Chameth.com - posts like docker-automatic-nginx-proxy, g15-ram-upgrade, why-you-should-be-using-https but not docker-proxying-redux, finding-an-awkward-bug-with-claude-code

Upgrading the RAM in a Dell G15 laptop

2023-07-29T00:00:00Z

The Dell G15

I currently use a Dell G15 laptop for work. It has served me well for a little over a year, but recently it has been struggling a little with my day-to-day workload. It came with 32GB of RAM — the highest possible specification at the time¹ — but that is apparently no longer enough for me.

For a recent project, I was working on a Rust library used in an Android app. That meant running the usual glut of Android tools (Android Studio, an emulator and at least one Gradle daemon) alongside a normal IDE (IntelliJ IDEA). Throw in a web browser and a couple of electron apps, and I often managed to use all 32GB.

When you start swapping memory out to an encrypted disk — even an SSD — it doesn’t make for great performance. At first, I tried to work around this by enabling the Linux out-of-memory (OOM) killer, but it turns out that it’s not too good with Electron apps: it will kill the large browser process, but then the small Electron wrapper will just respawn it.

Can it be upgraded or not?

The obvious solution to not having enough RAM is to add more RAM. A quick look in the manual showed this might not be possible, though. The manual includes the following “Memory specifications” table:

Description	Values
Memory slots	Two SODIMM slots
Memory type	DDR5
Memory speed	4800
Maximum memory configuration	32GB
Minimum memory configuration	8GB
Memory size per slot	8GB or 16GB
Memory configurations supported	8 GB, 1 x 8 GB, DDR5, 4800 MHz 16 GB, 1 x 16 GB, DDR5, 4800 MHz 16 GB, 2 x 8 GB, DDR5, 4800 MHz, dual-channel 32 GB, 2 x 16 GB, DDR5, 4800 MHz, dual-channel

That unambiguously says that an upgrade from 32GB is not possible. I gave up.

Later though, I was complaining about memory issues to a friend, and he pointed out a Dell forum thread where a couple of people claim to have successfully installed dual-channel 32GB modules. Since the alternative was getting an entire new PC after only a year, I decided to give it a go.

The upgrade attempt

I ordered a pair of Crucial 32GB DDR5-4800 SODIMMs, and after they turned up dismantled the laptop. The G15 comes apart pretty normally: there are uncovered screws on the bottom holding the lower part of the case on. With those removed and some gentle prying, it pops off, and you get access to the battery, GPU and motherboard.

The first thing I saw was this:

The G15 motherboard adamantly proclaiming that it doesn’t want 32GB SODIMMs

Not one but two labels that indicate it will only accept 8GB or 16GB modules. Oh well, what’s the worst that can happen?

Oops?

I dutifully installed the new modules, reconnected the battery and put the case back together. I pressed the power button, and… nothing. None of the usual garish lights that immediately come on, no screen output, just a dead laptop. After reading some more of the user manual, I found that there is a tiny status LED on the side next to the ethernet port. Forcing the laptop to power off and back on again, the status LED blinked a distress code at me: 2 amber blinks, 4 white blinks. The manual says that is — unsurprisingly — a memory fault.

I figured at this point that the manual and labels on the motherboard were probably right. I took the laptop apart again, reinstalled the original 2x16GB modules, reassembled it, and pressed the power button. It didn’t boot. I don’t spend a lot of time fiddling inside computers, but I’ve done it enough that I’m reasonably confident I can’t entirely break a computer while swapping some RAM modules. I took to Googling², and found an interesting article that said Dell laptops don’t like to boot after RAM changes unless you clear the CMOS by popping out the battery for 15 minutes.

I opened the laptop up, and looked around for the CMOS battery. There wasn’t one. Turns out they don’t exist any more. I left the main battery disconnected for a while to see if it would help, and it didn’t.

Unexpected success

I started to get worried: if I couldn’t fix this, I wouldn’t be able to work until I got a new PC, and that wasn’t really in my budget at the minute. I sat reading old forum threads and help guides³, none of which were actually useful. Out of nowhere, though, the laptop booted up.

Naturally, I immediately shut the laptop down again, opened it up, and switched back to the new RAM modules. Then I turned it on again and sat waiting. After about 15 minutes of it looking totally dead, it turned on and showed a BIOS warning about the hardware configuration being changed. It then booted perfectly normally, and all 64GB of RAM was visible and usable.

My theory is that the forum threads were right: Dell laptops are funny about RAM upgrades. But somehow in removing the physical CMOS battery, they’ve kept the same “you have to wait 15 minutes” behaviour just without any indication that’s what’s happening. Regardless, I now have enough RAM even for the greediest of IDEs and Electron apps.

Bizarrely, the maximum spec has decreased to 16GB since then. ↩︎
In the generic sense. I use Kagi these days. ↩︎
On my phone because, y’know, the laptop was busted. ↩︎

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 ↩︎

Why you should be using HTTPS

2016-06-17T00:00:00Z

The EFF’s HTTPS Everywhere logo

One of my favourite hobbyhorses recently has been the use of HTTPS, or lack thereof. HTTPS is the thing that makes the little padlock appear in your browser, and has existed for over 20 years. In the past, that little padlock was the exclusive preserve of banks and other ‘high security’ establishments; over time its use has gradually expanded to most (but not all) websites that handle user information, and the time is now right for it to become ubiquitous.

Why use HTTPS?

There are numerous advantages to using HTTPS, both for the users of a website and for the operator:

Privacy

The most obvious advantage is that HTTPS gives your users additional privacy. An insecure (HTTP) request can potentially be read by anyone on the same network, or the network operators, or anyone who happens to operate a network along the path between the user and the server.

Users on shared WiFi networks (such as those in coffee shops, hotels, or offices) are particularly vulnerable to passive sniffing by anyone else on that network. If the network is open (as is frequently the case) then anyone in radio range can see exactly what the user is up to.

Integrity

HTTPS also helps to maintain the integrity of your site. With a plain HTTP request, there’s nothing to stop anyone in between the server and the user from modifying the content of the request or the response. This is a frequent tactic used by annoying WiFi gateways (such as the ones you’d find in a hotel), dubious ISPs who want to serve you extra adverts, or just plain old nefarious attackers.

If you’re trying to convey some kind of information to users (and if you aren’t, why exactly are you running a website again?) it seems beneficial to both you and them if the information arrives as you intended, rather than in a modified form due to someone or something tampering with it.

Security

If your website has any kind of authentication, or session identifiers, it becomes extremely vulnerable to an attacker monitoring the traffic and stealing the credentials. This was starkly demonstrated in 2010 when Firesheep was released. This tool allowed anyone to quickly and automatically hijack social media accounts of anyone on the same network who was using HTTP to access them.

Even if your login pages are served over HTTPS, if you send a single session ID cookie over HTTP (such as a page you decided wasn’t particularly ‘important’) then an attacker can probably spoof the user’s session and gain full access to their account. Again, in the case of open WiFi networks that could be anyone in radio range.

Search engine rankings

Some search engines use HTTPS as a signal in their ranking algorithms. Google announced in 2004 that it was using the presence of HTTPS as a small positive signal, but that it may strengthen that signal over time as more and more websites switch to using a secure transport. It’s not unthinkable that at some point in the future there will be HTTPS-only search engines.

But… But… But…

There are lots of excuses for not implementing HTTPS. Most of them are either misguided or outdated.

It’s too expensive and/or complicated

In the past, getting HTTPS certificates was a pain. A number of free suppliers have existed for a while but the process for getting their certificates wasn’t particularly straight forward, and many imposed arbitrary restrictions on the certificate parameters. Even once you had the certificate, you had to fiddle about with your HTTP server configuration to make it work, remember to manually get a new certificate when the old one expired, and lots of other annoying busywork.

With the arrival of Let’s Encrypt, all that changed. You can retrieve and deploy a free HTTPS certificate with two or three commands. Renewal can be handled completely automatically with a single command executed by cron.

There’s no point; nothing on my site is sensitive

You might not think your content warrants privacy, but can you speak for everyone who accesses it? Even content that seems mundane to you — such as travel advice, or technical writing — could be used to build up a profile of a user. If an attacker is monitoring traffic in a coffee shop and sees a user looking at travel advice and weather forecasts for a foreign country, he could use that information to plan a burglary knowing that the user will be away. Similarly, some content which is perfectly mundane to you may actually be very sensitive in other countries with repressive governments. HTTPS makes it much harder for these people to snoop on traffic.

From another angle, if you’re offering any kind of information, instructions, or especially file downloads, there’s a severe risk to users if the content is modified on its way to them. An evil sysadmin could rewrite your travel advice to suggest visiting the local drug dealer’s hangout, or replace your download with a malware-infested version.

HTTPS is slower, uses more resources, etc

Back in 1995 this might have been a valid argument. Enabling HTTPS on a modern server will make an almost negligible difference to performance. If you also enable HTTP/2 (which most implementations only support over HTTPS), it’s likely to actually use fewer resources, and result in a faster, smoother experience for your users. HTTP/2 was designed to work with HTTPS, and designed with modern requirements and networking techniques in mind.

CloudFlare have an excellent demonstration of the benefits of HTTP/2, and it can show speed improvements of 2-3x in a typical environment. On top of being faster, HTTP/2 uses fewer connections which results in less resource overhead on both the server and the client.

So what are you waiting for?

If you run a website and aren’t using HTTPS, give it a try.

Automatic reverse proxying with Docker and nginx

2016-05-21T00:00:00Z

The Docker project logo

Over the past few weeks I’ve gradually been migrating services from running in LXC containers to Docker containers. It takes a while to get into the right mindset for Docker - thinking of containers as basically immutable - especially when you’re coming from a background of running things without containers, or in “full” VM-like containers. Once you’ve got your head around that, though, it opens up a lot of opportunities: Docker doesn’t just provide a container platform, it turns software into discrete units with a defined interface.

With all of your software suddenly having a common interface, it becomes trivial to automate a lot of things that would be tedious or complicated otherwise. You don’t need to manage port forwards because the containers just declare their ports, for example. You can also apply labels to the application containers, and then query the labels through Docker’s API.

Reverse proxying and SSL termination with Nginx and Let’s Encrypt

A fairly significant chunk of the software I run has a web interface. I don’t really want to expose and remember dozens of non-standard ports, so I configure an nginx instance as a reverse proxy. I’m of the opinion that all web traffic should be encrypted, so I also have to provide nginx with trusted certificates to use for each site it reverse proxies. Let’s Encrypt makes the process of obtaining free, trusted certificates approximately a thousand times easier than it was previously, but my workflow still ends up looking like this:

Create a new config file from a template and save it in /etc/nginx/sites-available
Temporarily disable SSL for the site as there’s no valid certificate yet
Enable the site by symlinking to it from /etc/nginx/sites-enabled
Reload nginx
Run the Let’s Encrypt client to obtain certificates
Enable SSL and for the site
Reload nginx

… And that’s not including the extra steps when I miss a semi-colon, accidentally skip a step and have to spend time figuring out why it’s not working, or any of the other human-induced problems that creep in.

I’d been toying with making a script to run through these steps manually for me, if I gave it a domain name and a reverse proxy target, but I never got around to it. Now I’m moving things to Docker, though, there’s an opportunity to automate the entire thing with no human interaction at all.

Existing solutions

It seemed like this probably wasn’t a unique idea, so I had a look around for existing solutions. The most popular by far seems to be nginx-proxy by Jason Wilder. This is based on his docker-gen project that takes a template and populates values from docker containers.

It’s a good solution, but there were a few bits I didn’t like. Firstly, templates don’t really lend themselves well to every step of the process: to request Let’s Encrypt certificates, the container uses a template to create a shell script which it then sources. Each container that generates a template also needs access to the Docker socket. Both of those cause an itch in the back of my head and make me want to say phrases like “attack surface”. I don’t think there’s actually a problem, but it doesn’t really sit well with me.

Secondly, the whole system seems slightly too tightly coupled for my liking. The Let’s Encrypt component needs to modify the nginx config in order to obtain the certificate, while the main nginx component is also making different changes to add and remove sites. It feels like if it doesn’t just work, it’s going to be difficult to debug and pry apart the different components.

Another potential solution is Rancher. This is a complete platform for managing containers, and I’m fairly sure if configured right it can grab certificates from Let’s Encrypt and do SSL termination using haproxy. I tried it for a bit but the whole platform seemed a bit overkill for my purposes, and I didn’t want to invest the time I’d need to fully understand it all.

Rolling my own

In the end I decided to roll my own solution. Here’s a high-level overview of how it all works:

Diagram showing components of a reverse proxy implementation

As you probably noticed, there are quite a few containers involved. Each one performs a small, well-defined task, and its output can easily be inspected in either a volume or a database. I think there’s some similarity to piping commands together on a command line — it’s a lot easier to reason about simpler commands like head, cut and tr than it would be one giant command that combined them. And, if it does go wrong, you can inspect the pipe at each stage to see where the problem is happening.

service-reporter and etcd

The first part of the chain is my service-reporter container. This uses the Docker API to get a list of containers, and store information about them in etcd. Etcd is a distributed key-value store (similar in some ways to redis or memcached). The container also watches for containers that are added and removed, and keeps etcd updated appropriately.

As the service metadata is stored in a database, no other part of the system needs to interact with Docker. If the Docker API changes, or the host configuration changes, then only this container has to be updated.

service-letsencrypt and letsencrypt-lexicon

The left fork of the diagram deals with obtaining SSL certificates. To keep it separate from the nginx configuration, it uses DNS-based challenge to prove that we control the domains. It does this by plumbing together two great open source projects: letsencrypt.sh, a Let’s Encrypt client implemented in bash with support for the dns-01 challenge type, and Lexicon, a python library for updating DNS records using a variety of providers.

My service-letsencrypt container connects to etcd and pulls a list of containers that have a label with the key com.chameth.vhost. It uses this to build a plain text list of certificates we require (in a format understood by letsencrypt.sh), and then monitors etcd for changes and repeats as necessary.

The letsencrypt-lexicon container runs letsencrypt.sh, using Lexicon to perform the required DNS updates, and produces certificates. The nice thing about this is that it can be used in a completely standalone fashion (you can just write a domains.txt yourself). It uses iowait to watch the domains text file for updates, and automatically reruns when there are changes. It also runs once a day to renew any certs that are coming up for expiry.

service-nginx and nginx

The right fork of the diagram is concerned with nginx. My service-nginx container again connects to etcd and pulls a list of containers. It uses a couple of labels to determine the vhost, proxy port, and proxy protocol. It then feeds these values into a template to create a server block for each site, configured with SSL certificates and a reverse proxy setup. The template covers only the very minimal settings, with the expectation that everything else will be done in the global config (things such as SSL ciphers, redirection from HTTP, etc).

This container works completely independently of the Let’s Encrypt side. You can use the Let’s Encrypt containers and mount the certificate volume, or you could just provide your own certificates. It doesn’t really make any difference.

Putting it all together

The only downside to having many small containers is that it’s a bit of a nuisance to get them all set up. Fortunately, Docker has a solution for this in the form of Docker compose. This allows you to write a YAML file defining all of the services you want to run, and bring them up or down in one go. It can handle volumes, dependencies, networking, etc. I’ll be publishing a docker-compose.yml file to get this entire stack up and running soon.