Creating a Generative Adversarial Network and Visions of the Future


The people generated by the ASIC device do not exist. They are synthetic creations of the Generative Adversarial Network.

Over the last few years many will know I’ve been engaged in researches into blockchain. Particularly Ravencoin X16R,X16RV2 and KAWPOW, as well as the many blockchain explorers/trackers/scanners that I have written.

Recently I’ve become a little bit obsessed with GAN, a recently invented class of machine learning frameworks designed by Ian Goodfellow and his colleagues in 2014 and his colleagues at Nvidia.[1] Two neural networks contest with each other in a game (in the form of a zero-sum game, where one agent’s gain is another agent’s loss).

Stylegan 1024px early model with –size 256 parameter

Naturally, using modern GPU power that has traditionally been used for physics simulations, gaming, computational problems and things like cryptocurrency mining, it was a novel idea to consider that such technology could be used to create new novel data. Or be a fundamental resource of great power and adversarial adaptation in the playing of the game.

Trent Klein on Twitter: ""I can't believe it. The computer beaten by flesh  & blood." ~Doctor Pulaski (Peak Performance) #StarTrek #Strategema… "
Naturally, the machine lacks many inherent qualities of a human grandmaster knowledgeable in practice and study, but under the right circumstances or rule-set the machine in this case “data” is able to utilize the advantage of great speed, raw compute power, stamina and perfect reproduction of a strategy to beat the grandmaster at “Strategema”. This surely is then practice over study. This shows that machines with the right knowledge have an advantage. And that human beings with the right machines, have great power with their novel advantage to direct them.

I was very impressed at deepfakes, and the speed that deeplearning, machine learning and other technology has grown, and although I was generally disinterested by early A.I, such as “ALICE” and other polymorphic approaches to computer programming, I was particularly captivated by the deeplearning of Nvidia’s GAN. It appeared that through the correct processing of image boundaries of a very huge amount of “data”, a neural network, much like Data’s in startrek, really was capable of producing extremely novel applications in science and technology. For example, there is no reason why a similar approach could not be used to improve designs, or even build an entire product from start to finish without any human intervention. It certainly would seem then the cosmic idea of a “universal constructor”, first introduced in the popular game “Deus Ex”, is not such a strange idea. Certainly not when it is possible to apply the same methodology for face mixing and latent tracing as with Nvidia GAN, to chemical structures. Theoretically a machine that conceive an indefinite number of combinations, but can also discriminatingly qualify them in a similar way to a human being. An impressive feat.

Stylegan 1024px early model with –size 512 parameter.
The “main” sample.png file generated by the GAN modeler algorithm. These above images are used for “MIXING” (see below)
The power of the Adversarial Network is able to in the early stages produce very basic images that do not yet exceed human modeling and perceptional awareness (such as whether the image is real or not)

Predicting the Beginning and the End

To those that worry, about the technology for the future that will destroy human ingenuity and practicality – I think that the transformative power, and capability of GAN and technology like it, should allow us to create self improving machines that soon will become our guardians of the earth and the extended galaxy. A far fetched idea to some, but this technology makes it seem inevitable to me.

Stylegan 1024px latest model with –size 1024 parameter.
The trained GAN Model although has a few issues in some of the images, is nearly flawless in it’s production

It may not be very soon, but from what I can see already and imagine, the possibilities for this technology are truly endless, and it will likely be used, it may very well be used for exploring the universe from home. This technology is so simple at present, that the more complex forms of it’s application, theoretically could create entire universes, and with the sufficient compute and energy, it might be possible to discover many things about our universe without actually studying them. Simply provide a few simple rules, and the rest can be generated. Theoretically, anyway. Perhaps, then, we might be nearing a real explanation for the Hawkings Paradox, perhaps some thermal dynamic problems such as the total energy available at the beginning of the universe can be solved in a similar way through GAN type neural compute from data presently at the “middle” and latent images of stars very distant in the “beginning” or past (it takes a long time for light to reach the planet earth so most cosmic light is ancient). Using this data a new type of fundamental GAN that doesn’t just shape engineering, and novel artistic insight or design, or some chemistry simulation, but it may indeed allow us to predict nearly all things, and create a new type of computer system that is quite different from the one we are familiar.

When we mix the trained GAN Model generations we get new sets of variations;

Stylegan 1024px early model with –size 1024 parameter. This image particularly shows well the adapative nature of the Generative Adversarial Network and shows how the deep learning algorithm “learns” effectively faces and can “mix” any attributes using it’s learned data from it’s previous deeplearning training. to me It is very impressive.

A new Computer System

This new computer system would, theoretically, make efficiencies everywhere where we do not. Such as the adequate and measurable metric or data storage, redundancy, and things like satellite imagery and weather reporting. The neutral net device should theoretically be linkable to human consciousness, and to a greater system and create a new type of VR highway, that I predict will one day exist, optimizing many frequent challenges of modern society, that, until about 30-40 years ago, did not exist, until the abundance of data came along. GAN is a result of the abundance of data, but perhaps certain fundamental societal and technological evolutions in civilisation. Technology like GAN and blockchain might just be an inevitable byproduct or endproduct, of more data than we can humanly handle. And finding a way to use the data we have more efficiently, and to track it properly with automation, (such as with cloud compute), this is key. Really – the secret mystical understanding of the future of technology – was based on the understanding of the derivation of technology, society, and art, and the manner in which humanity interacts with that over a period of time. This reveals how science and art, and the society that practices it must change, rather than that the change applies to society, the society very much applies to the change.

Creating the Neural Network on Nvidia/CUDA

Creating the network is simple enough to do, and this can be done without a Docker Container on what I’d recommend would be an Ubuntu 20.04 LTS system. You can also use a docker container, however a Ubuntu 20.04 LTS system with the reference Nvidia drivers and a venv environment should be sufficient for our needs. It’s worth noting that if you intend to use the latest version of torch, python 3.8 is incompatible with torch v2, and I had some difficulty installing v1 on my linux system, simply because I was running python 3.8. It should work OK if you have a venv with python 3.7 or similar. Because this configuration can break a lot of things. It is highly recommended to use either Docker or venv, or both or either to achieve this.

Installing and Preparing the Datasets

#install venv
sudo apt-get install python3-pip

# do not do this as root, create a user for it [or use your regular user]
adduser someuser
virtualenv venv -p python3

# active venv (must be done where venv created)
source venv/bin/activate

# clone my repo
git clone

# cd to repo and download the celeba dataset 
# ( )
cd sbgan

# Prepare the JPEG data (--out datasetout pathtosearchsubdirsforimages)
python --out data .

# install the necessary dependencies (note that torchvision 2 should be OK) I use it OK for this and you can skip requiring 1.x for this example
pip install torch pillow tqdm torchvision lmdb

# CUDA package names for thoroughness shouldnt be necessary if you've 3rd party nvidia drivers installed by Ubuntu 20.04 LTS.

# DANGEROUS step if you don't know what your doing
# apt-get install nvidia-cuda-dev nvidia-cuda-toolkit nvidia-cuda-toolkit-gcc 

# Start Training the Deeplearning Generative Adversarial Network with your dataset
python3 --mixing /home/adam/GAN/sbgan/data

Congratulations! You’ve reached this far and your GAN is now training. You’ll notice though that it’s running probably quite slowly. For really decent performance you’ll want to have a number of GPU. I’d recommend running on Amazon were it not so expensive. You can get multiple GPU systems though between $8 and $15 an hour, so, relatively that’s not bad considering Tesla P100 gpu’s can set you back thousands a piece. For those that mean business, and for the many that work on GAN more full time they seem to be using DGX-1 which have 6 or 9 GPU builtin and are very small. Unfortunately they cost about $129,000. Although it’s still quite a specialist field, it reminds me of where bigdata was 15-20 years ago. The same could be said for enterprise linux.

Things do change. The last steps now after many weeks would be to run against the models that your generating.

A sample is saved every 100 iterations in the sample directory.

Generating from Modelling

Once your GAN has been “trained”, it should be possible to generate some really amazing mixers of images and I was taken aback by how effective some of the software of modernity has become at identifying things, even when the software does not know what it is, detecting the boundary and “putting things in the right place” is all that matters to us.. very cool.

# Generate from the Trained Models created in checkpoint folder (happens as training goes by)
# Use size 8,16,32,64,128,256,512,1024, etc
# depending how far along the training

python3 /home/adam/GAN/sbgan/checkpoint/train_step-4.model --size 64 --n_row 8 --n_col 8

python3 /home/adam/GAN/sbgan/checkpoint/train_step-4.model --size 64 --n_row 8 --n_col 8

The Checkpoints for the GAN are generated in ./checkpoints, this allow you to retrain from any specific point and to compare or merge certain image sets later on if you wish to experiment with greater complexity

The Final results

I really love GAN’s now 😀

Just for fun I wrote this script that can automatically pull data in and out of a docker container.

# this script indefinitely makes a new face every x moments
# deep fake y'all nvidia cuda stylee

for (( i = 0; i <= $length; i=i+4 )) ; do
j=$(($i + 1))
k=$(($j + 1))
l=$(($k + 1))
echo "Processing face $i,$j,$k,$l";

docker run --gpus all -it --rm -v `pwd`:/scratch --user $(id -u):$(id -g) stylegan2ada:latest bash -c     "(cd /scratch && DNNLIB_CACHE_DIR=/scratch/.cache python3 --trunc=1 --seeds=$i,$j,$k,$l --outdir=out --network=" > /dev/null

sleep 10


Simple but, cool. meh. As you can see this one uses the stylegan2-ada pretained metfaces pkl model from nvlabs. Not bad for a quick poke around at a new subject.

Adding a User with Sudo Access using visudo

Use the command visudo to access the /etc/sudoers file.


Uncomment this line:

## Allows people in group wheel to run all commands
# %wheel        ALL=(ALL)       ALL

So it looks like:

## Allows people in group wheel to run all commands
 %wheel        ALL=(ALL)       ALL

Save the file then

Run this command for your user

usermod -aG wheel usernameforsudoaccesshere

Your done.

But test it

su usernamewithsudoaccess
sudo yum history

Any root only command is a good enough test for this. The command should run succesfully after re-providing your users password for sudo access.

Reverting a yum transaction & controlling auto-updates for yum-cron with excludes

Hey, so a customer was running yum-cron, the Redhat version of Canoninical’s unattended upgrades. An auto update for a package ran, which actually broke their backend.

# yum history info 172
Loaded plugins: replace, rhnplugin
This system is receiving updates from RHN Classic or Red Hat Satellite.
Transaction ID : 172
Begin time     : Sat May  6 05:45:29 2017
Begin rpmdb    : 742:11fcb243cc5701b9d2293d90cb4161e5edc34bb8
End time       :            05:45:31 2017 (2 seconds)
End rpmdb      : 742:0afbbf517315f18985b2d01d4c2e5250caf0afb5
User           : root <root>
Return-Code    : Success
Transaction performed with:
    Installed     rpm-4.11.3-21.el7.x86_64                @rhel-x86_64-server-7
    Installed     yum-3.4.3-150.el7.noarch                @rhel-x86_64-server-7
    Installed     yum-metadata-parser-1.1.4-10.el7.x86_64 @anaconda/7.1
    Installed     yum-rhn-plugin-2.0.1-6.1.el7_3.noarch   @rhel-x86_64-server-7
Packages Altered:
    Updated php56u-pecl-xdebug-2.5.1-1.ius.el7.x86_64 @rackspace-rhel-x86_64-server-7-ius
    Update                     2.5.3-1.ius.el7.x86_64 @rackspace-rhel-x86_64-server-7-ius
history info

The customer asked us to reverse the transaction, so I did, this was quite simple to do;

[[email protected] user]# yum history undo 172
Loaded plugins: replace, rhnplugin
This system is receiving updates from RHN Classic or Red Hat Satellite.
Undoing transaction 172, from Sat May  6 05:45:29 2017
    Updated php56u-pecl-xdebug-2.5.1-1.ius.el7.x86_64 @rackspace-rhel-x86_64-server-7-ius
    Update                     2.5.3-1.ius.el7.x86_64 @rackspace-rhel-x86_64-server-7-ius
Resolving Dependencies
--> Running transaction check
---> Package php56u-pecl-xdebug.x86_64 0:2.5.1-1.ius.el7 will be a downgrade
---> Package php56u-pecl-xdebug.x86_64 0:2.5.3-1.ius.el7 will be erased
--> Finished Dependency Resolution

Dependencies Resolved

 Package                                                  Arch                                         Version                                               Repository                                                                Size
 php56u-pecl-xdebug                                       x86_64                                       2.5.1-1.ius.el7                                       rackspace-rhel-x86_64-server-7-ius                                       205 k

Transaction Summary
Downgrade  1 Package

Total download size: 205 k
Is this ok [y/d/N]: y
Downloading packages:
Delta RPMs disabled because /usr/bin/applydeltarpm not installed.
php56u-pecl-xdebug-2.5.1-1.ius.el7.x86_64.rpm                                                                                                                                                                        | 205 kB  00:00:00
Running transaction check
Running transaction test
Transaction test succeeded
Running transaction
  Installing : php56u-pecl-xdebug-2.5.1-1.ius.el7.x86_64                                                                                                                                                                                1/2
  Cleanup    : php56u-pecl-xdebug-2.5.3-1.ius.el7.x86_64                                                                                                                                                                                2/2
  Verifying  : php56u-pecl-xdebug-2.5.1-1.ius.el7.x86_64                                                                                                                                                                                1/2
  Verifying  : php56u-pecl-xdebug-2.5.3-1.ius.el7.x86_64                                                                                                                                                                                2/2

  php56u-pecl-xdebug.x86_64 0:2.5.3-1.ius.el7

  php56u-pecl-xdebug.x86_64 0:2.5.1-1.ius.el7


In CentOS 7 and I believe RedHat RHEL 7 as well, if you don’t want to disable yum-cron altogether by running a yum remove yum-cron, you could exclude the specific package, or use wildcards to exclude all of them like php* , http*, etc.

vi /etc/yum/yum-cron.conf.

If you wish to exclude some packages from auto-update mechanism, you’ll have to add an exclude line, at the bottom of the file, in the base section.

exclude = kernel* php* httpd*

etc, I hope that this is of some assist,

cheers &
Best wishes,

Magento Rewrite Woes … really woes

I had a customer this week that had some terrible rewrite woes with their magento site. They knew that a whole ton of their images were getting 404’s most likely because rewrite wasn’t getting to the correct filesystem path that the file resided. This was due to their cache being broken, and their second developer not creating proper rewrite rule.

As a sysadmin our job is not a development role, we are a support role, and in order to enable the developer to fix the problem, the developer needs to be able to see exactly what it is, enter the sysads task. I wrote this really ghetto script, which essentially hunts in the nginx error log for requests that failed with no such file, and then qualifies them by grepping for jpg file types. This is not a perfect way of doing it, however, it is really effective at identifying the broken links.

Then I have a seperate routine that strips the each of the file uri’s down to the filename, and locates the file on the filesystem, and matches the filename on the filesystem that the rewrite should be going to, as well as the incorrect path that the rewrite is presently putting the url to. See the script below:


# Author: Adam Bull
# Company: Rackspace LTD, Hayes
# Purpose:
#          This customer has a difficulty with nginx rewriting to the incorrect file
# this script goes into the nginx error.log and finds all the images which have the broken rewrite rules
# then after it has identified the broken rewrite rule files, it searches for the correct file on the filesystem
# then correlates it with the necessary rewrite rule that is required
# this could potentially be used for in-place upgrade by developers
# to ensure that website has proper redirects in the case of bugs with the ones which exist.

# This script will effectively find all 404's and give necessary information for forming a rewrite rule, i.e. the request url, from nginx error.log vs the actual filesystem location
# on the hard disk that the request needs to go to, but is not being rewritten to file path correctly already

# that way this data could be used to create rewrite rules programmatically, potentially
# This is a work in progress

# These are used for display output
cat /var/log/nginx/error.log /var/log/nginx/error.log.1 | grep 'No such file' | awk '{print "URL Request:",$21,"\nFilesystem destination missing:",$7"\n"}'
zcat /var/log/nginx/*error*.gz  | grep 'No such file' | awk '{print "URL Request:",$21,"\nFilesystem destination detected missing:",$7"\n"}'

# These below are used for variable population for locating actual file paths of missing files needed to determine the proper rewrite path destination (which is missing)
# we qualify this with only *.jpg files

cat /var/log/nginx/error.log /var/log/nginx/error.log.1 | grep 'No such file' | awk '{print $7}' | sed 's/\"//g' |  sed 's/.*\///' | grep jpg > lost.txt
zcat /var/log/nginx/*error*.gz  | grep 'No such file' | awk '{print $7}' | sed 's/\"//g' |  sed 's/.*\///' | grep jpg >> lost.txt

cat /var/log/nginx/error.log /var/log/nginx/error.log.1 | grep 'No such file' | awk '{print "",$21}' | sed 's/\"//g' | grep jpg > lostfullurl.txt
zcat /var/log/nginx/*error*.gz  | grep 'No such file' | awk '{print "",$21}' | sed 's/\"//g' | grep jpg >> lostfullurl.txt

# The below section is used for finding the lost files on filesystem and pairing them together in variable pairs
# for programmatic usage for rewrite rules

while true
  read -r f1 <&3 || break
  read -r f2 <&4 || break
  printf '\n\n'
  printf 'Found a broken link getting a 404 at : %s\n'
  printf "$f1\n"
  printf 'Locating the correct link of the file on the filesystem: %s\n'
        find /var/www/magento | grep $f2
done 3<lostfullurl.txt 4<lost.txt

I was particularly proud of the last section which uses a ‘dual loop for two input files’ in a single while statement, allowing me to achieve the descriptions above.

Output is in the form of:

Found a broken link getting a 404 at :
Locating the correct link of the file on the filesystem:

As you can see the path is different on the filesystem to the url that the rewrite is putting the request to, hence the 404 this customer is getting.

This could be a really useful script, and, I see no reason why the script could not generate the rewrite rules programatically from the 404 failures it finds, it could actually create rules that are necessary to fix the problem. Now, this is not an ideal fix, however the script will allow you to have an overview either to fix this properly as a developer, or as a sysadmin to patch up with new rewrite rules.

I’m really proud of this one, even though not everyone may see a use for it. There really really is, and this customer is stoked, think of it like this, how can a developer fix it if he doesn’t have a clear idea of the things that are broken, and this is the sysads job,

Cheers &
Best wishes,

Less Ghetto Log Parser for Website Hitcount/Downtime Analysis

Yesterday I created a proof of concept script, which basically goes off and identifies the hitcounts of a website, and can give a technician within a short duration of time (minutes instead of hours) exactly where hitcounts are coming from and where.

This is kind of a tradeoff, between a script that is automated, and one that is flexible.

The end goal is to provide a hitcount vs memory commit metric value. A NEW TYPE OF METRIC! HURRAH! (This is needed by the industry IMO).

And also would be nice to generate graphing and mean, average, and ranges, etc. So can provide output like ‘stat’ tool. Here is how I have progress

# Author: 	Adam Bull, Cirrus Infrastructure, Rackspace LTD
# Date: 	March 20 2017
# Use:		This script automates the analysis of webserver logs hitcounts and
# 		provides a breakdown to indicate whether outages are caused by website visits
#		In correlation to memory and load avg figures

# Settings

# What logfile to get stats for

# What year month and day are we scanning for minute/hour hits

echo "Total HITS: MARCH"
grep "/$month/$year" "$logfile" | wc -l;

# Hours
for i in 0{1..9} {10..24};

do echo "      > 9th March 2017, hits this $i hour";
grep "$day/$month/$year:$i" "$logfile" | wc -l;

        # break down the minutes in a nested visual way thats AWsome

# Minutes
for j in 0{1..9} {10..60};
do echo "                  >>hits at $i:$j";
grep "$day/$month/$year:$i:$j" "$logfile" | wc -l;


Thing is, after I wrote this, I wasn’t really happy, so I refactored it a bit more;

# Author: 	Adam Bull, Cirrus Infrastructure, Rackspace LTD
# Date: 	March 20 2017
# Use:		This script automates the analysis of webserver logs hitcounts and
# 		provides a breakdown to indicate whether outages are caused by website visits
#		In correlation to memory and load avg figures

# Settings

# What logfile to get stats for

# What year month and day are we scanning for minute/hour hits

echo "Total HITS: $month"
grep "/$month/$year" "$logfile" | wc -l;

# Hours
for i in 0{1..9} {10..24};

hitsperhour=$(grep "$day/$month/$year:$i" "$logfile" | wc -l;);
echo "    > $day $month $year, hits this $ith hour: $hitsperhour"

        # break down the minutes in a nested visual way thats AWsome

# Minutes
for j in 0{1..9} {10..59};
hitsperminute=$(grep "$day/$month/$year:$i:$j" "$logfile" | wc -l);
echo "                  >>hits at $i:$j  $hitsperminute";


Now it’s pretty leet.. well, simple. but functional. Here is what the output of the more nicely refined script; I’m really satisfied with the tabulation.

[[email protected] automation]# ./
Total HITS: Mar
    > 9 Mar 2017, hits this  hour: 28793
                  >>hits at 01:01  416
                  >>hits at 01:02  380
                  >>hits at 01:03  417
                  >>hits at 01:04  408
                  >>hits at 01:05  385

All About NOVA and Xen Tools in Rackspace Cloud – why can’t I connect to my Windows server?

Why can’t I connect to my Rackspace Windows cloud-server, you ask? 2 important questions.

1. Is it a new build?
2. Is it using a custom image (a non rackspace base image).

(because the rackspace base images all have correct nova-agent and xen tools, so get networking information OK. But customer images don’t!). In the case you have run the below tests to see if nova-agent is running (or installed), you will need to install them.

Checking for the nova-agent and xe-guest-utilities

ps auxfwww | grep nova-agent
yum -qa xe-guest-utilities nova-agent
dpkg -l xe-guest-utilities nova-agent

Explanation and solution

Thanks for reaching out to us with your inquiry today. I’m glad to convey to you that I understand what the problem is with your cloud-server not being contactable.

Main reasons for breakage

The main reason why this is not working is most likely caused by some important pieces of software being missing. There is a piece of software called nova-agent, which is responsible for setting your cloud-servers IPV4 address, network subnet/mask, and ip routes, when it is first built. This is important, since the server image you built the server from, has different network details.

The rackspace build process giving networking detail to the VM is completely dependent on xe-guest-utilities and nova-agent

What has happened in this case, because the nova-agent wasn’t running on the cloud-server, the hypervisor software Rackspace use to automate cloud-server builds wasn’t able to contact the nova-agent running on your cloud-server, and therefore nova-agent wasn’t able to update the networking information. And hence, your not able to connect to it on it’s IPv4 address you are given at build time.

The steps to resolution: installing nova-agent and xen guest utilities
As such, nova-agent needs to be installed on the cloud-server you take the image from, it can be installed as follows:

Also nova-agent uses another piece of important software called xe-guest-utilities, or (Xen Tools) for your windows servers, this is an important ‘PV’ paravirtualization tools, responsible for seamless management of cloud-servers. Sorry that in this case it’s not working out seamlessly, but this can happen with images taken of servers which have had nova-agent disabled, uninstalled, or similar.

Upgrading the tools that nova-agent depends upon, can be installed by following the instructions at the following location:

# Options of how to do this / Summary of Solution Steps

Naturally, you might be wondering how to achieve these changes, if you cannot RDP to the server. This is quite understandable, there are two ways to get this working;

Option 1) Manually install nova-agent on the current server you cannot access, then manually install the Xen Tools in the same way. This shall fix the OS on the server itself, and not the original image you built the server from. So it is important to create a new cloud-server image after performing these steps and us verifying tools + nova-agent installed correctly.

2) Manually install nova-agent on the source server you initially taken the image from, and install Xen Tools, then re-image the server, and then re-deploy. This should seamlesssly work each time on build with that image, provided the tools are installed. You will not need to recreate the image, since your fixing the problem on the cloud-server source that the original image was taken from.

I appreciate that these things are not 100% simple to get your head around and can be confusing for customers, I hope my explanation and summary makes this a little more painless to fix. Of course if you have additional questions, comments or concerns or don’t understand something I’ve said, please don’t hesitate to reach out to us, we are here to help!

Adding nodes and Updating nodes behind a Cloud Load Balancer

I have succeeded in putting together a basic script documenting exactly how API works and for adding node(s), listing the nods behind the LB, as well as updating the nodes (such as DRAINING, DISABLED, ENABLED).

Use update node to set one of your nodes to gracefully drain (not accept new connections, wait for present connections to die). Naturally, you will want to put the secondary server in behind the load balancer first, with

Once new node is added as enabled, set the old node to ‘DRAINING’. This will gracefully switch over the server.

# List Load Balancers



TOKEN=`curl -X POST -d '{ "auth":{"RAX-KSKEY:apiKeyCredentials": { "username":"'$USERNAME'", "apiKey": "'$APIKEY'" }} }' -H "Content-type: application/json" |  python -mjson.tool | grep -A5 token | grep id | cut -d '"' -f4`

curl -v -H "X-Auth-Token: $TOKEN" -H "content-type: application/json" -X GET "$CUSTOMER_ID/loadbalancers/$LB_ID"


# Add Node(s)



TOKEN=`curl -X POST -d '{ "auth":{"RAX-KSKEY:apiKeyCredentials": { "username":"'$USERNAME'", "apiKey": "'$APIKEY'" }} }' -H "Content-type: application/json" |  python -mjson.tool | grep -A5 token | grep id | cut -d '"' -f4`

# Add Node
curl -v -H "X-Auth-Token: $TOKEN" -d @addnode.json -H "content-type: application/json" -X POST "$CUSTOMER_ID/loadbalancers/$LB_ID/nodes"


For the addnode script you require a file, called addnode.json
that file must contain the snet ip's you wish to add

# addnode.json

{"nodes": [
            "address": "",
            "port": 80,
            "condition": "ENABLED",






TOKEN=`curl -X POST -d '{ "auth":{"RAX-KSKEY:apiKeyCredentials": { "username":"'$USERNAME'", "apiKey": "'$APIKEY'" }} }' -H "Content-type: applic

# Update Node

curl -v -H "X-Auth-Token: $TOKEN" -d @updatenode.json -H "content-type: application/json" -X PUT "$CUSTOMER_ID/loadbalancers/$LB_ID/nodes/$NODE_ID"



## updatenode.json

            "condition": "DISABLED",

Naturally, you will be able to change condition to ENABLED, DISABLED, or DRAINING.

I recommend to use DRAINING, since it will gracefully remove the cloud-server, and any existing connections will be waited on, before removing the server from LB.

Automating Backups in Public Cloud using Cloud Files

Hey folks, I know it’s been a little while since I put an article together. However I have been putting together a really article explaining how to write bespoke backup systems for the Rackspace Community. It’s a proof of concept/demonstration/tutorial as opposed to a production application. However people looking to create custom cloud backup scripts may benefit from the experience of reading thru it.

You can see the article at the below URL:

Using Nova and Supernova to manage Firewall IP access lists, automation & more

So, a customer today reached out to us asking if Rackspace provided the entire infrastructure IP address ranges in use on cloud. The answer is, no. However, that doesn’t mean that making your firewall rules, or autoscale automation need to be painful.

In fact, Rackspace Cloud utilizes Openstack which fully supports API calls which will easily be able to provide this detail in just a few simple short steps. To do this you require nova to be installed, this is really relatively easy to install, and instructions for installing it can be found here;

Once you have installed nova, it’s simply a case of making sure you set these 4 lines correctly in your .bash_profile


OS_USERNAME is your mycloud login username (normally the primary user).
OS_TENANT_NAME is your Customer ID, it’s the number that appears in the URL of your control panel link, see below picture for illustration

Screen Shot 2016-08-10 at 2.45.05 PM

OS_PASSWORD is a bit misleading, this is actually where your apikey goes , but I think it’s possible to authenticate using your control panel password too, don’t do that for security reasons.

OS_REGION_NAME is pretty self explanatory, this is simply the region that you would like to list cloud-server IP’s in or rather, the region that you wish to perform NOVA API calls.

Making the API call using the nova API wrapper

# supernova lon list --tenant 100010101 --fields accessIPv4,name
[SUPERNOVA] Running nova against lon...
| ID                                   | accessIPv4      | Name      |
| 7e5a7f99-60ae-4c28-b2b8              |  |  xapp      |
| 94747603-812d-4594-850b              |  |   rabbit2   |
| d5b318aa-0fa2-4269-ae00              |  |   elastic5  |
| 6c1d8d33-ae5e-44be-b9f0              |  | | elastic6  |
| 9f79a7dc-fd19-4f8f-9c26              |   | | elastic3  |
| 05b1c52b-6ced-4db0-8af2              | | | elastic1  |
| c8302366-f2f9-4c36-8f7a              |  | | app5      |
| b159cd07-8e68-49bc-83ee              |  | | app6      |
| f1f31eef-97c6-4c68-b01a              |  | | ruby1     |
| 64b7f0fd-8f2f-4d5f-8f89              |  | | build3    |
| e320c051-b5cf-473a-9f96              |  |   mysql2    |
| 4fddd022-59a8-4502-bf6e              |  | | mysql1    |
| c9ad6951-f5f9-4351-b31d              |  | | worker2   |

This is pretty useful for managing autoscale permissions if you need to make sure your corporate network can be connected to from your cloud-servers when new cloud-servers with new IP are built out. considerations like this are really important when putting together a solution. The nice thing is the tools are really quite simple and flexible. If I wanted I could have pulled out detail for servicenet instead. I hope this helps make some folks lives a bit easier and works to demystify API to others that haven’t had the opportunity to use it.

You are probably wondering though, what field names can I use? a nova show will reveal this against one of your server UUID’s

# supernova lon show someuuidgoeshere
| Property                            | Value                                                            |
| OS-DCF:diskConfig                   | MANUAL                                                           |
| OS-EXT-SRV-ATTR:host                | censored                                                   |
| OS-EXT-SRV-ATTR:hypervisor_hostname | censored                                                 |
| OS-EXT-SRV-ATTR:instance_name       | instance-734834278-sdfdsfds-                   |
| OS-EXT-STS:power_state              | 1                                                                |
| OS-EXT-STS:task_state               | -                                                                |
| OS-EXT-STS:vm_state                 | active                                                           |
| censorednet network                 | censored                                                     |
| accessIPv4                          | censored                                                 |
| accessIPv6                          | censored                      |
| created                             | 2015-12-11T14:12:08Z                                             |
| flavor                              | 15 GB I/O v1 (io1-15)                                            |
| hostId                              | 860...         |
| id                                  | 9f79a7dc-fd19-4f8f-9c26-72a335ed2be8                             |
| image                               | Debian 8 (Jessie) (PVHVM) (cf16c435-7bed-4dc3-b76e-57b09987866d) |
| metadata                            | {"build_config": "", "rax_service_level_automation": "Complete"} |
| name                                | elastic3                                                         |
| private network                     |                                                 |
| progress                            | 100                                                              |
| public network                      |          |
| status                              | ACTIVE                                                           |
| tenant_id                           |                                                    |
| updated                             | 2016-02-27T09:30:20Z                                             |
| user_id                             |                             |

I censored some of the fields.. but you can see all of the column names, so if you wanted to see metadata and progress only, with the server uuid and server name.

nova list --fields name, metadata, progress

This could be pretty handy for detecting when a process has finished building, or detecting once automation has completed. The possibilities with API are quite endless. API is certainly the future, and, there is no reason why, in the future, people won't be building and deploying websites thru API only, and some sophisticated UI wrapper like NOVA.

Admittedly, this is very far away, but that should be what the future technology will be made of, stuff like LAMBDA, serverless architecture, will be the future.

Adding some excludes for Lsyncd

A customer was having some issues with their syncing, as was shown by their inotify

Error: Terminating since out of inotify watches.
Consider increasing /proc/sys/fs/inotify/max_user_watches

Fix was quite simple, to remove other folders from sync that aren’t necessary.

Adding this line to the /etc/lsyncd.conf


And creating the ‘excludes’ file for LsyncD, i.e. what folders you want to ignore, in this case we wanted to ignore old httpdocs.OLD backup.

# cat /etc/lsyncd-excludes.txt

A shockingly simple fix.

Please note that the path in lsyncd-excludes.txt is determined by the path in lsyncd. (do not give full path, give relative path inside the parent). It was a simple fix.