Relying upon the illusion of totally deterministic hardware and the subsequent locally optimal software design does not persist at scale.

5D hypercube here thanks to a lineage of a James after a Paul who was before a Peter following Oliver [most recently from the 5dstm, 5-dimensional Space-Time-Matter Consortium].

When engaging computational systems at scale these issues are undeniably common knowledge. So we have google to thank for open sourcing their Kubernetes project, circa 2015.

Enter Kubernetes:

Kubernetes Tribute here created by mini/dall-e model from huggingface

Kubernetes, a container orchestration system for automating software deployment, scaling, and management. Kubernetes delivers a more resilient and robust architecture.

This has allowed for the scaling of systems to:

While being administered and managed through interfaces like:

The cluster architecture is able to accomplish some more complex behaviors like self healing and some self organization.

Lens has a nice visualization extension which gives a visual rendering of the pods and their direct networked connections with one another in a 2d slice. This is a compilation of recording from a few other clusters, some much larger than this 10 rpi 4b shown in the other tools examples.

[Ku]bernetes tools

Lens also has decent ui/ux for administering and monitoring clusters.


K9s is a cli-console based program for management and administration


Arguably the smoothest administrator interface experience is with Kubenav from your cellphone or desktop.

Longhorn: distributed block storage

Longhorn allows for basically single command setup of dynamically sized distributed block storage for k8s.

To flesh out this topic area going to split into a couple more posts, to be cont. […]


efficiency, resiliency, reproducibility

Found a helpful script for templating virtual machines on proxmox hosts

Added value: automated, fast, templating, now including integrity checking without missing a beat

Kinetic Kudu[ubuntu 22.04 cloudimg] psionic non-voodoo

Republishing: templating with integrity checking, {con}templation in accord with integrity is in accord with excellence, Aristotle meet virtual machines running virtual machines running containerized images of machines. Going to have to change the site tag to projects, programming and puns.

The Visual-Cortex, a powerful graphics-engine? Expensive compute–


Programming 3D environments without many high level libraries makes clear why the visual-cortex is so large! [expensive it is to compute graphics?] Below are some excerpts of the low level of objects written to build from the ground up, everything. From vertex to triples, to triangles, and beyond– not recommended for anything besides painful learning. Especially with the verbosity of Java, here’s part of a triple class.

import java.nio.FloatBuffer;
import java.util.Scanner;

public class Triple
public double x, y, z;
public Triple( double a, double b, double c ) {
x = a; y = b; z = c;
public Triple( Scanner input ) {
x = input.nextDouble();
y = input.nextDouble();
z = input.nextDouble();

public void sendData( FloatBuffer buff ) {
buff.put( (float) x );
buff.put( (float) y );
buff.put( (float) z );

Finally built the castle in the sky

Which is then a part of a single vertex, like below; then with three vertices of 2 triple’s…. *drum roll* we can create a single shaded triangle.

import java.nio.FloatBuffer;
import java.util.Scanner;

public class Vertex {
private Triple position;
private Triple color;
public Vertex( Triple p, Triple c ) {
position = p;
color = c;
public Vertex( Scanner input ) {
position = new Triple( input );
color = new Triple( input );
public void sendData( FloatBuffer pb, FloatBuffer cb ) {
position.sendData( pb );
color.sendData( cb );

What is a world? What does it mean to have a world space and a horizon, Res Extensa. It turns out its not really that complicated or difficult to simulate a world, depending on resolution and complexity it can be computationally extensive.

Intimating the major elements involved in rendering a world and a 3-dimensional view point from within that space.


How about simulating many individual agents, each acting according to their own internal rules based on the limited knowledge they have from their perspective [keeping this a bit simpler than game theory with humans]. Two dimensions is plenty, below demonstrates some interesting, beautiful behavior emerging from just 3 simple rules.

This is a python variation I wrote of Craig Reynolds, ‘boids’ algorithm from 1986. The behavior is determined by just 3 rules which each of the boids, or particles in this case, follows for itself. I ran this on my iPad and the compute slowed it to barely a crawl, I sped up the screen recording for this high action production.

There is actually one more rule here, a 4th force helping to keep them on the screen

  • separation: steer to avoid crowding local flock
  • alignment: steer towards the average heading of local flock
  • cohesion: steer to move towards the average position (center of mass) of local flock

Some simple programs like these [even simpler], are turing complete and some sets of rules even create seemingly never ending complexity. If that sounds totally insane then you need to visit Stephen Wolfram’s work.


This is a short little clip from recording the p5js program I uploaded onto a page of my blog on the left side. It allows for the variables controlling length of joining and acceleration/deceleration to be adjusted.


The following ones are also boids variants, these inspired by some of Daniel Shiffman’s work in his book on simulation nature . It has two flocks with different ranges of starting characteristics, also interactively, tapping the screen adds to each flock. A long screen press toggles what I call visualized entropic mode, were the history of the biods movements is retained. Then shaking the device will clear the screen. I built an APK for Nethunter and one for the Graphene android I had been been working on.

Clearly they behave in some very interesting ways despite being incredibly simple.

Another beautiful visual, the data for this was passively collected from all wireless signals within range.

The local neighborhood, in terms of wireless access points and clients, explored in 3D.

M.2 Boot Pi 4 Hirsute Hippo EZ/PZ, Great relief.

Why SSD drives just to USB boot? A little bit faster and a lot more stable.

Why a more stable raspberry pi?

This is a large search space.. Running a node for Web 3.0 services, a node for any decentralized infrastructure, DeFi, IPFS, the Graph, ETH[…]

After following several tutorials which failed along with thousands of line of code dedicated to automating the setup for USB boot from a sata drive [transferring or cloning from an SD card] it felt like duty to write a quick post. I hope this saves someone time, perhaps frustration, and certainly as in my own case, feeling silly for having not started with this obvious approach.

After all the ‘USB boot on Ubuntu 21.4 server with a raspberry pi 4’– + similar, tutorials and scripts all failed, I thought about it and… Eureka! I plugged it in. I just flashed the image directly to my drive via USB. After trying lots of cables I found that using one of the USB 180° male – male adapters to connect to the drive worked with most other combinations.

Then just flash it like you would an sd card, configure system-boot just like an sd card and boot with only the usb connection to the drive [no sd card].

I haven’t tested with other images or pi’s [only pi 4 64bit ubuntu 21.04 image for raspi]– as this is ancillary to my task at hand, but I certainly would try this before what seem like incredibly silly methods in retrospect from tutorials I came across.



Not a lot more work, but some. Here flash ssd drive and sd card and connect or insert them both. Then ssh to the device and do a full update and upgrade. If you want to really dig in see the documentation at:


Or just sudo apt install raspi-config and then enter the interface sudo raspi-config and you’ll find the bootloader options under ‘advanced’ sub menu. Select boot usb first and reboot into your ssd drive as root system. —

Gnu Image Manipulation Program practice [EO]

Sustainable Interfacing


Synthetic Intelligence

In order for language to stay active and alive to itself their must still be an audience for Philosophy. Whether the possibility of philosophy could be lost, if left in a state of wonder then one finds oneself where all philosophy begins.

Relevance of scalable intelligence to Knowing Oneself and the possibility of scaling minds in general. The possible appearance of singularity, and becoming.

The race of temporal minds with scaling intelligence. Novel appearance of the eternal in such a way that currently non-scaling minds could potentially begin to scale and become scaling.

Recounting recent: Dork

A ‘Zork like’ text based rpg called…

My team and I wrote dork in python using scrum implementation of agile method, delivering working fully tested iterations of the code according to product owner specifications derived from customer requests in two week sprints. Documentation is on ‘readthedocs’.

We used github for version control with travis-ci and sonarcloud for continuous integration and inspection. The full repository is public on github.


Each new game randomly generates a maze and factories populate the world with descriptions, interactive items and NPC’s from databases. Games can be saved and loaded with persistence of the game state, map, inventory, NPC’s and points.

The project turned out well and was a pleasure to work on. Working with team brought new difficulties the work and complexity of the project we were able to achieve within a short time frame was far beyond what could have been done individually. I have some future expansions planned for the game so stay tuned!



Kali NetHunter

GrapheneOS has a reputation for currently being one of the most secure and private solutions possible for a phone. Naturally upon hearing about it I had to check it out. Here’s a list of the currently supported devices as of the end of Febuary 2021.

I’ve improved my Nethunter setup quite a bit as well so thought an update was due.


With some time into it grapheneOS can really increase anonymity, privacy and security, without the cost of massive functionality. I currently have mine setup with an always on VPN, end to end encrypted communications, tor browser and the ability to switch from VPN to Orbot and proxy all traffic over tor. Permanent add blocking and hardened browsers. Off-line maps so location data and gps can be turned off without losing navigation capacity. Peer to peer decentralized file synchronization along with IPFS-lite.

guardian project/haven

The guardian projects repository can also be imported to whichever FOSS android market you prefer, and though tangential to graphene their application Haven is pretty cool.


Configured with Orbot and your signal account Haven is a multi sensor security system which will securely text you if alarmed as well as having its own onion service you can login to. Haven uses many of the phones sensors to keep real time awareness of its environment, such as picking up any sounds, vibrations, changes in light or movement. Triggering the alarms starts recording from the interfaces and sends an encrypted text via signal. All of these sensors can have their sensitivity adjusted to prevent false alarms. Some of them can be very sensitive without dialing it down. I recommend calibrating it a bit ‘live’ else you might come back to a phone with 100% full data of videos like myself while testing it.

Kali Linux NetHunter

[wifite2 demo]

current wifi capabilities with only the onboard chip
  • A plethora of WEP attacks
  • WPA Handshake Capture and offline crack
  • WPA PMKID Hash Capture and offline crake
  • WPS Brute-Force PIN attack
  • WPS offline Pixie-Dust attack
  • WPS offline NULL PIN attack
Viewing the phone horizontally is a must, I usually use a little blue tooth keyboard.
with on the go cable and second ap
with an anker adapter and another AP we have a remote implant, an extra battery can be paired for extra life; and of course a stand on the coffee table may not be ideal
  • WIFI signal jamming [additional antenna via usb needed]
  • Implant and use all the tools with remote access over ssh

In this accelerated screen recording wifite is enabled by disconnecting from any networks, switching the firmware and then starting the program on interface wlan0 (index 0 the first WiFi adapter, the onboard WiFi chip. Wifite automatically scanning for a few seconds capturing a list around 150 potential targets, then Initialize an attack against against a personal WiFi network I started for the purpose.

Lets improve it. What’s?
better than ssh: Mosh
Easier to type on: iPad
Rubber Ducky’s?
Rucky disables screenshots and any recording during use so these images are borrowed from: https://store.nethunter.com/en/
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With all the fantastic work on Rucky I couldn’t leave they/them out.

The source code: https://github.com/mayankmetha/Rucky

You can download Rucky directly from the NetHunter app store. Of course this is all FOSS. You can download the NetHunter app store from :


And conveniently check the pgp signature via QR code to when downloading before install. Rucky does require root and a USB HID patch for use.

with the lovely color scheme on my device

At https://ducktoolkit.com/ on your phone or any browser you can select from an array of payloads based upon your target, encode the payload, disguise the signatures on your device and load it straight into the app, Rucky. These tools are almost getting easy to use but the barrier of the difficulty to getting this setup in the first place and customizing/configuring it for use seems to still be keeping at bay hoards of teenagers who might otherwise in their lack of experience attempt to use them nefariously.

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Tower Of Pibylon- how high can we pi?

My Raspberry cluster has come a long ways since the first iteration I showed with a docker cluster running OpenFaaS. I added some of the new Pi4 with 8gig of ram, added an ssd drive which I networked shared to the entire cluster. I am just about to tear it down again for improvements so its time for a snap shot.

When rebuilding the cluster I wrote an Ansible playbook to bootstrap it so that I didn’t have to repeat the same 15 processes 10 times. There’s a few major repositories doing similar things but none of them matched my vision so I wrote my own. This repo is already deprecated from version changes to Ansible but I’ll update when I finished with the hardware improvements. The repository is here:


Besides the upcoming rework; if interested, note that inventory file needs to be changed to match Rpi IP's and those IPs should be static. This script doesn't set the static IP because I have a managed switch and am running them all on a virtual lan. Also unless you are my neighbor the time/zone task within the configurations or the universal tasks may also need a change.

Ansible: beautiful and simple

The Read.md from the repository:

To highlight a few, the playbook sets new password, transfers ssh keys, hardens the system, as well as getting the Kubernetes cluster up and going with one Master and transfers the config locally to make use of kubectl to control the cluster. Among the rest.

I adapted a project from Alex Ellis’ to light an led on the blinkt module for each pod being run on a node, giving an indicator of load, balance or any failures.

Bigger, faster, taller, stronger- and not just the hardware. The real gems have been automating the bootstrap with Ansible, managing with Kubernetes (especially lens) and deploying with Helm.

ssd to one of the rPi’s to have some larger persistent storage

I’ve been running a few services on the cluster, I added a SATA adapter and an SSD drive to one of the pi’s to host my own cloud storage. I installed Falco(cloud-native runtime security) through helm along with metalb for the load-balancer, an nginx ingress, with a let’s Encrypt deployment for certificates. Also used pi hole running on the cluster as my networks DNS, providing local caching and secure dns and dnssec for everything else.

The number’s aren’t too drastic here but this is all being caught despite my browsers running ublock-origin.

I forwarded from a domain name that I own to the services I was exposing to the internet so I could reach them whenever wherever. Exposing your own services on the net has a long list of items to go through in terms of safety but just to touch on the basics, long high entropy password which cannot be guessed within the lifetime of the universe is a good start.

Following this up with a dual factor hardware key, also not a bad idea.

This doesn’t address any of the network and firewall changes needed but hopefully I can get into a bit more detail when I have time to share about hosting my own cloud security and surveillance system.

Much more to come but here are some pictures showing a bit of how nice it is to run your own Nextcloud server with the universal support their community has created I have it running on Android, iOS, MacOS, and Ubuntu.

Then to give a look at lens and how slick it is for any who haven’t seen it, it is amazing and easily lets you move from controlling a few things through the CLI to easily managing a massive scaling design.

not this Lens

-this lens https://k8slens.dev/

Going to try and catch up on this back log of things I’ve been working on! I think some android projects and Apps I’ve done and basic AI simulations may be next. Since I mentioned it here’s part of the hardware used to transition to fully manage my security systems with cloud access, no monthly fees and control of my own data, getting full throughput with deep packet inspection and ect,

Recounting Recent: Lucid Flight

Lucid Dreaming app for Android

Lucid Flight is an android app I wrote in Kotlin to assist in lucid dreaming. I’m working on an iOS version in swift and plan to add both to their stores once leisure allows some refinement. The source code is private so the following shows functionality and demonstrates concept.

Lucid Flight app icon | Flying after ‘waking up’ is a quintessential lucid dream

Lucid dreaming has become pretty well known recently but to briefly summarize, it is realizing that you are dreaming while you are dreaming. Given that we sleep for about one third of our lives, gaining the ability to be conscious during our sleep greatly lengthens and enriches our lives. Lucid dream research and scholarship continues being published.

LaBerge, Stephen, et al. “Lucid Dreaming: Physiological Correlates of Consciousness during REM Sleep.” The Journal of Mind and Behavior, vol. 7, no. 2/3, 1986, pp. 251–258. JSTOR, www.jstor.org/stable/43853217. Accessed 22 May 2020.

The benefits of lucid dreaming are far vaster than I want to go into here but suffice it to say that it is awesome, in the literal sense of the word. I chose the name and icon because flying once lucid is one of the most common and most exhilarating experiences.

simple animated vector graphic for load screen

All the incomplete lucid dreaming devices of recent years inspired me to create this. Several have gained full funding on Kickstarter and similar platforms and never released a product. Starting at $200+ dollars makes them cost prohibitive to many as well. Better to use the phone and (hopefully) fitness tracker we already have.

Basically they are masks or devices that take readings from your body in order to determine when you enter the dream stage of sleep. The devices then trigger signals to your dreaming body that you can learn to recognize within the dream state and use as cues to realize you are dreaming.

“[…] dreaming can be viewed as the special case of perception without the constraints of external sensory input. Conversely, perception can be viewed as the special case of dreaming constrained by sensory input.” -Stephen LaBerge

Integration with google fit api’s heart rate data provides data for the apps prediction of REM entry

Some of the Lucid Dream devices use EEG brain signals, some watch for eye movement with sensors over the eyes. Lucid flight predicts REM with heart rate data. Ouraring has an image showing precisely how in their article on heart rate while sleeping.

Resting heart rate curve


Ouraring ignores the sharp peaks in sleeping heart rate for this curves abstraction but the sharp peaks are exactly what lucid flight looks for. Spikes in heart rate are from entry into dreams.

The strategy is to predict REM then signal the sleeper they’re dreaming but not so loud it wakes them completely. Most use lights and some also use sound. The app allows users to customize their dream alarm. The highly customizable alarm allows users to find the sweep spot between waking and being easily recognizable within dreams. Like how shining a flashlight on a dreamers face can trigger the appearance of an oncoming train if it doesn’t wake them.

Heart rate data is in a scrolling view above min, mean, and max for testing adjustments to the REM prediction algorithm.

The middle toggle activates dream detection mode. The bottom three toggles control whether the alarm strobes the flashlight and screen brightness, plays a recorded sound or default tone, and third whether the alarm causes vibration.

Options allow users to record a custom message which the alarm plays back. As well as changing alarm length and previewing the alarm.

Lucid dreaming is very difficult for most people and learning to recognize dream signals while you are dreaming is hard. Nonetheless, having some software and hardware’s help can seriously accelerate the learning curve.

The biggest predictor of successful lucidity is a strong motivation to learn. To that end the app home screen displays inspirational messages about lucid dreaming.