An ongoing project of mine involves the migration of home services (Unifi, Pi-hole, etc) to my Kubernetes cluster. This post explores my approach to migrating Pi-hole, with the help of MetalLB.

MetalLB Overview

MetalLB is a load balancer implementation for environments that do not natively provide this functionality. For example, with AWS, Azure, GCP and others, provisioning a “LoadBalancer” service will make API calls to the respective cloud provider to provision a load balancer. For bare-metal / on-premises and similar environments this may not work (depending on the CNI used). MetalLB bridges this functionality to these environments so services can be exposed externally.

 

 

MetalLB consists of the following components:

• Controller Deployment – A single replica deployment responsible for IP assignment.
• Speaker DaemonSet – Facilitates communication based on the specified protocols used for external services.
• Controller and Speaker service accounts – RBAC permissions required for respective components.
• Configuration ConfigMap – Specifies parameters for either L2 or BGP configuration. The former being used in this example for simplicity.

The Speaker and Controller components can be deployed by applying the MetalLB manifest:

kubectl apply -f https://raw.githubusercontent.com/google/metallb/v0.8.1/manifests/metallb.yaml

A configmap is used to complement the deployment by specifying the required parameters. Below is an example I’ve used.

apiVersion: v1
kind: ConfigMap
metadata:
namespace: metallb-system
name: config
data:
config: |
address-pools:
- name: default
protocol: layer2
addresses:
- 172.16.10.221-172.16.10.230

The end result is any service of type “LoadBalancer” will be provisioned from the pool of IP addresses in the above configmap.

 

PI-Hole Overview

Pi-Hole is a network-wide adblocker. It’s designed to act as a DNS resolver employing some intelligence to identify and block requests to known ad sites. An advantage of implementing it vs something like Ublock Origin, is PiHole operates at the network level, and is, therefore, device/client agnostic and requires no plugins/software on the originating device.

 

 

The makers of Pi-Hole have an official Dockerhub repo for running Pi-Hole as a container, which makes it easier to run in Kubernetes, but with some caveats, as is described below.

Storing Persistent Data with Pi-Hole

A Pi-Hole container can be fired up with relative ease and provides some effective ad-blocking functionality but if the container is deleted or restarted, any additional configuration post-creation will be lost, it would, therefore, be convenient to have a persistent location for the Pi-Hole configuration, so blocklist / regex entries / etc could be modified. The makers of Pi-Hole have documented the location and use of various configuration files. Of interest are the following:

adlists.list: a custom user-defined list of blocklist URL’s (public blocklists maintained by Pi-Hole users). Located in /etc/pihole

regex.list : file of regex filters that are compiled with each pihole-FTL start or restart. Located in /etc/pihole

 

Approach #1 – Persistent Volumes

This approach leverages a persistent volume mounted to /etc/pihole with a “Retain” policy. This would ensure that if the container terminates, the information in /etc/pihole would be retained. One disadvantage of this includes the operational overhead of implementing and managing Persistent Volumes.

Approach #2 – Config Maps

This approach leverages configmaps mounted directly to the pod, presented as files. Using this method will ensure consistency of configuration parameters without the need to maintain persistent volumes, with the added benefit of residing within the etcd database and is therefore included in etcd backups. This method also completely abstracts the configuration from the pod, which can easily facilitate updates/changes.

 

Implementation

Given the options, I felt #2 was better suited for my environment. YAML manifests can be found in https://github.com/David-VTUK/k8spihole.

 

00-namespace.yaml

Create a namespace for our application. This will be referenced later

apiVersion: v1
kind: ConfigMap
metadata:
namespace: metallb-system
name: config
data:
config: |
address-pools:
- name: default
protocol: layer2
addresses:
- 172.16.10.221-172.16.10.230

01-configmaps.yaml

This is where our persistent configuration will be stored.

Location for adlists:

apiVersion: v1
kind: ConfigMap
metadata:
name: pihole-adlists
namespace: pihole-test
data:
adlists.list: |
https://raw.githubusercontent.com/StevenBlack/hosts/master/hosts
......etc

Location for regex values

apiVersion: v1
kind: ConfigMap
metadata:
name: pihole-regex
namespace: pihole-test
data:
regex.list: |
^(.+[-_.])??adse?rv(er?|ice)?s?[0-9]*[-.]
......etc

Setting environment variables for the timezone and upstream DNS servers.

apiVersion: v1
kind: ConfigMap
metadata:
name: pihole-env
namespace: pihole-test
data:
TZ: UTC
DNS1: 1.1.1.1
DNS2: 1.0.0.1

02-deployment.yaml

This manifest defines the parameters of the deployment, of significance are how the config maps are consumed. For example, the environment variables are set from the respective configmap:

containers:
- name: pihole
image: pihole/pihole
env:
- name: TZ
valueFrom:
configMapKeyRef:
name: pihole-env
key: TZ

The files are mounted from the aforementioned configmaps as volumes:

volumeMounts:
- name: pihole-adlists
mountPath: /etc/pihole/adlists.list
subPath: adlists.list
- name: pihole-regex
mountPath: /etc/pihole/regex.list
subPath: regex.list
volumes:
- name: pihole-adlists
configMap:
name: pihole-adlists
- name: pihole-regex
configMap:
name: pihole-regex

03-service.yaml

Currently, you cannot mix UDP and TCP services on the same Kubernetes load balancer, therefore two services are created. One for the DNS queries (UDP 53) and one for the web interface (TCP 80)

kind: Service
apiVersion: v1
metadata:
name: pihole-web-service
namespace : pihole-test
spec:
selector:
app: pihole
ports:
- protocol: TCP
port: 80
targetPort: 80
name : web
type: LoadBalancer
---
kind: Service
apiVersion: v1
metadata:
name: pihole-dns-service
namespace: pihole-test
spec:
selector:
app: pihole
ports:
- protocol: UDP
port: 53
targetPort: 53
name : dns
type: LoadBalancer

Deployment

After configuring the configmaps, the manifests can be deployed:

david@david-desktop:~/pihole$ kubectl apply -f .
namespace/pihole-test created
configmap/pihole-adlists created
configmap/pihole-regex created
configmap/pihole-env created
deployment.apps/pihole-deployment created
service/pihole-web-service created
service/pihole-dns-service created

Extract the password for Pi-Hole from the container:

david@david-desktop:~/pihole$ kubectl get po -n pihole-test
NAME                                 READY   STATUS    RESTARTS   AGE
pihole-deployment-6ffb58fb8f-2mc97   1/1     Running   0          2m24s
david@david-desktop:~/pihole$ kubectl logs pihole-deployment-6ffb58fb8f-2mc97 -n pihole-test | grep random
Assigning random password: j6ddiTdS

Identify the IP address of the web service:

david@david-desktop:~/pihole$ kubectl get svc -n pihole-test
NAME                 TYPE           CLUSTER-IP       EXTERNAL-IP     PORT(S)        AGE
pihole-dns-service   LoadBalancer   10.100.40.39     172.16.10.226   53:31725/UDP   3m38s
pihole-web-service   LoadBalancer   10.107.251.224   172.16.10.225   80:30735/TCP   3m38s

Access Pi-Hole on the web service external IP using the password extracted from the pod:

All that remains is to reconfigure DHCP or static settings to point to the pihole-dns-service Loadbalancer address for its DNS queries.

I’m quite surprised how much it has blocked thus far (~48 hours of usage):

 

Happy Ad Blocking!

 

The persistent storage requirement for the container ecosystem

When we talk about containers we generally think about microservices and all things ephemeral. But does this mean that we can’t facilitate stateful workloads leverage persistent storage? Absolutely not.

In the docker world, we choose a storage “driver” to back our persistent storage onto. The driver we choose is based on a number of requirements and which operating system our Docker hosts run. The table below lists the recommended out-of-the-box drivers for Docker Community Edition.

Most of the above are battle-hardened, well-documented drivers. But what if we’re running a vSphere based environment and want to integrate with some vSphere resources?

vSan Storage Driver

Docker introduced the Docker Volume Plugin framework. This extended the integration options between Docker and other storage platforms including (but not limited to):

• Amazon EBS
• EMC Scaleio
• NFS
• Azure File Services
• iSCSI
• VMware based storage
  • vSAN, VMFS

 

The vSAN Storage Driver for Docker has two components:

vSphere Data Volume Driver

This is installed on the ESXi host and primarily handles the VMDK creation that is requested by the underlying container ecosystem. It also keeps track of the mapping between these entities.

 

vSphere Docker Volume Plugin

This is installed on the Docker host and primarily acts as the northbound interface that facilitates requests from users / API / CLI to create persistent storage volumes to be used by containers.

From an architectural perspective it looks like this:

 

Step 1 – The user instantiates a new docker volume, specifying the appropriate driver (ie VMDK).

Step 2 – The vSphere Data Volume Driver accepts the request and communicates via the ESXi host to the underlying storage, which can be vSAN, VMFS or a mounted NFS share.

Why use this?

A distinct advantage of leveraging vSphere-backed storage for containers is how we can utilise native capabilities of the underlying storage infrastructure. For example, if we use vSAN as the backend storage for containers we can leverage:

• Deduplication
• Compression
• Encryption
• Erasure Coding.

As of this week, I started a new position at Insight as a VMware/SDDC Solutions Architect/Evangelist. Exciting times!

I’ll be fortunate to work with the likes of established community contributors and experts in the field such as vJenner and Chan.

Why Insight?

The IT landscape is constantly changing and with it, we as IT professionals must adapt accordingly. I wanted a new challenge, to expand my horizons and delve deeper into the areas I’ve already gained experience in. Insight is such a place that will allow me to do this. My new boss described it quite eloquently: “We sell everything to everyone”. This doesn’t mean that Insight will push for subpar products though – part of the philosophy here is that we’re transparent, flexible and agnostic. Leading solutions are evaluated and assessed to address a plethora of challenges presented by both existing and new customers. Multiple vendors, multiple products, private/public/hybrid cloud and everything in-between is considered as part of the product/solutions/services portfolio.

I will continue to focus primarily on VMware based solutions with a bit of AWS on top, together with complementary technologies (IE storage, networking, containers, automation, scripting)