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An interesting Tailscale + Docker gotcha

2026-01-29T00:00:00Z

As I’ve written about before, I use Tailscale for a lot of things. I thought I had it set up in a reasonably secure manner, but I recently noticed a problem.

I use Tailscale’s ACLs to limit what each node can access, based on the tags I apply to it. So an app node can’t access anything via Tailscale, while an integration or server node can access things tagged with either app or integration. This is expressed pretty simply in the Tailscale ACL JSON:

{
	"tagOwners": {
		// Servers that can be SSH'd into
		"tag:server": [],
		// Applications that are exposed on tailscale but never connect out
		"tag:app": [],
		// Things which talk to other services over tailscale (connecting to apps etc)
		"tag:integration": [],
	},
	"grants": [
		{
			// Users can access everything
			"src": ["autogroup:member"],
			"dst": ["*"],
			"ip":  ["*"],
		},
		{
			// Servers and integrations can access integrations and apps
			"src": ["tag:server", "tag:integration"],
			"dst": ["tag:integration", "tag:app"],
			"ip":  ["*"],
		},
	],
}

Over the past week I’ve been setting up a private Forgejo instance behind Tailscale, complete with an actions runner that runs things using a docker-in-docker container. I didn’t want the runner knowing anything about Tailscale, so I had it configured to speak to Forgejo direct over HTTP (forgejo:3000) instead of using full Tailscale HTTPS URL that I use when accessing it (http://git.example-net.ts.net/)¹.

Everything was going fine, until I forgot to do that translation… and it worked. My Forgejo action runners could access anything on my tailnet. I run several things on Tailscale that just have authentication turned off, on the basis that only authorised devices can access them. Things like the admin interface for this website. I definitely didn’t intend for any workflow I run on my git server to have access to edit my website!

This wasn’t just limited to Forgejo, either. Any docker container I was running could access the tailnet. In hindsight it’s fairly obvious why: the host is running Tailscale, connected as a node tagged with my server tag. That creates a tailscale0 interface, and automagically sets up iptables rules to route Tailscale traffic over the interface. Docker also automagically sets up iptables rules to bridge traffic, and apparently these two sets of rules interact in such a way that traffic from Docker containers is allowed to route via the tailscale0 interface.

I say it’s fairly obvious in hindsight — there’s no reason why Docker would special case any particular host interface after all — but it still feels pretty surprising. Because both bits of software inject their own iptables rules, I never really had a good mental model for how they interact. The host Tailscale node was a completely separate building block to Docker. It would be a pain to use either of them if they didn’t do these rules, but it’s also one of the reasons I don’t really like “magical” things².

There are lots of ways to fix this, but none of them feel particularly great. You can configure both Tailscale and Docker to not automatically fiddle with iptables and handle the rules yourself, but I really hate dealing with iptables³. As a stopgap I did hold my nose and add some iptables rules to drop traffic to the tailscale0 interface if it originated from the IP ranges that Docker was configured to use:

iptables -I DOCKER-USER -s 192.168.0.0/16 -o tailscale0 -j DROP
iptables -I DOCKER-USER -s 172.17.0.0/12 -o tailscale0 -j DROP

The DOCKER-USER chain is a nice little escape hatch; it comes before the main auto-generated DOCKER chain, and Docker leaves the rules in it alone.

So I added these rules, and felt pretty good about myself, and then… everything started breaking in weird ways. After some debugging I realised the problem was DNS⁴. The server’s DNS resolver is 100.100.100.100, a special Tailscale address. This is so that it can resolve tailnet hostnames via MagicDNS (and so I don’t have to configure my custom DNS servers manually on each device; Tailscale does it for me). My new iptables rules inadvertently dropped all the DNS packets coming from docker containers. D’oh.

Obviously the solution here is to double down and add MORE iptables rules:

iptables -I DOCKER-USER -s 192.168.0.0/16 -d 100.100.100.100 -o tailscale0 -j ACCEPT
iptables -I DOCKER-USER -s 172.17.0.0/12 -d 100.100.100.100 -o tailscale0 -j ACCEPT

This got DNS working again, but it all feels a bit gross. Not least because to actually make these persist you need to use iptables-save, and then you also get all the rules that both Docker and Tailscale have inserted. I came across a script to filter out the Docker ones, but… yuck⁵.

I realised a cleaner idea might just be to lock down what server tagged nodes could access within Tailscale itself. That way I can avoid touching iptables at all. It’s handy to be able to curl services from the host when debugging, but it’s not really necessary. So I removed that access, and… stuff broke again. I’m using my Forgejo instance as a registry for some of the docker images I run, so the docker daemon needs to be able to reach it. I ended up making a new tag for infrastructure, which can be accessed from server devices. This does still allow all the docker containers to reach Forgejo, but I already have it set up with appropriate access controls and public/private repository splits. Forgejo is a service designed to run publicly, so this seems a reasonable trade-off for convenience. I used the tests feature of Tailscale’s ACL config to make sure I’d got the rules right:

{
	"tests": [
		{
			// Servers can only access infrastructure
			"src":   "tag:server",
			"proto": "tcp",
			"allow": [
				"tag:infrastructure:8080",
			],
			"deny": [
				"100.84.16.43:8080",
				"me@example.com:8080",
				"tag:server:8080",
				"tag:app:8080",
				"tag:integration:8080",
			],
		},
	],
}

The whole situation still feels a bit messy. If I ever get around to switching to nftables I might loop back and manually craft some rules for routing traffic, instead of leaving Tailscale and Docker to do their own thing.

I discovered later on that logging into the container registry at forgejo:3000 actually issued a redirect to https://git.example-net.ts.net/ so this was all basically for naught… ↩︎
I didn’t use Tailscale’s MagicDNS for a long time just because the word “magic” put me off. Only when I eventually got around to learning how it worked, and seeing that it wasn’t really that magical under the hood, did I change my mind. ↩︎
nftables seems far better in lots of ways, but I can’t really be bothered migrating. Maybe next time I reimage the server for whatever reason… ↩︎
It’s always DNS… ↩︎
Again, nftables would almost certainly help here. It actually has (gasp) configuration files. But again, I really didn’t want to spend the time migrating. ↩︎

Exposing game servers over Tailscale

2025-12-07T00:00:00Z

I’ve recently been playing a lot of Factorio with a friend. I’ve been hosting, but my desktop computer is behind far too many layers of NAT, and I can’t be bothered dealing with setting up port forwards. Up until today we made do with Steam’s networking support, which in our case ended up relaying the connection via one of their servers. This is amazing as a free, no-hassle service, but the performance was so-so. We’d get random lag spikes, or the initial map download would crawl along at about 1/100th of the speed we should be able to get. We’re both fans of Tailscale though, so maybe there’s an easy solution there?

Tailscale even have an article on sharing a Factorio server but it’s a ten minute long video¹, and focused on setting up an actual dedicated server in Docker rather than just clicking the convenient “Host” button in the game client. What we did instead was:

I shared my desktop’s Tailscale node with my friend, by creating a sharing link in the Admin console
My friend accepted the link, and could then see my machine in their admin panel
I used tailscale lock to sign my friend’s desktop’s node key, as I have tailnet lock enabled
I added a grant to my tailnet’s ACL to permit access from my friend to the specific IP/port on my tailnet:

		{
			"src": ["friend@example.com"],
			"dst": ["100.0.0.42", "fd7a::42"],
			"ip":  ["udp:34197"],
		}

After this, my friend could connect to Factorio by entering the Tailscale IP address, or the Tailscale hostname (as they use MagicDNS). Running tailscale status shows that Tailscale managed to establish a direct connection despite the many layers of NAT involved, and the performance improvements were significant and immediate.

We did a bit of testing, and confirmed that no other services on my machine are accessible. And sharing a machine by default only allows it to accept incoming connections, so I can’t get unwanted access to anything on my friend’s Tailnet, either.

I’ve written before about all the different ways I use Tailscale; this is yet another new way it’s solved a problem for me.

I’m not a fan of video tutorials at the best of times, but especially not when I want to do something as quickly as possible so I can get back to ~~my addiction~~ growing the factory. ↩︎

Avoiding the Consequences of Dumb Laws with Tailscale

2025-09-30T00:00:00Z

More and more sites are implementing privacy-invading age checks or just completely blocking the UK thanks to the Online Safety Act.

Protecting kids from some content online is certainly a noble goal, but the asinine guidance from Ofcom, threats of absolutely disproportionate fines, and the stupidly broad categories of content have resulted in companies just giving up or going through a tick-box exercise that offers very little protection but lots of inconvenience and a complete invasion of privacy.

Instead of uploading my ID to some third party company, I’ve taken to proxying my traffic through to a country that doesn’t have such stupid laws. Thankfully, Tailscale makes this really easy. I’ve discussed how I use Tailscale before, but not really covered app connectors. I find Tailscale’s description of these pretty confusing, but they basically amount to automatic, DNS-based subnet routing configurations (or, to put it another way, a per-website exit node). You can safely ignore all references to ‘SaaS apps’ in their docs.

I create a custom app connector, and give it the domains to be included:

App configuration in the Tailscale admin console

Tailscale then magically resolves those domains, and has the ‘connector’ advertise routes for them. Any client that accepts routes will start sending requests to the connector, which passes them onto the Internet at large. Any other traffic is left alone, unlike when you use an exit node.

The special bit here is how you can specify wildcard domains. Tailscale proxies the DNS requests from clients (so it can inject responses for nodes on your tailnet), which means it can dynamically update the routes as you resolve new domains. I tried to set this up more manually, and quickly came unstuck: despite using the same DNS servers, my server and my desktop would get different responses for the same query as it varied by geography. Trying to get the full set of IPs (and keeping them updated) would have been a nightmare. Tailscale expanding the wildcards nicely sidesteps all of that.

At first I was just proxying the traffic to one of my servers, but just today I added a new connector for Imgur and found I was still blocked, just for different reasons. They not only block my entire country but also a load of known datacenter IP ranges. Hmph. I fixed this by hacking up a new side project: tsv. It’s a simple Go app that accepts traffic from the tailnet (advertising itself as both an app connector and an exit node), and passes it on to another VPN.

There are lots of other ways you could accomplish this, but this makes it so all my devices can still access services without any additional configuration. As long as Tailscale is installed, the Internet will still work as it’s meant to, without all the nonsense. If I come across a site that doesn’t work, adding it is trivial: I just make a new app connector in Tailscale.

Obvious disclaimer: the laws in the UK are binding on the service providers, not the end user. Doing this sort of thing in other countries might be illegal. I don’t know; do your own research! Also all of this is a workaround for something that should be fixed at a legislative level, but I’m not holding my breath.

How I use Tailscale

2025-06-25T00:00:00Z

The Tailscale logo

I’ve been using Tailscale for around four years to connect my disparate devices, servers and apps together. I wanted to talk a bit about how I use it, some cool features you might not know about, and some stumbling blocks I encountered.

I’m not sure Tailscale needs an introduction for the likely audience of this blog, but I’ll give one anyway. Tailscale is basically a WireGuard¹ orchestration service, with lots of nice features sprinkled on top. It’s a subscription product, but it has an insanely generous free tier that covers basically anything you’d ever want to do as an individual. They also open source all their client software, and there’s a third party control server implementation called Headscale if you want to avoid the hosted system entirely.

Basic connectivity

At its core, Tailscale lets you easily connect from one device to another, even if they’re not directly exposed to the Internet. You install the Tailscale client wherever you like (on your phone, computer, servers, Raspberry Pi, etc), authenticate the machine with the control server, and it can then talk to all the other machines on the tailnet using their private Tailscale IP addresses.

That isn’t anything revolutionary: it’s the basic premise behind VPNs. But Tailscale makes it so easy. You don’t have to bother with any networking configuration. You don’t have to distribute keys. You just install the client², and login.

For example, my home automation service runs on a Raspberry Pi that sits behind two different routers. I installed Tailscale on it³, logged in, and immediately I could SSH into it from my computer or my phone even when they’re on different networks.

Speaking of SSH, Tailscale has special support for it whereby it handles any incoming connection to port 22 from the Tailscale network, and deals with authentication itself. No public keys or passwords: if you’re logged into Tailscale you can be logged into the machine. This is particularly handy when you SSH from a phone, as proper credential management is a bit of a nightmare there.

Exposing entire machines is just the start, though. If you run multiple services on the machine you need to remember which port they’re all on. Yuck. Instead, you can expose individual services as their own node on a tailnet. There are lots of options for doing so: there’s an official Docker image, a Go library, and many third-party tools (such as my own Centauri and tsp).

Not just a VPN

Exposing individual services wouldn’t be much use if you still had to remember their IP addresses. For a long time I manually added DNS entries for Tailscale nodes, allowing me to connect to http://grafana/ instead of http://100.73.190.100. Recently I switched to Tailscale’s MagicDNS, though, which takes care of that for you. Every machine on the tailnet gets an automatic DNS entry based on its name.

I initially shied off of this because it changes the DNS resolver on every machine it’s installed on, and it all seemed a bit too “magic” for me⁴. I got fed up with manually adding DNS entries though, so I spent a bit of time learning about it and got over my knee-jerk “what on earth is going on?!” reaction. The DNS controls also let you force a specific upstream DNS server. I use NextDNS everywhere, so having Tailscale automatically configure this for me on all my devices was a bonus⁵.

As well as the short names, you can resolve nodes on the tailnet using a slightly longer form: machine.your-tailnet.ts.net. The “your-tailnet” bit is randomly generated, and you can reroll it in the control panel to find a fun one. But why waste time say lot word, when few word do trick? Because Tailscale can make these addresses globally routable, and issue TLS certs for them too.

Say you’re developing something on your local machine, and want to get feedback from someone. You can use Tailscale’s “funnel” feature to expose it publicly:

tailscale funnel 127.0.0.1:8080

With no other options, this will expose the service over HTTPS on port 443. You can then invite people to visit https://machine.your-tailnet.ts.net and they’ll connect through to port 8080 on your machine. They don’t even need Tailscale installed. I don’t use this terribly often, but it’s a great quality-of-life improvement on the occasions I do want to share something.

Tailscale also has a “serve” command, which does much the same but only exposes it over your tailnet. This is how you’d use the Tailscale Docker image to expose a normal service onto your tailnet, but it’s also useful for similar development scenarios. Occasionally I’ll want to test something on my phone, and rather than make sure it’s connected to the right Wi-Fi network, recompiling the app to not bind to localhost, figuring out my machine’s IP, and so on, and so forth, I just run tailscale serve and access it over Tailscale.

Authentication, two ways

One of my minor frustrations with Tailscale was how cumbersome the authentication process was. I logged in using GitHub, and every time I tried to login to Tailscale, I had to bounce through the GitHub OAuth flow and then select which organisation I wanted to use. Even if I was logged in to GitHub, it still shows the permission page every time. It’s not a dealbreaker, but it’s definitely not smooth. This is what it looks like:

Logging in to Tailscale with a GitHub account

Tailscale have since added the ability to sign in with a custom OIDC provider, so I set up a KeyCloak instance, and my login flow now looks like this:

Logging in to Tailscale with KeyCloak as an OIDC provider

It’s a significantly shorter flow, and because KeyCloak is entirely under my control I can configure how long I stay logged in for. It also reduces my reliance on third parties: if GitHub goes down, or decides to ban my account⁶ or something, I can still access Tailscale.

That’s how you log in to Tailscale, but Tailscale can also assist with logging in to other services. If you connect to a HTTP service over Tailscale, it will add in the following headers:

Tailscale-User-Login: alice@example.com
Tailscale-User-Name: Alice Smith
Tailscale-User-Profile-Pic: https://example.com/photo.jpg

A lot of software has support for accepting login credentials provided by a reverse proxy, which is basically what’s happening here. For example, I run a Grafana instance that’s only exposed over Tailscale. Its config (set in environment variables) is:

GF_USERS_AUTO_ASSIGN_ORG: "true"
GF_USERS_AUTO_ASSIGN_ORG_ROLE: "Admin"
GF_AUTH_PROXY_ENABLED: "true"
GF_AUTH_PROXY_HEADER_NAME: "Tailscale-User-Login"
GF_AUTH_PROXY_HEADER_PROPERTY: "email"
GF_AUTH_PROXY_AUTO_SIGN_UP: "true"

So anyone who presents a Tailscale-User-Login header gets an admin account created with that as their e-mail address. It’s super convenient, but obviously make sure it’s only exposed via Tailscale if you do that!

Other services I run that support this include Miniflux (an RSS reader), Jelu (a book tracker), Linkding (a bookmark manager), and Seafile (a file storage system). If you’re hosting something yourself, look out for “proxy auth” or “remote users” in the documentation or configuration. It’s amazingly convenient to be able to access things without entering credentials.

ACLs, tags and mistakes

For a long time I didn’t bother with any kind of ACLs within my Tailscale network. Every machine could access every other machine. Then one day a thought hit me. The default Tailscale SSH config re-prompts you for user authentication, but I’d disabled that by tweaking the config… That means anyone with access to any of my machines (or who managed to get Tailscale credentials out of one of my apps) would be able to SSH into anywhere else on my network. Even as root! Compromising a small bit of my network would immediately lead to a complete take-over. What’s the point in defence-in-depth if you roll out a red carpet over the drawbridge for any attackers?

The first and most obvious fix for this was to restrict root access over SSH. I changed my Tailscale ACL to prompt for reauthentication for root access, but still allow regular SSH unprompted:

{
  "ssh": [
    {
      "action": "accept",
      "src":    ["autogroup:member"],
      "dst":    ["autogroup:self"],
      "users":  ["autogroup:nonroot"],
    },
    {
      "action": "check",
      "src":    ["autogroup:member"],
      "dst":    ["autogroup:self"],
      "users":  ["root"],
    },
  ],
}

This still didn’t sit right with me, though. Why should a random webserver be able to (theoretically) SSH into my desktop computer unchallenged? Tailscale allows you to do more advanced ACLs by applying tags to devices. I dutifully created a bunch of tags, and went through and tagged every device: user, server, app, container, and so on. This, it turns out, was a mistake. I could no longer SSH to anywhere. If I’d read the docs properly, I might have noticed how they describe tags:

Tailscale tags are how you authenticate and identify non-user devices, such as servers and ephemeral nodes. They serve two primary purposes: to provide an identity to non-user devices and to let you manage access control policies based on purpose.

By applying a nice user tag to all of my devices (computer, phone, tablet and so on), I’d effectively removed my own identity from them. They no longer counted for the autogroup:member source in the SSH config. Whoops. And it’s not easy to fix either:

You cannot remove all tags from a device. A device with a tag-based identity must have at least one tag.

So I’d have to remove all the affected devices, then re-add them. At the time I wanted to roll back all the tags, which would mean reconnecting dozens of nodes to the Tailnet. I did end up doing that, but I also took it as an opportunity to switch to KeyCloak as I mentioned earlier. Setting everything up again was a bit less painful when it wasn’t just correcting a dumb mistake.

I now have a much more sensible tag setup: servers are tagged server, apps are tagged app, and a few special apps are tagged integration. I then use Tailscale’s grants to limit access within the tailnet:

{
  "grants": [
    {
      // Users can access everything
      "src": ["autogroup:member"],
      "dst": ["*"],
      "ip":  ["*"],
    },
    {
      // Servers and integrations can access integrations and apps
      "src": ["tag:server", "tag:integration"],
      "dst": ["tag:integration", "tag:app"],
      "ip":  ["*"],
    },
  ],
}

This stops anyone but a user device from accessing servers, and stops plain apps from accessing anything at all. So for example my Grafana instance is tagged as an app; it doesn’t connect out over Tailscale for anything, it only exposes its interface over Tailscale. My home automation software is tagged as an integration, as it reaches out to other services over Tailscale (e.g., to push metrics it receives from devices).

You could go even further and limit which specific machines talk to which others, but I think this tier system sets reasonable boundaries for my use without getting too much in the way.

Even more

There are lots of other cool features offered by Tailscale that I’ve not covered: exit nodes (allowing you to route normal Internet traffic over Tailscale; very handy when you’re behind a router you don’t trust, or if you want to appear as being in another country for totally legitimate reasons); Tailscale lock (a system where existing nodes have to verify any new ones, guarding against both unauthorised access and Tailscale themselves inserting nodes into your network); file sharing, and more I’ve probably forgotten.

As I mentioned before, an awful lot is available on the free personal plan. It’s definitely worth checking out if you manage servers, or self-host anything. I can’t imagine going back to managing servers and private apps without Tailscale, and I’m excited to see what else they do going forward.

If you’re not familiar with it, WireGuard is a modern VPN included in the Linux kernel. It’s basically the only VPN that isn’t terrible. ↩︎
They have installation instructions and packaged versions of the client for just about every device you can imagine: Windows, Mac, every major Linux distribution, iOS, Android, etc, etc ↩︎
They even have an apt repository specifically for raspbian builds, so it’s super easy. ↩︎
Lots of people seem to treat “magic” as a good thing in software. I think it’s the absolutely opposite. I want to know how something works, not for it to be inscrutable! ↩︎
This is entirely optional, of course, you can just let each device do their own thing as well. ↩︎
I don’t think this is likely, but it’s one of my biggest concerns about using “social” logins. More-or-less all of these services can arbitrarily ban you with no recourse; why would you trust them as keyholders to other things? ↩︎

An introduction to containers

2020-03-01T00:00:00Z

So. Many. Containers.

I’m a huge fan of (software) containers. Most people I know fall in to one of two camps: either they also use, and are fans of, containers, or they haven’t yet really figured them out and view them as some kind of voodoo that they don’t really want or need.

I’m writing this short guide to explain a little how containers work - and how running something in a container isn’t really that much different to running it normally - to hopefully enable more people in that second group to give them a try. It’s aimed at people who have a fairly good grasp of how Linux works.

Containers are often mentioned in the same breath as VMs, which is not a helpful comparison or analogy. Think of containers as standard units of software, much like how Intermodal containers are standard units of freight transport across the world. When a company internationally ships goods in volume there isn’t a question about how they’re packaged - they go in an intermodal container. The same container can be deployed on a freight train, a lorry, or a ship. The haulage company doesn’t need to care what’s in the container because they’re completely standardised. Likewise, with software containers you don’t really need to care about what’s inside: the software you’re deploying could be written in Go, Python2, Python3, Bash, PHP, LOLCODE, or anything¹.

What does a running container look like?

When you run a container, you’re just running a process. In a lot of ways it’s not very different to what happens if you were to start the same process on the host computer.

For example I have a container that just runs cat(1). With no arguments, cat will read from stdin until it receives an EOF, so it’s handy to test with. If I run ps a on my computer, I can see the cat process in amongst everything else I’m currently running:

    PID TTY      STAT   TIME COMMAND
   7199 pts/1    Ss     0:01 /usr/bin/zsh
 323806 pts/0    Ss+    0:00 /bin/cat
 324120 pts/4    R+     0:00 ps a

The /bin/cat process is in a container, and the ps a underneath it is just running like normal on my desktop. They look very similar, right? If I look under /proc/323806 I can see all the usual attributes, the same as any other process running.

If I run ps in a container, though, it’s a different story:

    PID TTY      STAT   TIME COMMAND
      1 pts/0    Rs+    0:00 ps a

So inside the container it looks like there’s only one process running. It can’t see anything running “outside” on my desktop. The secret here is that this isn’t a special container trick: this is just a feature of the Linux kernel called namespacing.

If we go back to procfs and look at the ns/pid node we can see the process in the container is in a separate PID (process ID) namespace to the one on my desktop:

# readlink /proc/323806/ns/pid  
pid:[4026534564]
# readlink /proc/7199/ns/pid
pid:[4026531836]

Almost all² processes running ’normally’ on my desktop have the same PID namespace, whereas each container gets their own by default. PID namespaces are hierarchical: a new process is assigned a PID in its own namespace, and the parent namespace, and the grandparent namespace, and so on. That’s why I can see the process running in the container from my normal shell - the container’s namespace is a child of the main namespace all of my desktop software is running in.

Linux supports - and container software makes use of - a bunch of other namespaces too: mount points, network, UTS³, cgroups, and more. These all play a part in isolating a container from the system it is running on.

You can manually run a process with unshare(1) to “unshare” some namespaces from the parent process. For example if I run unshare -fp --mount-proc ps a, it looks very similar to running ps instead the container:

    PID TTY      STAT   TIME COMMAND
      1 pts/4    R+     0:00 ps a

So: a process running inside a container is just a heavily namespaced process running otherwise normally in the operating system. No voodoo magic here!

What about the filesystem? What are ‘images’?

Containers run in their own mount namespace meaning mount points can be different inside the container to those on the host. This means the container can have a different / mounted to the host, effectively giving it its own filesystem.

The root filesystem of the container is defined in the container’s image. If I use Docker to run a container using the Ubuntu image (docker run ubuntu), the root filesystem inside that container will resemble a minimal ubuntu install. Note that this is just the filesystem: the container doesn’t have its own kernel.

You might be thinking that sounds pretty inefficient. Downloading Ubuntu is definitely not instant, and doing it for every application you run would be insane! Quite. Containers solve this by using filesystem layers. These are stacked on top of one another to create the final filesystem. Each layer can be retrieved and cached independently of all others.

Say (for simplicity) that the Ubuntu image is a single layer. If I run one container with that image, then the layer will be downloaded and cached once. If I run three hundred containers with that image then the layer will be downloaded and cached once. Even better, if I use another image that’s based on Ubuntu but adds some software on top, only the “on top” layer will be downloaded if I already have the relevant “Ubuntu” layer cached.

If all the layers are cached, what happens when you change a file? This is dealt with using the copy-on-write technique: when you modify a file it is copied from the source layer and the changes are only made in a new layer. This is handled by the OverlayFS filesystem which is part of the mainline kernel.

When a container is running, changes made to its filesystem are temporary, and do not persist across container restarts. To persist data - or introduce new data to a container - you can mount volumes. How this works varies depending on how you’re running your container, but at the basic level it is pretty much the same as bind-mounting (mount -o bind).

You may be familiar with using chroots to change the apparent root directory of processes, perhaps with full-blown “jails” built on top. Containers offer much better isolation thanks to the use of namespaces. Instead of being constrained to a portion of the host’s filesystem, they don’t even have it mounted! Containers also get to specify their environment - if they expect in certain places, for example - instead of the sysadmin having to manually set up the chroot. Finally, containers offer much more fine-grained control over what processes can do (if you want it), and allow much more advanced use-cases such as inter-container networking.

Images and filesystems employ a little magic to ensure that layers are reusable and cacheable, but again there’s nothing terribly special about them: a container has a filesystem that appears to it to work the same way as a filesystem on the host, and it’s using a standard filesystem shipped with the kernel.

How about networking?

Again, networking is namespaced, so a container has its own network stack, its own virtual network interface, its own IP address and so on. How that network interacts with your real network depends on how you’re running the container. Docker, for example, can add iptables rules to NAT traffic between containers' networks and the outside world.

Containers can generally be connected into networks, and can communicate amongst themselves without the traffic actually leaving the host machine. This allows you to, for example, run a SQL database and connect it to a web application without ever exposing the database to the outside world. Moreover, as well as being isolated from the outside world, it’s isolated from other containers in other networks. If one of your applications has a crazy bug or is compromised, this significantly limits the damage it can do.

You have to explicitly opt in to “publishing” ports from a container, which exposes them to the outside world (either directly, or via a load balancer or some other middle-man, depending on how you’re running the container). This means you can pick and chose how the outside world sees the app you’re deploying: if it’s a web service that listens on both port 443 and port 80, you can chose to only expose the encrypted port.

If you run some containers and create some networks, you can see the interfaces and bridges on the host:

$ ip l
...
6: br-2405a8cc0445: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc noqueue state UP mode DEFAULT group default 
    link/ether 02:42:3e:fa:23:62 brd ff:ff:ff:ff:ff:ff
8: veth8ed0735@if7: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc noqueue master br-2405a8cc0445 state UP mode DEFAULT group default 
    link/ether b2:c1:5d:55:26:9b brd ff:ff:ff:ff:ff:ff link-netnsid 2
10: veth541d84b@if9: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc noqueue master br-9d7bc4024c1a state UP mode DEFAULT group default 
    link/ether 86:aa:5f:ee:da:1a brd ff:ff:ff:ff:ff:ff link-netnsid 1

This shows a bridge and two virtual NICs, just the same as if you’d manually created them (albeit with seemingly random names). So: as before, nothing special here.

Docker? Compose? K8s? Floccinaucinihilipilification?

(OK, Floccinaucinihilipilification isn’t actually a container technology, as far as I’m aware.)

Docker is the most popular container engine - that is, the bit of software that actually runs containers. It’s responsible for setting up all those namespaces we found, downloading and caching image layers, and actually starting and stopping the processes. Docker runs as a system-wide daemon - when you run a command like docker run ubuntu it actually just instructs the daemon to do the work.

There are several alternatives to Docker for running containers; one interesting one is Podman which runs containers without a daemon. Container engines have all standardised around the same image format looked after by the Open Container Initiative, so an image you build in Docker can be used in Podman, or pretty much any other engine.

Docker compose is a tool for defining and running multiple-container applications. I mentioned earlier running a database alongside a webapp - in practice to do this you’re going to have to configure a network for them, configure a mount point for the database to persist its data on, pass credentials in to both the database and the application, and so on. Doing all that by hand is tedious and error prone.

Docker compose lets you write “compose files”, which are simple yaml descriptions of the containers you wish to run, their properties, and details about any volumes or networks you may want. Out of the box, docker-compose will create a default network for each compose file you run so the containers within it can communicate.

Kubernetes is a container orchestrator, designed to automate deployment and management of large numbers of containers. It works with Docker under the hood, but provides a huge amount of tooling on top to allow you to deploy applications and manage their dependencies. It runs across multiple physical (or virtual) machines (while still allowing containers to communicate privately), and can support massive workloads by scaling out services (running multiple copies of a container on different hosts) and load balancing. Kubernetes is sometimes shorted to k8s (as in K - 8 elided letters - s) because computer people don’t like long words.

OK, they make sense now. But why bother?

Hopefully if you’ve read this far you’ve already picked up on some of the potential benefits, but this is my personal list:

Isolation. If I run some software in a container, there is very little it can do to upset me. It’s not going to leave bits of itself all over my filesystem, it can’t steal all of the secrets in my home directory, I can even limit its CPU and memory resources if I want. If I decide to stop running it, I just delete the container and it is completely gone: no trace remains.

Ease of use. If you give me a container image I have a very good idea of how to run it already. I might need to do some minor configuration to expose ports or mount volumes, but there’s no question about how to run it, how to make it automatically start, and there’s no “installation” procedure. If I want to then swap it with an alternative (say, move from MySQL to MariaDB), it’s potentially just a case of changing the name of the image I pull.

Dependencies included. Containers just run. Python 2 software includes Python 2 and just work. Python 3 software includes Python 3 and just work. I don’t have a massive headache trying to run both at the same time, because they take care of their own messes. Similarly I’m not going to have to install npm or cargo or composer to pull in dependencies for an application: that’s going to have been done in the build process.

Reproducibility. As a fallout from having dependencies included and being isolated from everything else, containers give you amazing reproducibility. If it “works on your machine” in a container, it’ll almost certainly work in production because it’s the exact same environment.

Standardisation. At the start of this article I called containers standard units of software. One of my favourite advantages of containers is that you basically get an API to list all the software you’re running. Most container engines let you supply labels attached to containers as well, so you can add your own annotations. I use this to annotate services which expose HTTP endpoints, and I have a tool that automatically generates SSL certificates for them and configures haproxy to route traffic to them. I can’t imagine how I’d do this without containers - I imagine it’d involve a lot of manual work.

Hopefully this has helped demystify containers a little. If you feel like I’ve missed something important out, or I’ve left you more confused than when you started, feel free to drop me a note using the feedback form below.

OK, maybe you should care if you’re deploying something written in crazy languages like PHP. ↩︎
Some multi-process apps, such as web browsers, are starting to use namespaces to enhance security, as do certain package systems like Flatpak ↩︎
“Unix timesharing system”; in practice this means having a separate hostname ↩︎