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tags: sds self-hosting

A gentlemans guide to self-hosting

I’m looking to self host more and more of my infrastructure, this comes with the old question of hardware maintenance and service failover; an often forgotten question around deployment reproducibility (aka the cattle vs pets argument). Finally a more nuanced question also arised around security, process and data isolation.

What do you plan to self host on?

Before we start talking about k8s like the hammer for every ~problem~ nail in sight, lets first consider what are we actually going to self host, and what are we looking to self host on. To make this process easier to follow, and because this is ultimately meant to be an engineering-log format blog, I will talk through my own adventure in re-self-hosting.


A pretty good driving force for building up your datacenter-in-a-closet is deciding on what right now you plan to self host (we can consider future expansion afterwards), and what sort of SLAs you wish to meet (if any).

Here is my list:

  1. CalDAV host (contacts& calendar syncing).
  2. Git repository (SSH).
  3. XMPP node.
  4. Email system without a web frontend.
  5. Taskwarrior backend.
  6. This blog.

I know I want to add more things in the future, but these services I already either self host or have running in someone else’s computer (“the cloud”).

XMPP and Email will probably need pretty decent SLA’s, though I use to self host email on a MkI RaspberryPI (when they first came out) and a USB HDD RAID array. I use to have to compile my own rpi kernel back in the day just to get the raid array + LXC to work… So ultimately I might be rather laissez-faire about my SLA’s.

I’m willing to accept up to 3 days of downtime for email, maybe 1 day for XMPP and 1 week for everything else.. Per month. 👌 :cowboypepe: I do however plan to migrate my friends to XMPP; they probably will not appreciate a day of downtime.


For me its fairly simple:

  1. The compromise of any one service should not give an attacker access to any other.
  2. The compromise of any service should not compromise my personal home network.
  3. If any hosted service needs to talk to another, it has to do so in the same way as I would outside the network (network isolation).


Considering my SLA’s we can start thinking about our hardware choices, the reason to do things in this order is because it makes us think about our data redundancy and backup strategy ;)

The first question to ask is homogeneous or heterogeneous? I want to support hetrogenous hardware, because I’m cheap and this lets me both aquire (whatever is cheap) and well have a lower power bill, less noise (inaudiable actually, is a requirement for me).

Next question is around contingency of data.

  1. Some services can technically survive data loss:
    • Git is meant to be a distributed system, I have repositories cloned on multiple machines.
    • Ditto my taskwarrior setup (also.. it doesnt contain anything that I wouldn’t mind loosing tomorrow (unlike my git repos)).
    • This blog is static pages from a git repo.
  2. I do not want to suffer data loss due to drive failure. I also do not want drive failure to impact service availability.
    • This all means RAID.
  3. Some services cannot survive data loss:
    • CalDAV and Email, though I have copies of data on various system, I would rather not loose data from either.
    • Probably the same for XMPP, but :cowboypepe:

Hardware architecture

You probably have already arrived at this answer, but it’s a good exercise to get to this point after actually writing answers down to the questions above - I had a very different idea in my mind before I started writing this post.

  1. Main work nodes need to run RAID arrays - if one drive fails, I do not want this to lead to immediate downtime.
  2. Backups, backups, backups:
    • Local hot snapshots.
    • Local cold snapshots (aka backup to removable media).
    • Remote periodic snapshots/backups.
    • All backups must be encrypted at rest and in transit (for remote backups).
    • Local hot and remote backups should be automatic (I wont remember to do them on time).
  3. All nodes should sit on UPS’s
  4. I will need multiple worker nodes to host services - I will ultimately need to take machines offline to replace dead drives, or motherboards ( ͡° ͜ʖ ͡°)

Cluster options

You already knew it was going to go here. I need (reasonably) High Availability for multiple workloads. There are existing options in this market, lets have a maybe quick brush over some of these (some not so quick, since they are de facto industry standards that I (and you ( ͡° ͜ʖ ͡°)) work with every day).

The hammer: K8S

Kubernetes has basically won this war, at least in industry, and its the de-facto standard for deploying microservices.


  1. Containarised deployment provides security in process isolation.
  2. Process resource limitation - processes using more resources than specified get restarted, this can be advantages from a HA and security perspecive, as you avoid hardware lockups.
  3. Centralised deployment configuration, as code; YAML, YAML everywhere as you define what your cluster looks like in one place. SDN and all…
  4. Software defined network topologies - good from a security perspective for isolation.
  5. Industry standard; when in Rome. Pods run docker images, you can use existing stuff.


  1. Complex to deploy and manage. Really.
  2. Microservice orientated - this is good if you want to denormalise your software architecture, but what if you want to run postfix+dovecot+spamd+dkim+…… together? You can shove all that in a Docker image and make a mega pod, but k8s will supervise the health of that pod as a whole, not of each process.
  3. Linux only - furthermore you probably will have to run a SysD distro, I plan to run this on *BSD.

Tesco’s own brand: Openshift


  1. You basically run RHE k8s.


  1. You basically run RHE k8s.

Jokes aside, we are evaluating this at work. I may write more here.


I really misunderstood this for a while, until I actually spent time looking at it. I think it will be possible to wrangle Mesos into managing a cluster like this, but thats not really what its for.

Diet Kubernetes: K3S

Basically k8s after spending time in the gym wrapped in cling film, presumably the sweat has had a shrink wrapping effect and all the bloat has been packaged in a single binary.


  1. Single binary makes deployment easy
  2. ARM optimised, I can run RPI nodes (heterogeneous hardware is important for me, also frankly I won’t need more compute power than a few RPI’s).


  1. You’re still managing a k8s stack

My mustache brings all the gentlemen to the barbers: Openstack

Actually, this is going one level up - you use this to build a cloud onto which you deploy k8s et al. If kubernetes is a hammer, then this is a mallet and I’m not sure my body is ready to deploy this beast.


I found this one much later, its a very, very interesting architecture and I think it might actually be worth trying out. Instead of denormalising your software architecture into horizontally scaling deployments of individual service components (aka microservices); you divide your setup into pods based on data access policies. I think they use a fancier word to describe this, but basically instead of podding individual services, you pod user data. Thus you would have one pod for an email stack, for one user.

In sandstorm parlance these pods are called grains, and you would thus have one grain per user per service. If I had 10x email users, I would have 10x grains, each one containing its own comprehensive email system.

This is a massive security gain, but I have only just found out about it and this post is actually being written post-factum.

NIHS: roll your own 👌


  1. Does whatever you want, how you want it.


  1. Probably doesnt work.

What’s in a cluster anyway

I could also just run up a bunch of nodes and provision them with ansible (or some other fancier tool). This will probably give me 80% of the value with 20% of the required effort. Especially if I provision services to run in Jails. This would give me process isolation, but still allow some processes to talk to each other (e.g. if I ran postfix+dovecot in the Linux world (I’m going to have to reevaluate this setup if I move it to BSD)); I would also get network isolation with jails. Having the jails backed by ZFS gives me encrypted atomic snapshots, and its easy enough to schedule remote snapshots using something as simple as SSH + crontab.

The only things I would miss, is automatic workload migration when de-provisioning a server - I would have to run ansible manually; though technically deprovisioning a k8s node still requires manual interaction to taint & drain it.

I also would not get the safety of automatic hardware failover - in other words, pod migration if one node dies. But have a look at my SLA times again. They’re pretty lax; lax enough that as long as I have decent data availability, I could simply spin up the dead jails in a new node by taking the last known snapshot from my local hot/online backups.

But if you think about it really hard, some might even say too hard , you could automate this. You could then build a simple distributed system which would automatically migrate jails by way of ZFS snapshots between nodes. It could even suggest the specific node that a jail (or LXC container, I should say at this point) should live in, based on resource usage. It could also allocate drive resources automatically for you to provision a new jail, based on node resource usage.

Such a system could even ensure realtime data redundancy amongst nodes for rapid failover in the event of a node failure.

For such a system, the operator would need little more than his ansible playbooks to provision individual services; the additional configuration would be around failover polices and node groups for some form of pseudo availability zones (or real availability zones, if one is a particularly financially well-endowed gentlemen).


Having these ideas in mind, I decided to make such a System for Cluster Resource Allocation and Provisioning.

Or simply: SCRAP.

It does exactly what it sounds like ͡° ͜ʖ ͡ –


As a sort of epilogue, I would like to give a TL;DR summary of the content above, and discuss the reason for this post:

I want to get my feet wet, where do I start?

You probably already know of a few curated awesome-xxxx lists well, there is one for self hosted software and deployment configurations:

  1. Use that as your guide for what part of your digital life you want to self-host.
  2. Understand that self-hosting doesn’t mean own hardware. You can still run this in someone else’s computer (DO/AWS/etc).

If you are ready for the own hardware adventure:

  1. Make a list of exactly what you have today that you will need to run. There can always be more tomorrow, but first consider what you are willing to port right now. And focus on porting, not standing up a new service; as this removes one unknown.
  2. Consider your SLAs, this will influence the kind of hardware you need (UPS’s, RAID, mobile broadband for failover, etc).
  3. Consider your security model, if only a little.
  4. Based on SLAs considerations, decide if you want managed deployments.
  5. Based on your desired SLAs and security models, consider if you want virtualised deployments.
  6. The outcomes of the last two points are your decision of whether or not to essentially run a private cloud.
  7. Get your feet wet and run a single node! :))

Why I’m making SCRAP

I hope that eventually SDS/SCRAP will become a simple and lightweight system for managing containarised deployments, giving you the benefit of a private cloud with something like k3s but without forcing you to denormalise your deployments.

( ✧≖ ͜ʖ≖)