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Thinking more about backups

2025-11-01T00:00:00Z

The Backblaze logo

Almost a year ago I wrote about how I do backups with Restic and Hetzner. That system has been ticking along well ever since, but recently I had some… thoughts. These backups are all well and good if I accidentally delete a file, or a database gets corrupted, or something, but there are two glaring issues:

Firstly, I’m backing up my Hetzner server to Hetzner cloud storage. If something happens to Hetzner — or my Hetzner account — then all my eggs go down with that basket. Obviously Hetzner are a big organisation and aren’t likely to just vanish overnight, but I’m less confident about my account. Could a false abuse report get it suspended? What if the UK passes even more dumb laws and Hetzner decide it’s easier just to not do business with people here? This is the same sort of concern I have about Google accounts: if you have half of your life in Google Drive and Google Mail, what happens if you comment on a YouTube video, get flagged by an AI moderation process, and your account gets suspended? It’s probably not very likely, but these are things my brain likes to dwell on.

Secondly, the credentials to access the backups sit on each machine that is backed up. If someone malicious gained access to the machine, they’d also have access to delete or tamper with all the backups. It feels a little silly that the same attack could take down both the originals and the backups. There’s no way to avoid that with Hetzner’s S3 implementation, as far as I can tell.

Exploring options

I toyed with the idea of making local copies of the backups, but the only way to avoid the same problems would be to keep them offline and do a manual copy every now and then. I didn’t really want to do that, and was concerned that if I did a monthly offline backup then I stood to lose up to a month of data in the worst case.

I then looked around at other S3 providers. Amazon’s glacier offering is tempting due to its very low storage costs, but you pay for that if you ever want to restore anything. There are also lots of weird pricing edge cases around moving data between storage classes, minimum file sizes, and so on. A much better option is Backblaze’s B2 product. Their pricing is much more straight-forward, and they have an interesting feature that’s particularly useful in this case: lifecycle rules. Coupled with the ability to create API keys that don’t have access to delete files (just “hide” them), this allows for what’s effectively an append-only store.

This works more-or-less out of the box with Restic. Joseph Price has a guide that goes into the setup in a bit more depth. Basically, whenever Restic would delete a file (e.g. during a “forget” or “prune” operation), it instead gets hidden and is only deleted when the B2 lifecycle rules decide it should be. I’ve kept the existing Hetzner S3 backups for now, and just added an extra step to the end of my script: a simple restic copy and a restic forget. B2 actually works out cheaper than the Hetzner storage, as they don’t bill you for a minimum of 1TB storage; my current usage is around $3/month. Not a bad price for some extra peace of mind!

Further Adventures in Music Organisation

2025-09-21T00:00:00Z

I wrote before about how I’d dropped Spotify in favour of locally stored music, but things have advanced a bit since. I had a few issues: Tauon would occasionally manage to lose its database and along with it all my carefully constructed playlists and song ratings¹, and the experience on my phone was not very fun.

I had to manually sync the music by plugging my phone in to the computer, and sometimes it just refused to mount the right partition. I don’t think there’s really a good way to debug an Apple phone not behaving properly when connected to a Linux desktop. Then I started wanting more than one playlist synced², and trying to find a way to make that work just broke me.

I spent a while looking at different ways of hosting the music centrally. Plexamp gets lots of good reviews, and I’ve used Plex a fair bit. I set about spinning up a Plex server, and just could not get it working. The server ran fine, served the web interface, but would neither associate with my account nor run standalone. The docs were contradictory and there was very little useful logging. After a lot of frustration, I stumbled across mentions that Plex block running on Hetzner. I assume that’s the cause of my issues, although I have no way to know for sure. I use Hetzner for all my servers and other hosted services, but Plex have decided I can’t run the self-hosted software that I have a lifetime subscription for there. What the actual fuck?

I could have probably worked around the arbitrary restriction, but I didn’t want to throw more time down the drain. Instead, I set up Navidrome, an open source music server. It supports the Subsonic protocol, which means you can use a whole slew of different clients with it (or even write your own). It also means there’s a nice way to get data in and out of it programmatically, which I recall being a bit of a fight with Plex.

Syncing and organising

All my music lived on my desktop, but now I wanted it on my server. At first I just used rsync to copy everything up. I’d maintain a local “master” copy, and periodically shove the changes to the server³. That quickly got old, so I set up Syncthing to keep the two folders in sync. That worked… for a while.

Concurrently, I was looking at improving the organisation of my music. It was mostly organised by some Go programs I’d thrown together to automate the importing, with no real validation of metadata or anything else. Some albums got split up into multiple folders because the tracks had different artists (and didn’t have an album artist set); some artists ended up with multiple folders with slight spelling or case variations. It was upsetting.

I’d used MusicBrainz Picard before to fix some issues, but I didn’t really like the UI, especially when trying to do bulk actions. The main alternative is beets, which describes itself as “the music geek’s media organiser”, and is entirely command line. I was intrigued.

I started playing around with beets, and quickly noticed a problem. Every time I changed a metadata tag in a music file, Syncthing had to upload the entire file. I was frequently changing tags across the whole library as I got beets set up how I wanted, and Syncthing was handling it by uploading gigabytes of files for every minor change. I was already a bit unhappy with having the content duplicated in two places, so now I was using a command line organiser I figured I could just get rid of my local copy and move everything to the server.

I set up a Docker container for beets, and then wrote some incredibly hacky shell scripts so I could run beet locally on my desktop and it would SSH to the server over Tailscale and exec into the container, passing the arguments along. Then I did one final sync of the music library, got rid of Syncthing, double checked I had a backup and deleted all of my local music.

Bears, Beets, Battlestar Galactica

Beets is amazing. It has a vast array of plugins that can do almost anything you could want with a music library, and the command line workflow works really well for me. It’s very well documented, and all the individual parts are pleasingly simple and easy to understand.

Here’s what it looks like when importing some new music:

Beets importing an album

If it doesn’t get a perfect match then it shows the closest matches, and summarises what’s different about them (missing tracks, different names, etc), and lets you decide what to do. Aside from the metadata matching, it’s doing a lot of things under the hood that aren’t necessarily apparent. It:

Looks up the genre from Last.fm
Analyses all the tracks and writes ReplayGain metadata to them
Fetches album art
Checks all the files to make sure they’re actually playable
Scrubs any existing metadata tags

It also maintains its own database, and you can query against it. The query language is both simple and quite powerful, like the rest of beets. As an example:

$ beet ls artist:"Linkin Park" year:2025 length:2:00..2:30 
Linkin Park - From Zero - Casualty

Almost all the other commands also let you use the query syntax, which makes the whole tool really powerful. Want to delete all country tracks that you added last month? No problem. Redownload all the album art for a certain band? Easy. You can even do smart playlists using the filters.

Actually playing music

With all this organisation, I’ve not actually mentioned one tiny detail: how I actually play music now. Navidrome has a web UI, which is perfectly usable, but I don’t really want my web browser involved as it makes balancing sound levels tricky, and getting media keys working is a pain. Thankfully there are loads of Subsonic clients. I’ve tried several, but eventually settled on Feishin on the desktop. It’s very pretty:

Feishin’s ’now playing’ screen

What attracted me to it, though, was its built-in support for Navidrome’s smart playlists. These aren’t even properly exposed in Navidrome’s web UI yet, but Feishin has a visual editor that lets you create and edit them. I ended up with an identical system to the playlists I had in Tauon: a “blacklist” playlist which are tracks I never want to play, a “favourites” playlist, and then an “everything” playlist which is the entire catalogue minus the blacklist.

On iOS I’ve settled on Arpeggi. It’s not actually on the App Store yet, but available via TestFlight. It’s one of those really nicely polished apps that are obviously a labour of love, not just out to do the minimum possible to get your money. It can cache songs offline, and automatically download entire playlists, and supports all of the standard Subsonic features like rating, reporting plays back to the server, and so on.

One unexpected benefit of using a central server is that it handles reporting plays to Last.fm and ListenBrainz instead of the clients. I don’t think I’ve ever bothered to configure my mobile clients to do that before, and now it just works automagically. I’m relying on those services more for recommendations and discovery, as that’s something you lose out on when self-hosting.

Making bad decisions about bitrates

With all the moving, copying, and organising, I started thinking about how large the collection was. The songs were all in different formats, depending on when and where I’d picked them up, and I couldn’t tell the difference between them. I did a test and transcoded an MP3 file down to 128kbps, and still couldn’t tell the difference. So armed with that sample size of 1, I transcoded the entire library and saved so much space.

I don’t remember which track I did that first test with, but it must have been a very unlucky pick. I quickly started to notice the distortions caused by the low bitrate. It was particularly bad in any song with a lot of treble, and started to really annoy me. I started a painful process of reimporting things in their original format. Beets came in clutch again, both with the import process (if you import a duplicate album, it asks if you want to replace the original, and shows the format and bitrate of them for comparison), and keeping track of what was left to fix (beet ls bitrate:..128000).

Having started paying more attention to the sound quality, I think I’ve been nibbled on by the audiophile bug. I’ve been trying to get new music in FLAC format where possible. I’m pretty sure I can’t tell the difference between a decent bitrate MP3 and a FLAC, but maybe if I got a better DAC and some nice headphones…? Someone please hide my credit card!

As for the library taking up a lot of space, I now realise it’s a price worth paying. I might need to swap out the server to one with more storage at some point in the future, but it’s generally worth upgrading every few years with rented dedicated servers anyway, as you often get more for the same amount of money. Next upgrade I’ll just make sure there’s an appropriately-sized disk instead of focusing entirely on RAM and CPU.

Writing more code

Naturally, this whole process spawned several side projects. When browsing albums in Navidrome, I was a bit upset that the album art wasn’t all a consistent size. I thought about scripting something to crop them consistently, but then I had a better idea, and jewelcase was born. It takes the album art, crops it down to a consistent size, and then renders it inside a jewel case. It applies some slight effects, like adjusting the colours, rounding the corners, and tweaking the edges so it looks a bit more real. I don’t know why⁴, but every time I see the effect it gives me a little spark of joy.

Album art, before and after jewelcase is applied

The other project is BASS, a tool that uses the Subsonic API to grab information about my music catalogue, and then generates a “Daily Mix” playlist. It uses a system of weights to select tracks semi-randomly, biasing towards favourite tracks, those that haven’t been played much, and a few other criteria. This gives me a nice balance between having my favourites on repeat, and exploring the full library at random.

All the weights in BASS are customisable, so I can tweak it to my heart’s desire, and anyone else can also run it and configure it entirely differently to me if they want to. I can’t imagine I would’ve been able to do that if I were using Plex!

I was running a version from git as the stable release had fun dependency issues on Arch, so it’s possible this wouldn’t be an issue in normal use. I also started backing up the database, but it’s still annoying to have to restore it. ↩︎
A “favourites” playlist for me, and a more “family friendly” playlist for when I’m playing music out loud that has a bit less screaming/swearing/etc. ↩︎
One of the reasons for starting this was being annoyed by the periodic sync to my phone, obviously it makes perfect sense to introduce a new, different periodic sync. ↩︎
Nostalgia? A little bit of OCD? Both? ↩︎

Simple backups with Restic and Hetzner Cloud

2024-12-06T00:00:00Z

Restic’s mascot, who’s dual-wielding umbrellas to save you from a rainy day.

I have a confession: for the past few years I’ve not been backing up any of my computers. Everyone knows that you should do backups, but actually getting around to doing it is another story.

Don’t get me wrong: most of my important things are “backed up” by virtue of being committed to remote git repositories, or attached to e-mails, or re-obtainable from the original source, and so on. I don’t think any machine failing completely would be a disaster for me, but it would certainly be a pain.

This week I finally got around to doing something, and it ended up being a lot more straight forward than my previous forays into backup-land.

Restic

After soliciting a few opinions, the choice of backup software came down to either Borg or Restic. I’m pretty sure either would have done what I want, but I leaned towards Restic for a few reasons: it has a more informative website, it’s written in Go rather than Python¹, and Borg seems to be transitioning between major releases at the moment².

The way Restic works is pretty simple: you initialise a ‘repository’, and can then call restic backup /some/path and it’ll get backed up to the repository. Restic handles keeping different backups separate, and only sending data that’s changed, and deduplicating, and so on. You basically point it at a thing you don’t want to lose, and it sorts it out for you. Perfect.

There are equally straight-forward commands for removing old snapshots (restic forget) and verifying backups (restic check). One of the nice things about modern backup solutions is they support a whole range of backends. I was originally going to spin up a small VPS to host my backups, but noticed that Restic supported S3-compatible stores…

Hetzner Cloud Object Storage

I host my servers with Hetzner, and was going to use them to spin up a VPS as well. Despite the “Cloud” branding on a bunch of products, they offer reasonable prices and good service. A couple of months ago, they started offering S3-compatible object storage.

The pricing isn’t totally straight forward, but for continuous use the “free quota” amounts to 1TB of storage and 1TB of egress a month. Ingress is free, as is traffic within the eu-central region (where all my servers are). That quota is only awarded when you pay the “base price”, though, which is €4.99 a month. So basically it’s €5 a month for 1TB of storage and enough egress to fully restore every single byte. That’s better value than any VPS I can find, much cheaper than Amazon S3, and about the same as Backblaze B2.

Getting them to work together

Now you’d think making the tool that supports S3-compatible object storage work with your S3-compatible object storage would be easy, right? Well not quite. The library Restic uses to deal with S3 backends has some strange logic for figuring out the bucket name given a URL. It doesn’t quite seem to work right, though…

Hetzner buckets have URLs like s3://bucketname.hel1.your-objectstorage.com³, but just passing that to Restic gives an error that the bucket is not specified. The docs mention there’s an advanced option to make it use the virtual host for the bucket name: -o s3.bucket-lookup=dns. But that… also doesn’t work. What I ended up doing was specifying the URL as s3://hel1.your-objectstorage.com/bucketname, and also passing in the dns option. The library then seems to muddle its way back to a real, working URL. I’m not sure why it works like this: maybe it’s just a weird aspect of S3 that I’m oblivious to?

The next fun part is that you can configure Restic entirely by using environment variables, except for that -o s3.bucket-lookup=dns argument. That has to go on the command line. I ended up making a little wrapper script to invoke Restic correctly:

#!/bin/sh

# The password restic will use to encrypt your data. You should generate
# something nice and secure.
export RESTIC_PASSWORD=repo-password

# The path to the repository where restic will save the backup. In our case
# this takes the form `s3:<endpoint>/<bucket>`. Your endpoint might be different
# to mine depending on the region your bucket is in.
export RESTIC_REPOSITORY=s3:hel1.your-objectstorage.com/bucket-name

# The access and secret key generated in the 'S3 credentials' section of the
# Hetzner Cloud Console
export AWS_ACCESS_KEY_ID=hetzner-access-key-id
export AWS_SECRET_ACCESS_KEY=hetzner-access-key

# Pass any arguments on to the restic command, along with the magic
# `s3.bucket-lookup` option we need to resolve the S3 URL properly.
exec restic -o s3.bucket-lookup=dns "$@"

Then in the backup script I just alias restic to use the script:

#!/bin/bash

set -eu

# This means any time we use `restic` below, we'll actually execute our special
# script which supplies all the env vars and arguments needed to find the
# repository. Make sure the path matches where you saved the script!
alias restic='~/.bin/restic'

# Actually do the backup. Each directory in the list below will be backed up
# separately.
dirs=(
	"/some/path/to/backup/"
	"/some/other/path/"
)
for i in "${dirs[@]}" 
do
	echo $i
	(cd $i && restic --verbose backup .)
done

# Prune our snapshots. You can tweak the numbers here. Run with `--dry-run` to
# see what effect any changes would have before actually committing to them. 
restic forget --keep-daily 7 --keep-weekly 10 --keep-monthly 24 --keep-yearly 10

The only other notable thing here is that the script changes into the directory to be backed up. If you give Restic an absolute path, it will create a new snapshot if the metadata of any folder in the path changes, which is not what I want.

If it wasn’t for the S3 URL issues, the whole thing would’ve probably taken me about half an hour. That’s including setting up the object storage, installing Restic, and so on. It’s painfully easy. Why didn’t I do this three years ago?!

Addendum: a step-by-step guide

If you want to do this yourself, here’s a quick step-by-step guide:

Log in to the Hetzner Cloud Console, and create a project.
On the “Object Storage” tab, create a new bucket. Note the name and the endpoint.
On the “Security” tab, go to “S3 Credentials” and generate new credentials. Note down the access key and the secret key.
Copy the first shell script above, fill in the password (you can pick!), endpoint, bucket name, access key and secret key.
Run the script with the init argument (e.g. ~/.bin/restic init). This will create a new repository, and only needs to be done once even if you backup multiple machines.
Copy the second shell script above, making sure the restic alias points at the script you saved in step 4. Change the list of directories to whatever you want to backup.
Schedule the script to be run automatically, using crontab or systemd timers or however you prefer.

To check everything is working, you can use the snapshots subcommand to see a list of saved snapshots. You might also want to try to restore a snapshot using the restore subcommand.

I’m not trying to be a language snob, but given the choice between two otherwise equal projects one in Go and one in Python, I’ll take the Go one. I know I’m not going to have weird library issues down the line, and I’m much more comfortable rummaging around the source. ↩︎
With a “Don’t use this in production!” notice on the shiny new version. ↩︎
Aside: I really hate URLs like that. What is with the trend for completely generic domains divorced from the service they’re a part of? ↩︎

Android testing with Espresso and Spoon

2017-05-16T00:00:00Z

I’ve been spending some time recently setting up automated testing for our collection of Android apps and libraries at work. We have a mixture of unit tests, integration tests, and UI tests for most projects, and getting them all to run reliably and automatically has posed some interesting challenges.

Running tests on multiple devices using Spoon

Spoon is a tool developed by Square that handles distributing instrumentation tests to multiple connected devices, aggregating the results, and making reports.

As part of our continuous integration we build both application and test APKs, and these are pushed to the build server as build artefacts. A separate build job then pulls these artefacts down to a Mac Mini we have in the office, and executes Spoon with a few arguments:

java -jar spoon-runner.jar \
    --apk application.apk \
    --test-apk applicationTests.apk \
    --fail-on-failure \
    --fail-if-no-device-connected

Spoon finds all devices, deploys both APKs on them, and then begins the instrumentation tests. We use two physical devices and an emulator to cover the form factors and API versions that are important to us; if any test fails on any of those devices, Spoon will return an error code and the build will fail.

For library projects, you only have a single APK containing both the tests and the library itself. The current version of Spoon requires both --apk and --test-apk to be specified, so we simply pass in the same APK to both. It looks like future versions of Spoon will be more flexible in this regard.

Spoon produces HTML reports, showing the status of each test run on each device. We have the report output folder collected as a build artefact, so the reports can be seen right from the build server:

Spoon output summary, showing results of 171 tests run on 3 devices

Flake-free UI testing with Espresso

Espresso is an Android library that provides an API for interacting with and making assertions about the UI of Android applications. Espresso has a very simple interface, and does lots of clever things under the hood to ensure that your tests only execute code when the UI is idle (and hence stable). You shouldn’t ever need to make your code sleep or wait.

In order for Espresso’s magic to work, it needs to know whenever some background activity is going on that it needs to wait for. By default, it hooks in to Android’s AsyncTask executor so it can wait for those to finish. In our apps, there were a few cases where we used an explicit Thread to do some background work, which caused tests to fail intermittently (depending on whether the thread performed its UI update before or after Espresso executed the test code). Rewriting these cases to use an AsyncTask enabled Espresso to figure out what was happening and the tests started passing reliably.

Another, similar, problem occurred where we were using RxJava to load some data. There are two possible ways to deal with this… Espresso has a concept of an idling resource, which provides a way of telling Espresso when a resource is busy so it can belay interacting with or testing the UI until the resource is finished. In our case, the code in question was going to be rewritten soon, so we went for a quicker and dirtier option: force RxJava to use the same executor as AsyncTask.

To do this, we added a simple test utility class that registers an RxJavaPlugin that overrides the Schedulers used by Rx:

/**
 * Hooks in to the RxJava plugins API to force Rx work to be scheduled on the
 * AsyncTask's thread pool executor. This is a quick and dirty hack to make
 * Espresso aware of when Rx is doing work (and wait for it).
 */
public final class RxSchedulerHook {

    private static final RxJavaSchedulersHook javaHook =
            new RxJavaTestSchedulerHook();

    private RxSchedulerHook() {
        // Should not be insantiated
    }

    public static void registerHooksForTesting() {
        if (RxJavaPlugins.getInstance().getSchedulersHook() != javaHook) {
            RxJavaPlugins.getInstance().reset();
            RxJavaPlugins.getInstance().registerSchedulersHook(javaHook);
        }
    }

    private static class RxJavaTestSchedulerHook extends RxJavaSchedulersHook {
        @Override
        public Scheduler getComputationScheduler() {
            return Schedulers.from(AsyncTask.THREAD_POOL_EXECUTOR);
        }

        @Override
        public Scheduler getIOScheduler() {
            return Schedulers.from(AsyncTask.THREAD_POOL_EXECUTOR);
        }

        @Override
        public Scheduler getNewThreadScheduler() {
            return Schedulers.from(AsyncTask.THREAD_POOL_EXECUTOR);
        }
    }
}

With the hook registered Rx does all of its work on the same thread pool as AsyncTask, which Espresso already knows about. It’s not the best long-term solution, but it means we don’t have to spend time integrating IdlingResource for code that doesn’t have long to live. With the hook in place, the tests that were flaking because of Rx started passing reliably as well.

Getting automatic screenshots of failures

Spoon provides a client library to, among other things, take a screenshot of the device. Espresso provides a hook that can be used to change how errors are handled. Putting the two together is very simple:

final FailureHandler defaultHandler =
        new DefaultFailureHandler(
                InstrumentationRegistry.getTargetContext());

Espresso.setFailureHandler(new FailureHandler() {
    @Override
    public void handle(Throwable throwable, Matcher<View> matcher) {
        try {
            Spoon.screenshot(
                    getActivity(),
                    "espresso-failure",
                    description.getClassName(),
                    description.getMethodName());
        } catch (Exception ex) {
            Log.e(TAG, "Error capturing screenshot", ex);
        }
        defaultHandler.handle(throwable, matcher);
    }
});

In our new error handler we simply ask Spoon to take a screenshot, then call Espresso’s original handler so that it can output its debugging information and fail the test. The Spoon runner automatically picks up the screenshot and adds it to the report:

Spoon output details, showing a screenshot captured of the failure

Having the screenshot, error message and logs all presented in a clean UI makes debugging failures much, much easier than searching through a huge build log to try and find the exception.

Filtering tests based on device capabilities

Some tests won’t work on every device you throw at them. We had two problems: some tests require a higher API version than some of our devices, and some of the UIs under test were designed to run only on certain resolutions.

The main cause for our dependence on newer API versions was the use of WireMock, a brilliant library for stubbing out web services. WireMock requires API 19, while our physical devices tend to run versions older than that. Stopping these tests running is simply a case of applying an annotation to the class:

@SdkSuppress(minSdkVersion=19)

Screen resolution is a bit more complicated. One of our apps is designed for a specific tablet device (and will never be used on anything else), and trying to render the UI on smaller screens results in items overlapping, important parts ending up below the fold, and other problems.

We’d still like all the other tests for that app to run on all of the devices, though, so we can test them on a variety of API versions and in other conditions. We just need to suppress the UI tests. To do this, we subclassed the Android ActivityTestRule and overrode the apply method:

@Override
public Statement apply(Statement base, final Description description) {
    if (!canRunUiTests(InstrumentationRegistry.getContext())) {
        // If we can't run UI tests, then return a statement that does nothing
        // at all.  With normal JUnit tests we'd just throw an assumption
        // failure and the test would be ignored, but that makes the Android
        // runner angry.
        return new Statement() {
            @Override
            public void evaluate() throws Throwable {
                // Do nothing
            }
        };
    }

    return super.apply(base, description);
}

/**
 * Checks that the screen size is close enough to that of our tablet device.
 */
@TargetApi(Build.VERSION_CODES.HONEYCOMB_MR2)
private boolean canRunUiTests(Context context) {
    if (Build.VERSION.SDK_INT < Build.VERSION_CODES.HONEYCOMB_MR2) {
        return false;
    }
    int screenWidth = dpToPx(context,
            context.getResources().getConfiguration().screenWidthDp);
    return screenWidth >= 600;
}

private int dpToPx(Context context, int dp) {
    DisplayMetrics displayMetrics = context.getResources().getDisplayMetrics();
    return Math.round(dp * displayMetrics.density);
}

When the rule is run, we check if the screen width meets a minimum number of pixels. If it doesn’t, an empty Statement is returned that turns the test into a no-op. These show up as passed rather than skipped in the output, but there doesn’t seem to be a nice way to signal to the Android JUnit runner that the test is being ignored programatically.