"Unnatural Love" by "Keith Garner" on Flickr

Configuring a Remote Desktop (Gnome Shell) for Ubuntu

I started thinking a couple of weeks ago, when my coding laptop broke, that it would be really useful to have a development machine somewhere else that I could use.

It wouldn’t need a lot of power (after all, I’m mostly developing web apps and not compiling stuff), but it does need to be a desktop OS, as I rather like being able to open code editors and suchlike, while I’ve got a web browser open.

I have an Android tablet, which while it’s great for being a tablet, it’s not much use as a desktop, and … yes, I’ve got a work laptop, but I don’t really want to install software on that (and I don’t think my admin team would be happy if I did).

Also, I quite like Linux.

Some time ago, I spotted that AWS has a “Virtual Desktop” environment, and I think that’s kinda what I’m after. Something I can spin up, run for a bit and then shut it down, so I thought I’d build something like that… but not pesky Windows, after all… who likes Windows, eh? ;)

So, I built a Virtual Desktop Environment (VDE) in AWS, using Terraform and a bit of shell script!

I start from an Ubuntu 18.04 server image, and, after the install is complete, I run this user-data script inside it. Yes, I know I could be doing this with Ansible, but… eh, I wanted it to be a quick deployment ;)

Oh, and there’s a couple of Terraform managed variables in here – ${aws_eip.vde.public_ip} is the AWS public IP address assigned to this host., ${var.firstuser} is the username we want to rename “ubuntu” (the stock server username) to. ${var.firstgecos} is the user’s “real name” which the machine identifies the user as (like “Log out Jon Spriggs” and so on). ${var.userpw} is either the password you want it to use, OR (by default) pwgen 12 which generates a 12 character long password. ${var.desktopenv} is the name of the desktop environment I want to install (Ubuntu by default) and … well, ${var.var_start} is a bit of a fudge, because I couldn’t, in a hurry, work out how to tell Terraform not to mangle the bash variable allocation of ${somevar} which is the format that Terraform also uses. D’oh.

#! /bin/bash
#################
# Set Hostname
#################
hostnamectl set-hostname vde.${aws_eip.vde.public_ip}.nip.io
#################
# Change User
#################
user=${var.firstuser}
if [ ! "$user" == 'ubuntu' ]
then
  until usermod -c "${var.firstgecos}" -l $user ubuntu ; do sleep 5 ; done
  until groupmod -n $user ubuntu ; do sleep 5 ; done
  until usermod  -d /home/$user -m $user ; do sleep 5 ; done
  if [ -f /etc/sudoers.d/90-cloudimg-ubuntu ]; then
    mv /etc/sudoers.d/90-cloudimg-ubuntu /etc/sudoers.d/90-cloud-init-users
  fi
  perl -pi -e "s/ubuntu/$user/g;" /etc/sudoers.d/90-cloud-init-users
fi
if [ '${var.userpw}' == '$(pwgen 12)' ]
then 
  apt update && apt install pwgen
fi
newpw="${var.userpw}"
echo "$newpw" > /var/log/userpw
fullpw="$newpw"
fullpw+="\n"
fullpw+="$newpw"
echo -e "$fullpw" | passwd $user
##########################
# Install Desktop and RDP
##########################
apt-get update
export DEBIAN_FRONTEND=noninteractive
apt-get full-upgrade -yq
apt-get autoremove -y
apt-get autoclean -y
apt-get install -y ${var.desktopenv}-desktop xrdp certbot
##########################
# Configure Certbot
##########################
echo "#!/bin/sh" > /etc/letsencrypt/merge_cert.sh
echo 'cat ${var.var_start}{RENEWED_LINEAGE}/privkey.pem ${var.var_start}{RENEWED_LINEAGE}/fullchain.pem > ${var.var_start}{RENEWED_LINEAGE}/merged.pem' >> /etc/letsencrypt/merge_cert.sh
echo 'chmod 640 ${var.var_start}{RENEWED_LINEAGE}/merged.pem' >> /etc/letsencrypt/merge_cert.sh
chmod 750 /etc/letsencrypt/merge_cert.sh
certbot certonly --standalone --deploy-hook /etc/letsencrypt/merge_cert.sh -n -d vde.${aws_eip.vde.public_ip}.nip.io -d ${aws_eip.vde.public_ip}.nip.io --register-unsafely-without-email --agree-tos
# Based on https://www.snel.com/support/xrdp-with-lets-encrypt-on-ubuntu-18-04/
sed -i 's~^certificate=$~certificate=/etc/letsencrypt/live/vde.${aws_eip.vde.public_ip}.nip.io/fullchain.pem~; s~^key_file=$~key_file=/etc/letsencrypt/live/vde.${aws_eip.vde.public_ip}.nip.io/privkey.pem' /etc/xrdp/xrdp.ini
##############################
# Fix colord remote user issue
##############################
# Derived from http://c-nergy.be/blog/?p=12043
echo "[Allow Colord all Users]
Identity=unix-user:*
Action=org.freedesktop.color-manager.create-device;org.freedesktop.color-manager.create-profile;org.freedesktop.color-manager.delete-device;org.freedesktop.color-manager.delete-profile;org.freedesktop.color-manager.modify-device;org.freedesktop.color-manager.modify-profile
ResultAny=no
ResultInactive=no
ResultActive=yes" > /etc/polkit-1/localauthority/50-local.d/45-allow.colord.pkla
##############################
# Configure Desktop
##############################
if [ '${var.desktopenv}' == 'ubuntu' ]
then 
  echo "#!/bin/bash" > /tmp/desktop_settings
  echo "gsettings set org.gnome.desktop.input-sources sources \"[('xkb', 'gb')]\"" >> /tmp/desktop_settings
  echo "gsettings set org.gnome.desktop.app-folders folder-children \"['Utilities', 'Sundry', 'YaST']\"" >> /tmp/desktop_settings
  echo "gsettings set org.gnome.desktop.privacy report-technical-problems false" >> /tmp/desktop_settings
  echo "gsettings set org.gnome.desktop.screensaver lock-enabled false" >> /tmp/desktop_settings
  echo "gsettings set org.gnome.desktop.session idle-delay 0" >> /tmp/desktop_settings
  echo "echo yes > /home/${var.firstuser}/.config/gnome-initial-setup-done" >> /tmp/desktop_settings
  sudo -H -u ${var.firstuser} dbus-launch --exit-with-session bash /tmp/desktop_settings
  rm -f /tmp/desktop_settings
fi
##########################
# Install VSCode
##########################
wget https://vscode-update.azurewebsites.net/latest/linux-deb-x64/stable -O /tmp/vscode.deb
apt install -y /tmp/vscode.deb
rm /var/crash/*
shutdown -r now

Ubuntu 18.04 has a “first login” wizard, that lets you pre-set up things like, what language will you be using. I bypassed this with the gsettings commands towards the end of the script, and writing the string “yes” to ~/.config/gnome-initial-setup-done.

Also, I wanted to be able to RDP to it. I’m a bit concerned by the use of VNC, especially where RDP is more than capable. It’s just an apt-install away, so… that’s what I do. But, because I’m RDP’ing into this box, I wanted to prevent the RDP session from locking, so I provide two commands to the session: gsettings set org.gnome.desktop.screensaver lock-enabled false which removes the screensaver’s ability to lock the screen, and gsettings set org.gnome.desktop.session idle-delay 0 which stops the screensaver from even starting in the first place.

Now all I need to do is to figure out where I’m going to store my code between boots ;)

So, in summary, I now have a Virtual Machine, which runs Ubuntu 18.04 Desktop, in AWS, with an RDP connection (powered by xRDP), and a disabled screensaver. Job done, I think!

Oh, and if I’m doing it “wrong”, let me know in the comments? :)

Featured image is “Unnatural Love” by “Keith Garner” on Flickr and is released under a CC-BY-SA license.

"So many coats..." by "Scott Griggs" on Flickr

Migrating from docker-compose to Kubernetes Files

Just so you know. This is a long article to explain my wandering path through understanding Kubernetes (K8S). It’s not an article to explain to you how to use K8S with your project. I hit a lot of blockers, due to the stack I’m using and I document them all. This means there’s a lot of noise and not a whole lot of Signal.

In a previous blog post I created a docker-compose.yml file for a PHP based web application. Now that I have a working Kubernetes environment, I wanted to port the configuration files into Kubernetes.

Initially, I was pointed at Kompose, a tool for converting docker-compose files to Kubernetes YAML formatted files, and, in fact, this gives me 99% of what I need… except, the current version uses beta API version flags for some of it’s outputted files, and this isn’t valid for the version of Kubernetes I’m running. So, let’s wind things back a bit, and find out what you need to do to use kompose first and then we can tweak the output file next.

Note: I’m running all these commands as root. There’s a bit of weirdness going on because I’m using the snap of Docker and I had a few issues with running these commands as a user… While I could have tried to get to the bottom of this with sudo and watching logs, I just wanted to push on… Anyway.

Here’s our “simple” docker-compose file.

version: '3'
services:
  db:
    build:
      context: .
      dockerfile: mariadb/Dockerfile
    image: localhost:32000/db
    restart: always
    environment:
      MYSQL_ROOT_PASSWORD: a_root_pw
      MYSQL_USER: a_user
      MYSQL_PASSWORD: a_password
      MYSQL_DATABASE: a_db
    expose:
      - 3306
  nginx:
    build:
      context: .
      dockerfile: nginx/Dockerfile
    image: localhost:32000/nginx
    ports:
      - 1980:80
  phpfpm:
    build:
      context: .
      dockerfile: phpfpm/Dockerfile
    image: localhost:32000/phpfpm

This has three components – the MariaDB database, the nginx web server and the PHP-FPM CGI service that nginx consumes. The database service exposes a port (3306) to other containers, with a set of hard-coded credentials (yep, that’s not great… working on that one!), while the nginx service opens port 1980 to port 80 in the container. So far, so … well, kinda sensible :)

If we run kompose convert against this docker-compose file, we get five files created; db-deployment.yaml, nginx-deployment.yaml, phpfpm-deployment.yaml, db-service.yaml and nginx-service.yaml. If we were to run kompose up on these, we get an error message…

Well, actually, first, we get a whole load of “INFO” and “WARN” lines up while kompose builds and pushes the containers into the MicroK8S local registry (a registry is a like a package repository, for containers), which is served by localhost:32000 (hence all the image: localhost:3200/someimage lines in the docker-compose.yml file), but at the end, we get (today) this error:

INFO We are going to create Kubernetes Deployments, Services and PersistentVolumeClaims for your Dockerized application. If you need different kind of resources, use the 'kompose convert' and 'kubectl create -f' commands instead.

FATA Error while deploying application: Get http://localhost:8080/api: dial tcp 127.0.0.1:8080: connect: connection refused

Uh oh! Well, this is a known issue at least! Kubernetes used to use, by default, http on port 8080 for it’s service, but now it uses https on port 6443. Well, that’s what I thought! In this issue on the MicroK8S repo, it says that it uses a different port, and you should use microk8s.kubectl cluster-info to find the port… and yep… Kubernetes master is running at https://127.0.0.1:16443. Bah.

root@microk8s-a:~/glowing-adventure# microk8s.kubectl cluster-info
Kubernetes master is running at https://127.0.0.1:16443
Heapster is running at https://127.0.0.1:16443/api/v1/namespaces/kube-system/services/heapster/proxy
CoreDNS is running at https://127.0.0.1:16443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy
Grafana is running at https://127.0.0.1:16443/api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
InfluxDB is running at https://127.0.0.1:16443/api/v1/namespaces/kube-system/services/monitoring-influxdb:http/proxy

So, we export the KUBERNETES_MASTER environment variable, which was explained in that known issue I mentioned before, and now we get a credential prompt:

Please enter Username:

Oh no, again! I don’t have credentials!! Fortunately the MicroK8S issue also tells us how to find those! You run microk8s.config and it tells you the username!

roo@microk8s-a:~/glowing-adventure# microk8s.config
apiVersion: v1
clusters:
- cluster:
    certificate-authority-data: <base64-data>
    server: https://10.0.2.15:16443
  name: microk8s-cluster
contexts:
- context:
    cluster: microk8s-cluster
    user: admin
  name: microk8s
current-context: microk8s
kind: Config
preferences: {}
users:
- name: admin
  user:
    username: admin
    password: QXdUVmN3c3AvWlJ3bnRmZVJmdFhpNkJ3cDdkR3dGaVdxREhuWWo0MmUvTT0K

So, our username is “admin” and our password is … well, in this case a string starting QX and ending 0K but yours will be different!

We run kompose up again, and put in the credentials… ARGH!

FATA Error while deploying application: Get https://127.0.0.1:16443/api: x509: certificate signed by unknown authority

Well, now, that’s no good! Fortunately, a quick Google later, and up pops this Stack Overflow suggestion (mildly amended for my circumstances):

openssl s_client -showcerts -connect 127.0.0.1:16443 < /dev/null | sed -ne '/-BEGIN CERTIFICATE-/,/-END CERTIFICATE-/p' | sudo tee /usr/local/share/ca-certificates/k8s.crt
update-ca-certificates
systemctl restart snap.docker.dockerd

Right then. Let’s run that kompose up statement again…

INFO We are going to create Kubernetes Deployments, Services and PersistentVolumeClaims for your Dockerized application. If you need different kind of resources, use the 'kompose convert' and 'kubectl create -f' commands instead.

Please enter Username: 
Please enter Password: 
INFO Deploying application in "default" namespace
INFO Successfully created Service: nginx
FATA Error while deploying application: the server could not find the requested resource

Bah! What resource do I need? Well, actually, there’s a bug in 1.20.0 of Kompose, and it should be fixed in 1.21.0. The “resource” it’s talking about is, I think, that one of the APIs refuses to process the converted YAML files. As a result, the “resource” is the service that won’t start. So, instead, let’s convert the file into the output YAML files, and then take a peak at what’s going wrong.

root@microk8s-a:~/glowing-adventure# kompose convert
INFO Kubernetes file "nginx-service.yaml" created
INFO Kubernetes file "db-deployment.yaml" created
INFO Kubernetes file "nginx-deployment.yaml" created
INFO Kubernetes file "phpfpm-deployment.yaml" created

So far, so good! Now let’s run kubectl apply with each of these files.

root@microk8s-a:~/glowing-adventure# kubectl apply -f nginx-service.yaml
Warning: kubectl apply should be used on resource created by either kubectl create --save-config or kubectl apply
service/nginx configured
root@microk8s-a:~# kubectl apply -f nginx-deployment.yaml
error: unable to recognize "nginx-deployment.yaml": no matches for kind "Deployment" in version "extensions/v1beta1"

Apparently the service files are all OK, the problem is in the deployment files. Hmm OK, let’s have a look at what could be wrong. Here’s the output file:

root@microk8s-a:~/glowing-adventure# cat nginx-deployment.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  annotations:
    kompose.cmd: kompose convert
    kompose.version: 1.20.0 (f3d54d784)
  creationTimestamp: null
  labels:
    io.kompose.service: nginx
  name: nginx
spec:
  replicas: 1
  strategy: {}
  template:
    metadata:
      annotations:
        kompose.cmd: kompose convert
        kompose.version: 1.20.0 (f3d54d784)
      creationTimestamp: null
      labels:
        io.kompose.service: nginx
    spec:
      containers:
      - image: localhost:32000/nginx
        name: nginx
        ports:
        - containerPort: 80
        resources: {}
      restartPolicy: Always
status: {}

Well, the extensions/v1beta1 API version doesn’t seem to support “Deployment” options any more, so let’s edit it to change that to what the official documentation example shows today. We need to switch to using the apiVersion: apps/v1 value. Let’s see what happens when we make that change!

root@microk8s-a:~/glowing-adventure# kubectl apply -f nginx-deployment.yaml
error: error validating "nginx-deployment.yaml": error validating data: ValidationError(Deployment.spec): missing required field "selector" in io.k8s.api.apps.v1.DeploymentSpec; if you choose to ignore these errors, turn validation off with --validate=false

Hmm this seems to be a fairly critical issue. A selector basically tells the orchestration engine which images we want to be deployed. Let’s go back to the official example. So, we need to add the “selector” value in the “spec” block, at the same level as “template”, and it needs to match the labels we’ve specified. It also looks like we don’t need most of the metadata that kompose has given us. So, let’s adjust the deployment to look a bit more like that example.

root@microk8s-a:~/glowing-adventure# cat nginx-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: nginx
  name: nginx
spec:
  replicas: 1
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - image: localhost:32000/nginx
        name: nginx
        ports:
        - containerPort: 80
        resources: {}
      restartPolicy: Always

Fab. And what happens when we run it?

root@microk8s-a:~/glowing-adventure# kubectl apply -f nginx-deployment.yaml
deployment.apps/nginx created

Woohoo! Let’s apply all of these now.

root@microk8s-a:~/glowing-adventure# for i in db-deployment.yaml nginx-deployment.yaml nginx-service.yaml phpfpm-deployment.yaml; do kubectl apply -f $i ; done
deployment.apps/db created
deployment.apps/nginx unchanged
service/nginx unchanged
deployment.apps/phpfpm created

Oh, hang on a second, that service (service/nginx) is unchanged, but we changed the label from io.kompose.service: nginx to app: nginx, so we need to fix that. Let’s open it up and edit it!

apiVersion: v1
kind: Service
metadata:
  annotations:
    kompose.cmd: kompose convert
    kompose.version: 1.20.0 (f3d54d784)
  creationTimestamp: null
  labels:
    io.kompose.service: nginx
  name: nginx
spec:
  ports:
  - name: "1980"
    port: 1980
    targetPort: 80
  selector:
    io.kompose.service: nginx
status:
  loadBalancer: {}

Ah, so this has the “annotations” field too, in the metadata, and, as suspected, it’s got the io.kompose.service label as the selector. Hmm OK, let’s fix that.

root@microk8s-a:~/glowing-adventure# cat nginx-service.yaml
apiVersion: v1
kind: Service
metadata:
  labels:
    app: nginx
  name: nginx
spec:
  ports:
  - name: "1980"
    port: 1980
    targetPort: 80
  selector:
    app: nginx
status:
  loadBalancer: {}

Much better. And let’s apply it…

root@microk8s-a:~/glowing-adventure# kubectl apply -f nginx-service.yaml
service/nginx configured

Fab! So, let’s review the state of the deployments, the services, the pods and the replication sets.

root@microk8s-a:~/glowing-adventure# kubectl get deploy
NAME     READY   UP-TO-DATE   AVAILABLE   AGE
db       1/1     1            1           8m54s
nginx    0/1     1            0           8m53s
phpfpm   1/1     1            1           8m48s

Hmm. That doesn’t look right.

root@microk8s-a:~/glowing-adventure# kubectl get pod
NAME                      READY   STATUS             RESTARTS   AGE
db-f78f9f69b-grqfz        1/1     Running            0          9m9s
nginx-7774fcb84c-cxk4v    0/1     CrashLoopBackOff   6          9m8s
phpfpm-66945b7767-vb8km   1/1     Running            0          9m3s
root@microk8s-a:~# kubectl get rs
NAME                DESIRED   CURRENT   READY   AGE
db-f78f9f69b        1         1         1       9m18s
nginx-7774fcb84c    1         1         0       9m17s
phpfpm-66945b7767   1         1         1       9m12s

Yep. What does “CrashLoopBackOff” even mean?! Let’s check the logs. We need to ask the pod itself, not the deployment, so let’s use the kubectl logs command to ask.

root@microk8s-a:~/glowing-adventure# kubectl logs nginx-7774fcb84c-cxk4v
2020/01/17 08:08:50 [emerg] 1#1: host not found in upstream "phpfpm" in /etc/nginx/conf.d/default.conf:10
nginx: [emerg] host not found in upstream "phpfpm" in /etc/nginx/conf.d/default.conf:10

Hmm. That’s not good. We were using the fact that Docker just named everything for us in the docker-compose file, but now in Kubernetes, we need to do something different. At this point I ran out of ideas. I asked on the McrTech slack for advice. I was asked to run this command, and would you look at that, there’s nothing for nginx to connect to.

root@microk8s-a:~/glowing-adventure# kubectl get service
NAME         TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
kubernetes   ClusterIP   10.152.183.1    <none>        443/TCP    24h
nginx        ClusterIP   10.152.183.62   <none>        1980/TCP   9m1s

It turns out that I need to create a service for each of the deployments. So, now I have a separate service for each one. I copied the nginx-service.yaml file into db-service.yaml and phpfpm-service.yaml, edited the files and now… tada!

root@microk8s-a:~/glowing-adventure# kubectl get service
NAME         TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
db           ClusterIP   10.152.183.61   <none>        3306/TCP   5m37s
kubernetes   ClusterIP   10.152.183.1    <none>        443/TCP    30h
nginx        ClusterIP   10.152.183.62   <none>        1980/TCP   5h54m
phpfpm       ClusterIP   10.152.183.69   <none>        9000/TCP   5m41s

But wait… How do I actually address nginx now? Huh. No external-ip (not even “pending”, which is what I ended up with), no ports to talk to. Uh oh. Now I need to understand how to hook this service up to the public IP of this node. Ahh, see up there it says “ClusterIP”? That means “this service is only available INSIDE the cluster”. If I change this to “NodePort” or “LoadBalancer”, it’ll attach that port to the external interface.

What’s the difference between “NodePort” and “LoadBalancer”? Well, according to this page, if you are using a managed Public Cloud service that supports an external load balancer, then putting this to “LoadBalancer” should attach your “NodePort” to the provider’s Load Balancer automatically. Otherwise, you need to define the “NodePort” value in your config (which must be a value between 30000 and 32767, although that is configurable for the node). Once you’ve done that, you can hook your load balancer up to that port, for example Client -> Load Balancer IP (TCP/80) -> K8S Cluster IP (e.g. TCP/31234)

So, how does this actually look. I’m going to use the “LoadBalancer” option, because if I ever deploy this to “live”, I want it to integrate with the load balancer, but for now, I can cope with addressing a “high port”. Right, well, let me open back up that nginx-service.yaml, and make the changes.

root@microk8s-a:~/glowing-adventure# cat nginx-service.yaml
apiVersion: v1
kind: Service
metadata:
  labels:
    app: nginx
  name: nginx
spec:
  type: LoadBalancer
  ports:
  - name: nginx
    nodePort: 30000
    port: 1980
    targetPort: 80
  selector:
    app: nginx
status:
  loadBalancer: {}

The key parts here are the lines type: LoadBalancer and nodePort: 30000 under spec: and ports: respectively. Note that I can use, at this point type: LoadBalancer and type: NodePort interchangably, but, as I said, if you were using this in something like AWS or Azure, you might want to do it differently!

So, now I can curl http://192.0.2.100:30000 (where 192.0.2.100 is the address of my “bridged interface” of K8S environment) and get a response from my PHP application, behind nginx, and I know (from poking at it a bit) that it works with my Database.

OK, one last thing. I don’t really want lots of little files which have got config items in. I quite liked the docker-compose file as it was, because it had all the services in as one block, and I could run “docker-compose up”, but the kompose script split it out into lots of pieces. In Kubernetes, if the YAML file it loads has got a divider in it (a line like this: ---) then it stops parsing it at that point, and starts reading the file after that as a new file. Like this I could have the following layout:

apiVersion: apps/v1
kind: Deployment
more: stuff
---
apiVersion: v1
kind: Service
more: stuff
---
apiVersion: apps/v1
kind: Deployment
more: stuff
---
apiVersion: v1
kind: Service
more: stuff

But, thinking about it, I quite like having each piece logically together, so I really want db.yaml, nginx.yaml and phpfpm.yaml, where each of those files contains both the deployment and the service. So, let’s do that. I’ll do one file, so it makes more sense, and then show you the output.

root@microk8s-a:~/glowing-adventure# mkdir -p k8s
root@microk8s-a:~/glowing-adventure# mv db-deployment.yaml k8s/db.yaml
root@microk8s-a:~/glowing-adventure# echo "---" >> k8s/db.yaml
root@microk8s-a:~/glowing-adventure# cat db-service.yaml >> k8s/db.yaml
root@microk8s-a:~/glowing-adventure# rm db-service.yaml
root@microk8s-a:~/glowing-adventure# cat k8s/db.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: db
  name: db
spec:
  replicas: 1
  selector:
    matchLabels:
      app: db
  template:
    metadata:
      labels:
        app: db
    spec:
      containers:
      - env:
        - name: MYSQL_DATABASE
          value: a_db
        - name: MYSQL_PASSWORD
          value: a_password
        - name: MYSQL_ROOT_PASSWORD
          value: a_root_pw
        - name: MYSQL_USER
          value: a_user
        image: localhost:32000/db
        name: db
        resources: {}
      restartPolicy: Always
---
apiVersion: v1
kind: Service
metadata:
  labels:
    app: db
  name: db
spec:
  ports:
  - name: mariadb
    port: 3306
    targetPort: 3306
  selector:
    app: db
status:
  loadBalancer: {}

So, now, if I do kubectl apply -f k8s/db.yaml I’ll get this output:

root@microk8s-a:~/glowing-adventure# kubectl apply -f k8s/db.yaml
deployment.apps/db unchanged
service/db unchanged

You can see the final files in the git repo for this set of tests.

Next episode, I’ll start looking at making my application scale (as that’s the thing that Kubernetes is known for) and having more than one K8S node to house my K8S pods!

Featured image is “So many coats…” by “Scott Griggs” on Flickr and is released under a CC-BY-ND license.

apt update && apt full-upgrade -y && apt autoremove -y && apt autoclean -y

Apt Updates with Ansible

I’ve got a small Ansible script that I bundle up on Ubuntu boxes to do apt updates. This was originally a one-statement job, but I’ve added a few lines to it, so I thought I’d explain what I’m doing (more for myself, for later!)

Initally, I just had a task to do apt: upgrade=full update_cache=yes autoremove=yes autoclean-yes but if you’re running the script over and over again, well, this gets slow… So I added a tweak!

Here it is folks, in all it’s glory!

- hosts: all
  tasks:
  - name: Get stat of last run apt
    stat:
      path: /var/cache/apt/pkgcache.bin
    register: apt_run

  - name: "Apt update, Full-upgrade, autoremove, autoclean check"
    debug:
      msg: "Skipping apt-update, etc. actions as apt update was run today"
    when: "'%Y-%m-%d' | strftime(apt_run.stat.mtime) in ansible_date_time.date"

  - name: "Apt update, Full-upgrade, autoremove, autoclean"
    apt:
      upgrade: full
      update_cache: yes
      autoremove: yes
      autoclean: yes
    when: "'%Y-%m-%d' | strftime(apt_run.stat.mtime) not in ansible_date_time.date"

What does this do? Well, according to this AskUbuntu post, the best file to check if an update has been performed is /var/cache/apt/pkgcache.bin, so we check the status of that file. Most file systems available to Linux distributions provide the mtime – or “last modified time”. This is returned in the number of seconds since UTC 00:00:00 on the Unix Epoch (1970-01-01), so we need to convert that to a date., which we return as YYYY-MM-DD (e.g. today is 2020-01-06) and then compare that to what the system thinks today is. If the dates don’t equate (so one string doesn’t match the other – in other words, apt update wasn’t run today), it runs the update. If the dates do match up, we get a statement saying that apt update was already run.

Fun times!

"Shipping Containers" by "asgw" on Flickr

Creating my first Docker containerized LEMP (Linux, nginx, MariaDB, PHP) application

Want to see what I built without reading the why’s and wherefore’s? The git repository with all the docker-compose goodness is here!

Late edit 2020-01-16: The fantastic Jerry Steel, my co-host on The Admin Admin podcast looked at what I wrote, and made a few suggestions. I’ve updated the code in the git repo, and I’ll try to annotate below when I’ve changed something. If I miss it, it’s right in the Git repo!

One of the challenges I set myself this Christmas was to learn enough about Docker to put an arbitrary PHP application, that I would previously have misused Vagrant to contain.

Just before I started down this rabbit hole, I spoke to my Aunt about some family tree research my father had left behind after he died, and how I wished I could easily share the old tree with her (I organised getting her a Chromebook a couple of years ago, after fighting with doing remote support for years on Linux and Windows laptops). In the end, I found a web application for genealogical research called HuMo-gen, that is a perfect match for both projects I wanted to look at.

HuMo-gen was first created in 1999, with a PHP version being released in 2005. It used MySQL or MariaDB as the Database engine. I was reasonably confident that I could have created a Vagrantfile to deliver this on my home server, but I wanted to try something new. I wanted to use the “standard” building blocks of Docker and Docker-Compose, and some common containers to make my way around learning Docker.

I started by looking for some resources on how to build a Docker container. Much of the guidance I’d found was to use Docker-Compose, as this allows you to stand several components up at the same time!

In contrast to how Vagrant works (which is basically a CLI wrapper to many virtual machine services), Docker isolates resources for a single process that runs on a machine. Where in Vagrant, you might run several processes on one machine (perhaps, in this instance, nginx, PHP-FPM and MariaDB), with Docker, you’re encouraged to run each “service” as their own containers, and link them together with an overlay network. It’s possible to also do the same with Vagrant, but you’ll end up with an awful lot of VM overhead to separate out each piece.

So, I first needed to select my services. My initial line-up was:

  • MariaDB
  • PHP-FPM
  • Apache’s httpd2 (replaced by nginx)

I was able to find official Docker images for PHP, MariaDB and httpd, but after extensive tweaking, I couldn’t make the httpd image talk the way I wanted it to with the PHP image. Bowing to what now seems to be conventional wisdom, I swapped out the httpd service for nginx.

One of the stumbling blocks for me, particularly early on, was how to build several different Dockerfiles (these are basically the instructions for the container you’re constructing). Here is the basic outline of how to do this:

version: '3'
services:
  yourservice:
    build:
      context: .
      dockerfile: relative/path/to/Dockerfile

In this docker-compose.yml file, I tell it that to create the yourservice service, it needs to build the docker container, using the file in ./relative/path/to/Dockerfile. This file in turn contains an instruction to import an image.

Each service stacks on top of each other in that docker-compose.yml file, like this:

version: '3'
services:
  service1:
    build:
      context: .
      dockerfile: service1/Dockerfile
    image: localhost:32000/service1
  service2:
    build:
      context: .
      dockerfile: service2/Dockerfile
    image: localhost:32000/service2

Late edit 2020-01-16: This previously listed Dockerfile/service1, however, much of the documentation suggested that Docker gets quite opinionated about the file being called Dockerfile. While docker-compose can work around this, it’s better to stick to tradition :) The docker-compose.yml files below have also been adjusted accordingly. I’ve also added an image: somehost:1234/image_name line to help with tagging the images for later use. It’s not critical to what’s going on here, but I found it useful with some later projects.

To allow containers to see ports between themselves, you add the expose: command in your docker-compose.yml, and to allow that port to be visible from the “outside” (i.e. to the host and upwards), use the ports: command listing the “host” port (the one on the host OS), then a colon and then the “target” port (the one in the container), like these:

version: '3'
services:
  service1:
    build:
      context: .
      dockerfile: service1/Dockerfile
    image: localhost:32000/service1
    expose:
    - 12345
  service2:
    build:
      context: .
      dockerfile: service2/Dockerfile
    image: localhost:32000/service2
    ports:
    - 8000:80

Now, let’s take a quick look into the Dockerfiles. Each “statement” in a Dockerfile adds a new “layer” to the image. For local operations, this probably isn’t a problem, but when you’re storing these images on a hosted provider, you want to keep these images as small as possible.

I built a Database Dockerfile, which is about as small as you can make it!

FROM mariadb:10.4.10

Yep, one line. How cool is that? In the docker-compose.yml file, I invoke this, like this:

version: '3'
services:
  db:
    build:
      context: .
      dockerfile: mariadb/Dockerfile
    image: localhost:32000/db
    restart: always
    environment:
      MYSQL_ROOT_PASSWORD: a_root_pw
      MYSQL_USER: a_user
      MYSQL_PASSWORD: a_password
      MYSQL_DATABASE: a_db
    expose:
      - 3306

OK, so this one is a bit more complex! I wanted it to build my Dockerfile, which is “mariadb/Dockerfile“. I wanted it to restart the container whenever it failed (which hopefully isn’t that often!), and I wanted to inject some specific environment variables into the file – the root and user passwords, a user account and a database name. Initially I was having some issues where it wasn’t building the database with these credentials, but I think that’s because I wasn’t “building” the new database, I was just using it. I also expose the MariaDB (MySQL) port, 3306 to the other containers in the docker-compose.yml file.

Let’s take a look at the next part! PHP-FPM. Here’s the Dockerfile:

FROM php:7.4-fpm
RUN docker-php-ext-install pdo pdo_mysql
ADD --chown=www-data:www-data public /var/www/html

There’s a bit more to this, but not loads. We build our image from a named version of PHP, and install two extensions to PHP, pdo and pdo_mysql. Lastly, we copy the content of the “public” directory into the /var/www/html path, and make sure it “belongs” to the right user (www-data).

I’d previously tried to do a lot more complicated things with this Dockerfile, but it wasn’t working, so instead I slimmed it right down to just this, and the docker-compose.yml is a lot simpler too.

  phpfpm:
    build:
      context: .
      dockerfile: phpfpm/Dockerfile
    image: localhost:32000/phpfpm

See! Loads simpler! Now we need the complicated bit! :) This is the Dockerfile for nginx.

FROM nginx:1.17.7
COPY nginx/default.conf /etc/nginx/conf.d/default.conf

COPY public /var/www/html

Weirdly, even though I’ve added version numbers for MariaDB and PHP, I’ve not done the same for nginx, perhaps I should! Late edit 2020-01-16: I’ve put a version number on there now, previously where it said nginx:1.17.7 it actually said nginx:latest.

I’ve created the configuration block for nginx in a single “RUN” line. Late edit 2020-01-16: This Dockerfile now doesn’t have a giant echo 'stuff' > file block either, following Jerry’s advice, and I’m using COPY instead of ADD on his advice too. I’ll show that config file below. There’s a couple of high points for me here!

server {
  index index.php index.html;
  server_name _;
  error_log /proc/self/fd/2;
  access_log /proc/self/fd/1;
  root /var/www/html;
  location ~ \.php$ {
    try_files $uri =404;
    fastcgi_split_path_info ^(.+\.php)(/.+)$;
    fastcgi_pass phpfpm:9000;
    fastcgi_index index.php;
    include fastcgi_params;
    fastcgi_param SCRIPT_FILENAME $document_root$fastcgi_script_name;
    fastcgi_param PATH_INFO $fastcgi_path_info;
  }
}
  • server_name _; means “use this block for all unnamed requests”.
  • access_log /proc/self/fd/1; and error_log /proc/self/fd/2;These are links to the “stdout” and “stderr” file descriptors (or pointers to other parts of the filesystem), and basically means that when you do docker-compose logs, you’ll see the HTTP logs for the server! These two files are guaranteed to be there, while /dev/stderr isn’t!

Because nginx is “just” caching the web content, and I know the content doesn’t need to be written to from nginx, I knew I didn’t need to do the chown action, like I did with the PHP-FPM block.

Lastly, I need to configure the docker-compose.yml file for nginx:

  nginx:
    build:
      context: .
      dockerfile: Dockerfile/nginx
    image: localhost:32000/nginx
    ports:
      - 127.0.0.1:1980:80

I’ve gone for a slightly unusual ports configuration when I deployed this to my web server… you see, I already have the HTTP port (TCP/80) configured for use on my home server – for running the rest of my web services. During development, on my home machine, the ports line instead showed “1980:80” because I was running this on Instead, I’m running this application bound to “localhost” (127.0.0.1) on a different port number (1980 selected because it could, conceivably, be a birthday of someone on this system), and then in my local web server configuration, I’m proxying connections to this service, with HTTPS encryption as well. That’s all outside the scope of this article (as I probably should be using something like Traefik, anyway) but it shows you how you could bind to a separate port too.

Anyway, that was my Docker journey over Christmas, and I look forward to using it more, going forward!

Featured image is “Shipping Containers” by “asgw” on Flickr and is released under a CC-BY license.

"Mesh Facade" by "Pedro Ângelo" on Flickr

Looking at the Nebula Overlay Meshed VPN Network from Slack

Around 2-3 years ago, Slack– the company who produces Slack the IM client, started working on a meshed overlay network product, called Nebula, to manage their environment. After two years of running their production network on the back of it, they decided to open source it. I found out about Nebula via a Medium Post that was mentioned in the HangOps Slack Group. I got interested in it, asked a few questions about Nebula in the Slack, and then in the Github Issues for it, and then recently raised a Pull Request to add more complete documentation than their single (heavily) commented config file.

So, let’s go into some details on why this is interesting to me.

1. Nebula uses a flat IPv4 network to identify all hosts in the network, no matter where in the network those hosts reside.

This means that I can address any host in my (self allocated) 198.18.0.0/16 network, and I don’t need to worry about routing tables, production/DR sites, network tromboneing and so on… it’s just… Flat.

[Note: Yes, that IP address “looks” like a public subnet – but it’s actually a testing network, allocated by IANA for network testing!]

2. Nebula has host-based firewalling built into the configuration file.

This means that once I know how my network should operate (yes, I know that’s a big ask), I can restrict my servers from being able to reach my laptops, or I can stop my web server from being able to talk to my database server, except for on the database ports. Lateral movement becomes a LOT harder.

This firewalling also looks a lot like (Network) Security Groups (for the AWS and Azure familiar), so you have a default “Deny” rule, and then layer “Allow” rules on top. You also have Inbound and Outbound rules, so if you want to stop your laptops from talking anything but DNS, SSH, HTTPS and ICMP over Nebula…. well, yep, you can do that :)

3. Nebula uses a PKI environment. Where you can have multiple Certificate Authorities.

This means that I have a central server running my certificate authority (CA), with a “backup” CA, stored offline – in case of dire disaster with my primary CA, and push both CA’s to all my nodes. If I suddenly need to replace all the certificates that my current CA signed, I can do that with minimal interruption to my nodes. Good stuff.

Nebula also created their own PKI attributes to identify the roles of each device in the Nebula environment. By signing that as part of the certificate on each node too, means your CA asserts that the role that certificate holds is valid for that node in the network.

Creating a node’s certificate is a simple command:

nebula-cert sign -name jon-laptop -ip 198.18.0.1/16 -groups admin,laptop,support

This certificate has the IP address of the node baked in (it’s 198.18.0.1) and the groups it’s part of (admin, laptop and support), as well as the host name (jon-laptop). I can use any of these three items in my firewall rules I mentioned above.

4. It creates a peer-to-peer, meshed VPN.

While it’s possible to create a peer-to-peer meshed VPN with commercial products, I’ve not seen any which are as light-weight to deploy as this. Each node finds all the other nodes in the network by using a collection of “Lighthouses” (similar to Torrent Seeds or Skype Super Nodes) which tells all the connecting nodes where all the other machines in the network are located. These then initiate UDP connections to the other nodes they want to talk to. If they are struggling (because of NAT or Double NAT), then there’s a NAT Punching process (called, humourously, “punchy”) which lets you signal via the Lighthouse that you’re trying to reach another node that can’t see your connection, and asks it to also connect out to you over UDP… thereby fixing the connection issue. All good.

5. Nebula has clients for Windows, Mac and Linux. Apparently there are clients for iOS in the works (meh, I’m not on Apple… but I know some are) and I’ve heard nothing about Android as yet, but as it’s on Linux, I’m sure some enterprising soul can take a look at it (the client is written in Go).

If you want to have a look at Nebula for your own testing, I’ve created a Terraform based environment on AWS and Azure to show how you’d manage it all using Ansible Tower, which builds:

2 VPCs (AWS) and 1 VNet (Azure)
6 subnets (3 public, 3 private)
1 public AWX (the upstream project from Ansible Tower) Server
1 private Nebula Certificate Authority
2 public Web Servers (one in AWS, one in Azure)
2 private Database Servers (one in AWS, one in Azure)
2 public Bastion Servers (one in AWS, one in Azure) – that lets AWX reach into the Private sections of the network, without exposing SSH from all the hosts.

If you don’t want to provision the Azure side, just remove load_web2_module.tf from the Terraform directory in that repo… Job’s a good’n!

I have plans to look at a couple of variables, like Nebula’s closest rival, ZeroTier, and to look at using SaltStack instead of Ansible, to reduce the need for the extra Bastion servers.

Featured image is “Mesh Facade” by “Pedro Ângelo” on Flickr and is released under a CC-BY-SA license.

Building a simple CA for testing purposes

I recently needed to create a Certificate Authority with an Intermediate Certificate to test some TLS inspection stuff at work. This script (based on a document I found at jamielinux.com) builds a Certificate Authority and creates an Intermediate Certificate Authority using the root.

I’ve also done something similar with Ansible before, but I’ve not got that to hand :)

Late edit, 2019-08-21: Found it! Needs some tweaks to add the sub-CA or child certs, but so-far it would work :)

“code crunching” by “Ruben Molina” on Flickr

Getting Started with Terraform on AWS

I recently wrote a blog post about Getting Started with Terraform on Azure. You might have read it (I know I did!).

Having got a VM stood up in Azure, I wanted to build a VM in AWS, after all, it’s more-or-less the same steps. Note, this is a work-in-progress, and shouldn’t be considered “Final” – this is just something to use as *your* starting block.

What do you need?

You need an AWS account for this. If you’ve not got one, signing up for one is easy, but bear in mind that while there are free resource on AWS (only for the first year!), it’s also quite easy to suddenly enable a load of features that cost you money.

Best practice suggests (or rather, INSISTS) you shouldn’t use your “root” account for AWS. It’s literally just there to let you define the rest of your admin accounts. Turn on MFA (Multi-Factor Authentication) on that account, give it an exceedingly complex password, write that on a sheet of paper, and lock it in a box. You should NEVER use it!

Create your admin account, log in to that account. Turn on MFA on *that* account too. Then, create an “Access Token” for your account. This is in IAM (Identity and Access Management). These are what we’ll use to let Terraform perform actions in AWS, without you needing to actually “log in”.

On my machine, I’ve put the credentials for this in /home/<MYUSER>/.aws/credentials and it looks like this:

[default]
aws_access_key_id = ABC123DEF456
aws_secret_access_key = AaBbCcDd1234EeFf56

This file should be chmod 600 and make sure it’s only your account that can access this file. With this token, Terraform can perform *ANY ACTION* as you, including anything that charges you money, or creating servers that can mine a “cryptocurrency” for someone malicious.

I’m using Windows Subsystem for Linux (WSL). I’m using the Ubuntu 18.04 distribution obtained from the Store. This post won’t explain how to get *that*. Also, you might want to run Terraform on Mac, in Windows or on Linux natively… so, yehr.

Next, we need to actually install Terraform. Excuse the long, unwrapped code block, but it gets what you need quickly (assuming the terraform webpage doesn’t change any time soon!)

mkdir -p ~/bin
cd ~/bin
sudo apt update && sudo apt install unzip
curl -sLO $(curl https://www.terraform.io/downloads.html | grep "linux_amd64.zip" | cut -d\" -f 2) && unzip terraform*.zip && rm terraform*.zip && chmod 755 terraform

Starting coding your infrastructure

Before you can build your first virtual machine on AWS, you need to stand up the supporting infrastructure. These are:

  • An SSH Keypair (no password logins here!)
  • A VPC (“Virtual Private Cloud”, roughly the same as a VNet on Azure, or somewhat like a L3 switch in the Physical Realm).
  • An Internet Gateway (if your VPC isn’t classed as “the default one”)
  • A Subnet.
  • A Security Group.

Once we’ve got these, we can build our Virtual Machine on EC2 (“Elastic Cloud Compute”), and associate a “Public IP” to it.

To quote my previous post:

One quirk with Terraform, versus other tools like Ansible, is that when you run one of the terraform commands (like terraform init, terraform plan or terraform apply), it reads the entire content of any file suffixed “tf” in that directory, so if you don’t want a file to be loaded, you need to either move it out of the directory, comment it out, or rename it so it doesn’t end .tf. By convention, you normally have three “standard” files in a terraform directory – main.tf, variables.tf and output.tf, but logically speaking, you could have everything in a single file, or each instruction in it’s own file.

Getting Started with Terraform on Azure – Building the file structure

For the sake of editing and annotating the files for this post, these code blocks are all separated, but on my machine, they’re all currently one big file called “main.tf“.

In that file, I start by telling it that I’m working with the Terraform AWS provider, and that it should target my nearest region.

If you want to risk financial ruin, you can put things like your access tokens in here, but I really wouldn’t chance this!

Next, we create our network infrastructure – VPC, Internet Gateway and Subnet. We also change the routing table.

I suspect, if I’d created the VPC as “The Default” VPC, then I wouldn’t have needed to amend the routing table, nor added an Internet Gateway. To help us make the routing table change, there’s a “data” block in this section of code. A data block is an instruction to Terraform to go and ask a resource for *something*, in this case, we need AWS to tell Terraform what the routing table is that it created for the VPC. Once we have that we can ask for the routing table change.

AWS doesn’t actually give “proper” names to any of it’s assets. To provide something with a “real” name, you need to tag that thing with the “Name” tag. These can be practically anything, but I’ve given semi-sensible names to everything. You might want to name everything “main” (like I nearly did)!

We’re getting close to being able to create the VM now. First of all, we’ll create the Security Groups. I want to separate out my “Allow Egress Traffic” rule from my “Inbound SSH” rule. This means that I can clearly see what hosts allow inbound SSH access. Like with my Azure post, I’m using a “data provider” to get my public IP address, but in a normal “live” network, you’d specify a collection of valid source address ranges.

Last steps before we create the Virtual Machine. We need to upload our SSH key, and we need to find the “AMI” (AWS Machine ID) of the image we’ll be using. To create the key, in this directory, along side the .tf files, I’ve put my SSH public key (called id_rsa.pub), and we load that key when we create the “my_key” resource. To find the AMI, we need to make another data call, this time asking the AMI index to find the VM with the name containing ubuntu-bionic-18.04 and some other stuff. AMIs are region specific, so the image I’m using in eu-west-2 will not be the same AMI in eu-west-1 or us-east-1 and so on. This filtering means that, as long as the image exists in that region, we can use “the right one”. So let’s take a look at this file.

So, now we have everything we need to create our VM. Let’s do that!

In here, we specify a “user_data” file to upload, in this case, the contents of a file – CloudDev.sh, but you can load anything you want in here. My CloudDev.sh is shown below, so you can see what I’m doing with this file :)

So, having created all this lot, you need to execute the terraform workload. Initially you do terraform init. This downloads all the provisioners and puts them into the same tree as these .tf files are stored in. It also resets the state of the terraform discovered or created datastore.

Next, you do terraform plan -out tfout. Technically, the tfout part can be any filename, but having something like tfout marks it as clearly part of Terraform. This creates the tfout file with the current state, and whatever needs to change in the Terraform state file on it’s next run. Typically, if you don’t use a tfout file within about 20 minutes, it’s probably worth removing it.

Finally, once you’ve run your plan stage, now you need to apply it. In this case you execute terraform apply tfout. This tfout is the same filename you specified in terraform plan. If you don’t include -out tfout on your plan (or even run a plan!) and tfout in your apply, then you can skip the terraform plan stage entirely.

Once you’re done with your environment, use terraform destroy to shut it all down… and enjoy :)

Featured image is “code crunching” by “Ruben Molina” on Flickr and is released under a CC-ND license.

"Confused" by "CollegeDegrees360" on Flickr

Using AWSCLI on Ubuntu/Ubuntu-in-WSL

This is a brief note to myself (but might be useful to you)!

awscli (similar to the Azure az command) is packaged for Ubuntu, but the version which is in the Ubuntu 18.04 repositories is “out of date” and won’t work with AWS. You *actually* need to run the following:

sudo apt update && sudo apt install python3-pip -y && sudo -H pip3 install --upgrade awscli

If you’ve unfortunately already installed awscli from apt, do the following:

sudo apt remove awscli -y

Then, logout (for some reason, binary path caching is a thing now?) and log back in, and then run the above pip install line.

Solution found via this logged issue on the awscli git repo.

Featured image is “Confused” by “CollegeDegrees360” on Flickr and is released under a CC-BY-SA license.

"Feb 11" by "Gordon" on Flickr

How to quickly get the next SemVer for your app

SemVer, short for Semantic Versioning is an easy way of numbering your software versions. They follow the model Major.Minor.Patch, like this 0.9.1 and has a very opinionated view on what is considered a Major “version bump” and what isn’t.

Sometimes, when writing a library, it’s easy to forget what version you’re on. Perhaps you have a feature change you’re working on, but also bug fixes to two or three previous versions you need to keep an eye on? How about an easy way of figuring out what that next bump should be?

In a recent conversation on the McrTech slack, Steven [0] mentioned he had a simple bash script for incrementing his SemVer numbers, and posted it over. Naturally, I tweaked it to work more easily for my usecases so, this is *mostly* Steven’s code, but with a bit of a wrapper before and after by me :)

Late Edit: 2022-11-19 ictus4u spotted that I wasn’t handling the reset of PATCH to 0 when MINOR gets a bump. I fixed this in the above gist.

So how do you use this? Dead simple, use nextver in a tree that has an existing git tag SemVer to get the next patch number. If you want to bump it to the next minor or major version, try nextver minor or nextver major. If you don’t have a git tag, and don’t specify a SemVer number, then it’ll just assume you’re starting from fresh, and return 0.0.1 :)

Want to find more cool stuff from the original author of this work? Here is a video by the author :)

Featured image is “Feb 11” by “Gordon” on Flickr and is released under a CC-BY-SA license.

"Key mess" by "Alper Çuğun" on Flickr

Making Ansible Keys more useful in complex and nested data structures

One of the things I miss about Jekyll when I’m working with Ansible is the ability to fragment my data across multiple files, but still have it as a structured *whole* at the end.

For example, given the following directory structure in Jekyll:

+ _data
|
+---+ members
|   +--- member1.yml
|   +--- member2.yml
|
+---+ groups
    +--- group1.yml
    +--- group2.yml

The content of member1.yml and member2.yml will be rendered into site.data.members.member1 and site.data.members.member2 and likewise, group1 and group2 are loaded into their respective variables.

This kind of structure isn’t possible in Ansible, because all the data files are compressed into one vars value that we can read. To work around this on a few different projects I’ve worked on, I’ve ended up doing the following:

- set_fact:
    my_members: |-
      [
        {%- for var in vars | dict2items -%}
          {%- if var.key | regex_search(my_regex) is not none -%}
            "{{ var.key | regex_replace(my_regex, '') }}": 
              {%- if var.value | string %}"{% endif -%}
              {{ var.value }}
              {%- if var.value | string %}"{% endif %},
          {%- endif -%}
        {%- endfor -%}
      ]
  vars:
    my_regex: '^member_'

So, what this does is to step over all the variables defined (for example, in host_vars\*, group_vars\*, from the gathered facts and from the role you’re in – following Ansible’s loading precedence), and then checks to see whether the key of that variable name (e.g. “member_i_am_a_member” or “member_1”) matches the regular expression (click here for more examples). If it does, the key (minus the regular expression matching piece [using regex_replace]) is added to a dictionary, and the value attached. If the value is actually a string, then it wraps it in quotes.

So, while this doesn’t give me my expressive data structure that Jekyll does (no site.data.members.member1.somevalue for me), I do at least get to have my_members.member1.somevalue if I put the right headers in! :)

I’ll leave extending this model for doing other sorts of building variables out (for example, something like if var.value['variable_place'] | default('') == 'my_members.member' + current_position) to the reader to work out how they could use something like this in their workflows!

Featured image is “Key mess” by “Alper Çuğun” on Flickr and is released under a CC-BY license.