Python is a dynamically typed language. However, starting with Python 3.5 (PEP 484), type hints were introduced. Type hints (note: not strong type checking) make it possible, post coding of Python, to do static type checking of code.
Here’s a great figure showing the evolution of Python type hinting:
There is a dominating idea that extinction events occur suddenly. However, Climate Change Heating, a possible extinction event is occurring over decades. In the context of investing for a decade or more, these are my ideas for the Climate Change Heating macro event.
Almost all the international participation proposals detail how to slow down Climate Change Heating (CCH).
Most people, who think the climate is heating up adversely, believe that technology will save our butts from CCH.
What does the…
I refer to
kubectl often throughout this blog article.
kubectl is your local command-line interface (CLI) for exchanging declarative or imperative directives with a single Kubernetes cluster. The Kubernetes cluster is on your local sandbox; we use Minikube or remotely by the network.
A summary of most
kubectl commands are:
kubectl throughout this blog article, I also use
Minikube is a popular tool to train with or test Kubernetes on your local workstation(s).
Minikube is how you run Kubernetes on your local computer(s).
I think of Minikube as a…
An explanation and usage of Kubernetes should not discuss internal architectural components. Instead, I discuss Kubernetes basic concepts with code examples. In the end, as a bonus, Kubernetes has a glaring hole in its design.
Whether a single person, startup, or mega-corp, there will be a small number of users on your first day of offering your application to the public.
What about the second day or the third week? Will it be a dud or go viral?
Viral means lots of users. You have to develop and test the software to spread the increasing user load across the computing…
Literate programming is a superset of DevOps or Change Integration/Change Deployment (CI/CD). I detail how to implement literate programming by customizing nbdev for existing Github repositories. Example code can be used for other vendor repositories, such as Gitlab and Bitbucket.
Literate programming is a programming paradigm introduced by Donald Knuth in which a computer program is given an explanation of its logic in a natural language, such as English, interspersed with snippets of macros and traditional source code, from which compilable source code can be generated — Wikipedia
Literate programming, as originally conceived, places documentation, code, and test together in…
The Docker image for our Jupyter Python and R users required them to set their
Nbextensions preferences after every launch. We were able to increase Jupyter notebook user productivity by setting commonly used
Nbextensions preferences in the Docker image.
We have a shared disk where anybody can copy the template files to their local directory structure.
Each member of Dev and Test copies Release 1.3.0
dockerSeasons directory over to their