Home Lab - Configuring the cattle · Viktor Adam's blog

Let me explain the configuration method I use for my services and HTTP endpoints. Spoiler: it’s Docker and it’s automated.

So far…

In the previous posts of the series, I walked you through how I’ve set up my home lab with ARMv8 servers and docker-compose and how it’s changed to Swarm.

While I only had an Nginx and maybe 3 Flask services in the stack, I could have just used some hard-coded configuration (I didn’t) to get them to work together. Even for small stacks though, it makes complete sense to let the system describe and configure what it needs to, leaving you with time to spend on more important things instead, like developing your apps and tools, not fiddling with config files all the time.


OK, so I don’t want to deal with configuration files, but I kind of have to, right? Unfortunately.

If I do have to write a config file once though, then I can just take a bit of extra time and care to create it as a template, so I don’t have to touch it the next time something changes in the system. If I’m lucky.

There are quite a few templating languages and frameworks around, Go templates seem to be quite popular these days, for example. You can even find systems that use templates to auto-generate configuration for you, based on current state read from the underlying system. If you want to go further, there are others that can run actions when the configuration is updated, reloading HAProxy for example with SmartStack or Consule Template. Then, there are systems, which can tap into your existing services to generate their own configuration periodically, or on changes, and reload their internal logic or routing, for example Traefik. Have a look at the open-source tools in this space, they’re all pretty awesome!

I sort of like doing things the hard way, so naturally, I wrote my own configuration generator tool: docker-pygen.

It’s nothing special really, it was just the most convenient for me at the time. It’s written in Python, and it uses Jinja2 templates, which I was already familiar with through Flask, and it uses the Docker API through the docker-py SDK to listen for events and read current state. It was heavily inspired by docker-gen from Jason Wilder, but I really didn’t want to start using Go templates, and it didn’t support Swarm.

By running the docker-pygen container in the stack, and giving it access to the Docker daemon, it can listen for selected Docker events and evaluate its template, with the Docker service, task, container and node information available to it as variables. If the target file changes, it can also execute an action, like sending a signal to a container, or restarting one.

Some of the information I need in my templates really are dynamic that change all the time, like IP addresses of the containers for example. Some of it is static though, and will always stay the same for a service. For example, the domain the endpoint is exposed on, or the internal port number to forward requests to, etc. For these metadata, I’m using Docker service labels in the stack YAML, so it’s all in code and checked into version control.

Reverse proxy config

I’ve mentioned in previous posts that I’m an Nginx fan, I think it’s just awesome! Nginx doesn’t do dynamic backends though, in the open-source community version at least, so every time a new container starts or stops, the target backend addresses need to be updated in the Nginx configuration file, and the master process needs to be reloaded. This can be done by sending a HUP signal to the process. If you use the official Nginx library image, then you can send a reload signal with docker kill -s HUP <nginx-container>, that will be forwarded to the main process, pid 1 in the container.

You can have a look at a working template in this GitHub repo as an example. Let me explain the main bits here too.

# included from the root /etc/nginx/nginx.conf as
# include /etc/nginx/conf.d/*.conf; {% for virtual_host, same_host_services in services|groupby('labels.routing-host') %} {% if not virtual_host %} {% continue %} {% endif %} {% for context_path, matching_services in same_host_services|groupby('labels.routing-context') if matching_services|map(attribute='labels.routing-port') %} {% set server_name = '%s__%s'|format(virtual_host, context_path)|replace('/', '_') %} upstream {{ server_name }} { {% for service in matching_services if service.labels['routing-port'] %} # service: {{ service.name }} {% for task in service.tasks.with_status('running') if task.networks.matching('web').first_value.ip_addresses.first_value %} # {{ task.name }} server {{ task.networks.matching('web').first_value.ip_addresses.first_value }}:{{ service.labels['routing-port'] }}; {% endfor %} {% endfor %} } {% else %} {% continue %} {% endfor %} # ... server blocks below ... {% endfor %}

This example generates one upstream per domain and URI prefix, and it lists the IP addresses of all the running tasks for a service responsible for dealing with requests on these URLs. If you’re using Docker health-checks, and you should, then it will filter out the ones that are running but unhealthy, because of the .with_status('running') bit in the template.

# ... continued from above server { server_name {{ virtual_host }}; listen 443 ssl http2; ssl_certificate /etc/letsencrypt/live/{{ virtual_host }}/fullchain.pem; ssl_certificate_key /etc/letsencrypt/live/{{ virtual_host }}/privkey.pem; gzip_types text/plain text/css text/xml application/xml application/xml+rss text/javascript application/javascript application/x-javascript application/json image/svg+xml font/otf font/ttf font/woff font/woff2; proxy_buffering off; error_log /proc/self/fd/2; access_log /proc/self/fd/1 access_log_format; {% for context_path, matching_services in same_host_services|groupby('labels.routing-context') if matching_services|map(attribute='labels.routing-port') %} {% set first_service = matching_services|first %} {% set internal_context_path = first_service.labels['routing-internal-context']|default('', true) %} {% set server_name = '%s__%s'|format(virtual_host, context_path)|replace('/', '_') %} {% set max_body_size = first_service.labels['routing-max-body']|default('', true) %} location {{ context_path }}/ { {% if first_service.labels['routing-auth'] %} {% set realm = first_service.labels['routing-auth-realm']|default(first_service.name, true) %} auth_basic "{{ realm }}"; auth_basic_user_file {{ first_service.labels['routing-auth'] }}; {% endif %} {% if first_service.labels['routing-on-https'] %} proxy_pass https://{{ server_name }}{{ internal_context_path }}/; {% else %} proxy_pass http://{{ server_name }}{{ internal_context_path }}/; {% endif %} proxy_set_header Host $http_host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header X-Forwarded-Proto $scheme; # HTTP 1.1 support proxy_http_version 1.1; proxy_set_header Connection ""; {% if max_body_size != '' %} client_max_body_size {{ max_body_size }}; {% endif %} add_header Vary Origin; } {% endfor %}

Here, we are just mapping the upstreams to domains and locations. I use common settings for everything that makes sense for my systems, and allow overriding some of them from labels, for example maximum upload size or basic authentication settings.

Notice that the configuration doesn’t refer to any of the services or tasks explicitly. It doesn’t have special cases or one-off extras for some of them. Everything is treated the same and the behaviour can be altered through runtime metadata attached to the containers.

The PyGen service is using a similar configuration like this below.

services: nginx: image: nginx:1.13.6 # ... nginx-pygen: image: rycus86/docker-pygen command: > --template /etc/docker-pygen/templates/nginx.tmpl --target /etc/nginx/conf.d/default.conf --signal nginx HUP --interval 3 10 --swarm-manager --workers tasks.web_nginx-pygen-worker deploy: replicas: 1 placement: constraints: - node.role == manager volumes: - /mnt/shared/nginx-config:/etc/nginx/conf.d - /mnt/shared/compose/nginx-pygen.tmpl:/etc/docker-pygen/templates/nginx.tmpl:ro - /var/run/docker.sock:/var/run/docker.sock:ro nginx-pygen-worker: image: rycus86/docker-pygen:worker command: --manager web_nginx-pygen read_only: true deploy: mode: global volumes: - /var/run/docker.sock:/var/run/docker.sock:ro # ...

I use a template file, that is also checked into version control, and I get it to signal the nginx service to reload the configuration when something changes. The --interval argument allows for batching the signal actions, so that even if the state changes 200 times in 10 seconds, we’ll only reload the Nginx configuration once.

The worker image shares the codebase with the main tool, but it doesn’t generate templates. Its purpose is, to listen for Docker events on all nodes in the Swarm cluster, and forward them to the manager instance. They can also execute actions, received from the manager, that can only target containers running on the same node. Restarts for example can be executed on the Swarm service level, with docker service update <service> --force, but signals can only be sent to individual containers, which are not necessarily running on the manager’s node.

This is why the worker is a global service, that will have an instance running on every node in the cluster. The manager instance has to run on a Swarm manager node, so it can access the Swarm APIs, which are not available to the worker nodes.

$ docker service ls
Error response from daemon: This node is not a swarm manager. Worker nodes can't be used to view or modify cluster state. Please run this command on a manager node or promote the current node to a manager.

SSL and certificates

I want my services to only expose secure endpoints to the internet. For this reason, all of them are HTTPS enabled and HTTP requests are simply redirected to the HTTPS variant.

To get SSL certificates, I use certbot from the awesome people of Let’s Encrypt. Their missions is to secure the internet, which is very noble, and for this reason, they provide free certificates, that are valid for 3 months. Before they expire, you can easily renew them using certbot. This is how I do it.

I have an Alpine Linux based Docker image, that has the certbot tool installed. Once every 12 hours, it checks all my subdomains to see if their certificate is due for renewal. It is done as a simple, parameterized command, executed in the container, not wrapped in another tool (yet). The main process is basically an infinite loop with sleep, and it has signal support to start the renewal immediately when I want it to set up a new domain quickly. Not very fancy, I know, but it gets the job done.

The actual renewal process is done by serving up a static file over HTTP on the new domain. This is really the only area that is accessible on port 80. The request will come in as http://your.domain.com/.well-known/acme-challenge/<token>, and the token name plus the content it expects come from certbot.

There other ways to verify that you own a domain, which might be simpler for your use-case. Check out the documentation to see those.

Assuming the domain is already set up and it’s pointing to your origin server, this process should be fairly straightforward. certbot allows you to define hooks for the setup and cleanup steps. For me, these look like this:

# setup script:
echo "${CERTBOT_VALIDATION}" > /var/www/challenge/${CERTBOT_TOKEN} # cleanup script:
rm -rf /var/www/challenge/*

The certbot-authenticator script takes the validation token parameters and saves them in a location where Nginx can access them. The certbot-cleanup script is basically just removing these. The actual certbot invocation is in a Bash script, generated by PyGen.

{% for ssl_domain, matching in services|groupby('labels.routing-host') if ssl_domain %} echo 'Checking certificate renewal for {{ ssl_domain }} ...' certbot certonly -n -d {{ ssl_domain }} --keep --manual \ --manual-auth-hook /usr/bin/certbot-authenticator \ --manual-cleanup-hook /usr/bin/certbot-cleanup \ --manual-public-ip-logging-ok \ --email {{ services.matching('certbot-helper').first.labels.letsencrypt_email }} \ --agree-tos
{% endfor %}

The email address, that I’ve registered with Let’s Encrypt, is defined in a Docker service label. The list of domain names also come from labels, which are attached to the services that they belong to. When I want to set up a new endpoint on a new subdomain, I just need to define it in the stack YAML with the appropriate labels, and the rest is magic!

The last piece of the puzzle is in the Nginx configuration. The server blocks contain SSL configuration like this:

server { ... ssl_certificate /etc/letsencrypt/live/{{ virtual_host }}/fullchain.pem; ssl_certificate_key /etc/letsencrypt/live/{{ virtual_host }}/privkey.pem; ...

To be honest, I still have a few manual steps to do in this workflow, one of them is to register the new subdomain on my DNS provider. This is how I’m planning to automate it soon.

Domain registration

I’ve originally bought viktoradam.net from Namecheap. After a while, I found myself in need of a CDN, so I signed up for Cloudflare and transferred the DNS setup there. Every time I add a new subdomain, it needs to be registered on their system.

Cloudflare has a pretty nice API and even a ready-to-use Python SDK for it. My first option is to have a service running in my stack, that picks up new domain names from the other services’ labels, and registers them using the API, if they’re missing. This would be very similar to the certbot workflow. I might run into some timing issues though, as new DNS entries need a couple of seconds or minutes to come alive, so it might not be ready in time for the Let’s Encrypt domain validation request.

My second option is to reduce how much I have to do manually. I’m using a free Slack account with some automation already. Slack supports chatbots, and there are even Python modules for them that look promising. I could write a bot, to which I could tell about a new subdomain I want registered, and it would do it for me. Less clicking around!

I might end up using something different when I get around to actually do it, but right now, these two options seem viable to me.

Dynamic DNS

I host my services on my home network with a regular internet subscription. My provider doesn’t guarantee a fixed IP address, so whenever it changes, I need to tell Cloudflare about the new one. This is pretty simple and a very common problem, therefore there is a tool to do this for me.

ddclient has been around since 2006, and it’s proven very useful for many people. To keep things portable, I run it as a service in a Docker container using my multi-arch image. All it does is, it wraps the ddclient tool as the main process, so the parameters are the exact same. It needs a configuration file to describe the provider, access keys and the list of domains. This can easily be templated like this:

use=web, web=dynamicdns.park-your-domain.com/getip
login={{ services.matching('ddclient').first.labels.ddclient_email }}
password='{{ services.matching('ddclient').first.labels.ddclient_password }}'
zone={{ services.matching('ddclient').first.labels.ddclient_zone }}
{% for ssl_domain, matching in services|groupby('labels.routing-host') if ssl_domain %} {% if loop.index > 1 %} , {% endif %} {{ ssl_domain }} {% endfor %}

Once I have this file generated, I can use it in my stack. Whenever the configuration changes, I need to restart the container to pick up the changes.

version: '3.4'
services: ddclient: image: rycus86/ddclient command: --daemon=300 --ssl --debug --file /var/config/ddclient/ddclient.conf deploy: replicas: 1 volumes: - ddclient-config:/var/config/ddclient:ro ddclient-pygen: image: rycus86/docker-pygen command: > --template /var/config/ddclient/ddclient.tmpl --target /var/config/ddclient/ddclient.conf --restart ddclient --interval 3 10 --swarm-manager --workers tasks.stack_ddclient-pygen-worker deploy: replicas: 1 placement: constraints: - node.role == manager volumes: - ddclient-config:/var/config/ddclient - /var/run/docker.sock:/var/run/docker.sock:ro ddclient-pygen-worker: image: rycus86/docker-pygen:worker command: --manager stack_ddclient-pygen read_only: true deploy: mode: global volumes: - /var/run/docker.sock:/var/run/docker.sock:ro volumes: ddclient-config: driver: local driver_opts: type: nfs device: :/mnt/shared/ddclient o: addr=,rsize=8192,wsize=8192,timeo=15,hard,intr

Monitoring configuration

I use Prometheus to collect metrics from my services and servers. It is a brilliant, pull-based collector that can scrape target systems, and efficiently store the time-series data for their metrics, and the changes of those.

You can read more about Prometheus in the next part of the series, that is all about monitoring and logging.

The scrape targets are defined in a YAML file. Prometheus supports many service discovery methods to collect the actual endpoints, one of them is dns_sd_config, that can list the IP addresses of services behind a common DNS name. This plays nicely with Swarm networking, that includes an internal DNS resolver for reasons exactly like this.

# inside a container within a Swarm stack
$ nslookup service Name: service
Address 1: $ nslookup tasks.service Name: tasks.service
Address 1: service.5.d646d2cgpuplwezam678s2oe4.snet
Address 2: service.1.mpr253lbth3ux58flm3zo7w7e.snet
Address 3: bceffa7c3a40.snet
Address 4: 2c131e102fd6
Address 5: service.3.p3lvxp18azni2z979l4oslxe2.snet

The Prometheus configuration file can be easily templated as well. When it changes, it can be hot-reloaded by sending a HUP signal to the main process. The template I use, scrapes the Docker engine metrics from all the nodes in the cluster, plus all the services that have labels describing their metrics endpoints.

global: scrape_interval: 15s evaluation_interval: 15s external_labels: monitor: 'my-stack' rule_files: scrape_configs: - job_name: 'prometheus' static_configs: - targets: ['localhost:9090'] - job_name: 'docker' static_configs: - targets: {% for node in nodes %} - '{{ node.address }}:9323' {% endfor %} {% for job_name, services in services|groupby('labels.prometheus-job') %} {% if not job_name %} {% continue %} {% endif %} {% set service = services|first %} {% set port = service.labels['prometheus-port'] %} {% if not port %} {% continue %} {% endif %} - job_name: '{{ job_name }}' dns_sd_configs: - names: ['tasks.{{ service.name }}'] port: {{ port }} type: A refresh_interval: 5s {% endfor %}

To put it all together, this is how this automation looks like in my stack:

services: ... prometheus: image: rycus86/prometheus:2.1.0 deploy: replicas: 1 ports: - "9090:9090" volumes: - type: volume source: prometheus-config target: /etc/prometheus read_only: true volume: nocopy: true - prometheus-data:/prometheus:nocopy prometheus-pygen: image: rycus86/docker-pygen command: > --template /etc/docker-pygen/templates/prometheus.tmpl --target /etc/prometheus/prometheus.yml --signal prometheus HUP --interval 10 30 --swarm-manager --workers tasks.stack_prometheus-pygen-worker deploy: replicas: 1 placement: constraints: - node.role == manager labels: - prometheus-job=pygen-manager-prometheus - prometheus-port=9413 volumes: - prometheus-config:/etc/prometheus:nocopy - /mnt/shared/prometheus-pygen.tmpl:/etc/docker-pygen/templates/prometheus.tmpl:ro - /var/run/docker.sock:/var/run/docker.sock:ro prometheus-pygen-worker: image: rycus86/docker-pygen:worker command: --manager stack_prometheus-pygen read_only: true deploy: mode: global labels: - prometheus-job=pygen-worker-prometheus - prometheus-port=9414 volumes: - /var/run/docker.sock:/var/run/docker.sock:ro prometheus-node-exporter: image: rycus86/prometheus-node-exporter:0.15.1 deploy: mode: global labels: - prometheus-job=node-exporter - prometheus-port=9100 pid: host ... volumes: prometheus-config: driver: local driver_opts: type: nfs4 device: :/prometheus-config o: addr=,rsize=8192,wsize=8192,timeo=14,intr prometheus-data: driver: local driver_opts: type: nfs4 device: :/prometheus-data o: addr=,rsize=8192,wsize=8192,timeo=14,intr

What’s next?

It feels like, there is always one more thing to automate. Whenever it gets uncomfortable or cumbersome to change some configuration or to set something up, I’m trying to find a way to automate it, so I wouldn’t have to bother with it again. In the end, whatever I can do manually, I could automate as well, for almost everything.

Once most of our configuration is taken care of automatically, it’s good to know if it does actually work. The next post will go over all the monitoring and logging systems I have in my stack.

The series has these parts so far: