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## Backing up with tar, curl, and SFTP with key-based authentication

I have multiple backup strategies, from restic (which was preceded by duplicity) to btrfs snapshots that I sync over ssh. You can never have too many backups though (especially for your most valuable data that can't be easily replaced), so in this post I want to share another of the mechanisms I employ.

Backup systems have to suit the situation at hand, and in this case I have a personal git server which I backup daily to Backblaze B2. In order to be really absolutely sure that I don't lose it though, I also back it up to my home NAS (see also the series that I wrote on it). As you might have guessed km the title of this post, it takes backups using tar. I have recently upgraded it to transfer these backups over SFTP (SSH File Transfer Protocol).

Given that the sftp command exists, one might wonder why I use curl instead. Unfortunately, sftp as far as I can tell does not support uploading a file passed in though stdin - which is very useful when you have limited disk space on the source host! But using curl, we can pipe the output of tar directly to curl without touching the disk.

Documentation is sadly rather sparse on using curl to upload via SFTP, so it took some digging to figure out how to do it using SSH keys. SSH keys are considerably more secure than using a password (and a growing number of my systems are setup to disallow password authentication altogether), so I'll be using SSH key based authentication in this post.

To start, you'll need to generate a new SSH keypair. I like to use ed25519:

ssh-keygen -t ed25519

When prompted, choose where you want to save it to (preferably with a descriptive name), and then do not put a password on it. This is important, because at least in my case want this to operate completely autonomously without any user input.

Then, copy the public SSH key to your remote server (I strongly recommend using an account that is locked to be SFTP-only and no shell access - this tutorial seems to be good at explaining the steps involved in doing this), and then on the device doing the backing up do a test to both make sure it works and add the remote server to the known_hosts file:

sudo -u backupuser bash
ssh -i path/to/keyfile -T remoteuser@remotehost

Now we've got our SSH / SFTP setup done, we can do the backup itself:

ionice -c Idle nice -n20 tar --create --exclude-tag .BACKUP_IGNORE --gzip --file path/to/dir_to_backup | curl -sS --user "remoteuser:" --key "path/to/sshkey_ed25519" --pubkey "path/to/sshkey_ed25519.pub" -T - "sftp://example.com/path/on/remote/upload_filename.tar.gz"

Let's break this down a bit:

• ionice -c Idle node -n20: Push the backup job into the background - both for the CPU and disk priorities. Optional.
• tar --create --exclude-tag .BACKUP_IGNORE --gzip --file path/to/dir_to_backup: An example tar command. Use whatever you want here.
• --user "remoteuser:": The remoteuser bit there is the user to login to the remote host with. The bit after the colon is technically the password, but we're leaving that blank 'cause we're using SSH keys instead.
• --key "path/to/sshkey_ed25519": The path to the SSH private key.
• -T -: Upload the standard input instead of a file on disk
• --pubkey "path/to/sshkey_ed25519.pub": The path to the SSH public key.
• sftp://example.com/path/on/remote/upload_filename.tar.gz: The host to upload to and path thereon to upload the standard input to. If you need to specify a custom port here, do sftp://example.com:20202/path/blah/.... instead, where 20202 is your custom port number.

Personally, I'm using this technique with an SSH tunnel, so my variant of the above command looks a bit like this (extra bits around the edges stripped away for clarity):

git_backup_user="sftpbackups";
git_backup_location="sftp://localhost:20204/git-backups";
git_backup_key="path/to/sshkey_ed25519";
upload_filename="git-$(date +"%Y-%m-%d").tar.gz"; nice -n20 tar --create --exclude-tag .BACKUP_IGNORE --gzip --file - git/{data,gitea,repos}/ www/blog | curl -sS --user "${git_backup_user}:" --key "${git_backup_key}" --pubkey "${git_backup_key}.pub" -T - "${git_backup_location}/${upload_filename}"

That's it for this post. If you've got any questions or comments, please post them below.

## lnav basics tutorial

Last year, I blogged about lnav. lnav is a fantastic tool for analysing log files, and after getting a question from CrimsonTome I thought I'd write up a longer-form tutorial on the basics of using it, as I personally find it exceedingly useful.

I'll be using an Ubuntu Server 20.04 instance for this tutorial, but anything Linuxy will work just fine. As mentioned in my previous post, it's available in the default repositories for your distribution. For apt-based systems, install like so:

sudo apt install lnav

Adjust for your own package manager. For example, pacman-based distributions should do this:

sudo pacman -S lnav

lnav operates on 1 or more input files. It's common to use logrotate to rotate log files, so this is what I'd recommend to analyse all your logs of a particular type in 1 go (here I analyse generic syslog logs):

lnav /var/log/syslog*

On your system you may need to sudo that. Once you've got lnav started, you may need to wait a moment for it to parse all the log files - especially if you have multi-million line logfiles.

After it's finished loading, we can get to analysing the logs at hand. The most recent logs appear at the bottom, and you'll notice that lnav will have coloured various parts of each log message - the reason for this will become apparently later on. lnav should also livestream log lines from disk too.

Use the arrow keys or scroll up / down to navigate log messages.

lnav operates via a command pallette system, which if you use GitHub's [Atom IDE] (https://atom.io/) or Sublime Text (which is apparently where the feature originated) may already be familiar to you. In lnav's case, it's also crossed with a simple shell. Let's start with the most important command: :filter-out.

To execute a command, simply start typing. Commands in lnav are prefixed with a colon :. :filter-out takes a regular expression as it's only argument and filters all log lines which match the given regular expression out and hides them. Sticking with our earlier syslog theme, here's an example:

:filter-out kernel:

You'll notice that once you've finished typing :filter-out, lnav will show you some help in a pane at the bottom of the screen showing you how to use that command.

:filter-out has a twin that's also useful to remember: :filter-in. Unlike :filter-out, :filter-in does the opposite - anything that doesn't match the specified pattern is hidden from view. Very useful if you know what kind of log messages you're looking for, and they are a (potentially very small) subset of a much larger and more unstructured log file.

:filter-in dovecot:

To delete all existing filters and reset the view, hit Ctrl + R.

lnav has many other built-in commands. Check out the full reference here: https://docs.lnav.org/en/latest/commands.html.

The other feature that lnav comes with is also the most powerful: SQLite3 support. By parsing common log file formats (advanced users can extend lnav by defining their own custom formats, but the specifics of how to do this are best left to the lnav documentation), it can enable you to query your log files by writing arbitrary SQLite queries!

To understand how to query a file, first hit the p key. This will show you how lnav has parsed the log line at the top of the screen (scroll as normal to look at different lines, and hit p again to hide). Here's an example:

Using this information, we can then make an SQL query against the data. Press semicolon ; to open the SQL query prompt, and then enter something like this:

SELECT * FROM syslog_log WHERE log_procname == "gitea";

....hit the enter key when you're done composing your query, and the results should then appear! You can scroll through them just like you do with the regular log viewer - you just can't use :filter-in and :filter-out until you leave the query results window with the q key (this would be a really useful feature though!).

If you're running lnav on your Nginx logs (located in /var/log/nginx/ by default), then I find this query to be of particular use:

SELECT COUNT(cs_referer) AS count, cs_referer FROM access_log GROUP BY cs_referer ORDER BY COUNT(cs_referer) DESC

That concludes this basic tutorial on lnav. There are many more features that lnav offers:

• :filter-expr for filtering the main view by SQL query
• Analysing files on remote hosts over SSH
• Search logs for a given string (press / and start typing)
• Too many others to list here

Check out the full documentation here: https://docs.lnav.org/

## Tips for training (large numbers of) AI models

As part of my PhD, I'm training AI models. The specifics as to what for don't particularly matter for this post (though if you're curious I recommend my PhD update blog post series). Over the last year or so, I've found myself training a lot of AI models, and dealing with a lot of data. In this post, I'm going to talk about some of the things I've found helpful and some of the things things I've found that are best avoided. Note that this is just a snapshot of my current practices now - this will probably gradually change over time.

I've been working with Tensorflow.js and Tensorflow for Python on various Linux systems. If you're on another OS or not working with AI then what I say here should still be somewhat relevant.

### Datasets

First up: a quick word on datasets. While this post is mainly about AI models, datasets are important too. Keeping them organised is vitally important. Keeping all the metadata that associated with them is also vitally important. Keeping a good directory hierarchy is the best way to achieve this.

I also recommend sticking with a standard format that's easy to parse using your preferred language - and preferably lots of other languages too. Json Lines is my personal favourite format for data - potentially compressed with Gzip if the filesize of is very large.

### AI Models

There are multiple facets to the problem of wrangling AI models:

1. Code that implements the model itself and supporting code
2. Checkpoints from the training process
3. Analysis results from analysing such models

All of these are important for different reasons - and are also affected by where it is that you're going to be training your model.

By far the most important thing I recommend doing is using Git with a remote such as GitHub and committing regularly. I can't stress enough how critical this is - it's the best way to both keep a detailed history of the code you've written and keep a backup at the same time. It also makes working on multiple computers easy. Getting into the habit of using Git for any project (doesn't matter what it is) will make your life a lot easier. At the beginning of a programming session, pull down your changes. Then, as you work, commit your changes and describe them properly. Finally, push your changes to the remote after committing to keep them backed up.

Coming in at a close second is implementing is a command line interface with the ability to change the behaviour of your model. This includes:

• Setting input datasets
• Specifying output directories
• Model hyperparameters (e.g. input size, number of layers, number of units per layer, etc)

This is invaluable for running many different variants of your model quickly to compare results. It is also very useful when training your model in headless environments, such as on High Performance Computers (HPCs) such as Viper that my University has.

For HPCs that use Slurm, a great tip here is that when you call sbatch on your job file (e.g. sbatch path/to/jobfile.job), it will preserve your environment. This lets you pass in job-specific parameters by writing a script like this:

#!/usr/bin/env bash
#SBATCH -J TwImgCCT
#SBATCH -N 1
#SBATCH -n 4
#SBATCH --gres=gpu:1
#SBATCH -o %j.%N.%a.out
#SBATCH -e %j.%N.%a.err
#SBATCH -p gpu05,gpu
#SBATCH --time=5-00:00:00
#SBATCH --mem=25600
# 25600 = 25GiB memory required

# Viper use Trinity ClusterVision: https://clustervision.com/trinityx-cluster-management/ and https://github.com/clustervision/trinityX

echo ">>> Installing requirements";
conda run -n py38 pip install -r requirements.txt;
echo ">>> Training model";
/usr/bin/env time --verbose conda run -n py38 src/my_model.py ${PARAMS} echo ">>> exited with code$?";

....which you can call like so:

PARAMS="--size 4 --example 'something else' --input path/to/file --output outputs/20211002-resnet" sbatch path/to/jobfile.job

You may end up finding you have rather a lot of code behind your model - especially for data preprocessing depending on your dataset. To handle this, I go by 2 rules of thumb:

1. If a source file of any language is more than 300 lines long, it should be split into multiple files
2. If a collection of files do a thing together rather nicely, they belong in a separate Git repository.

To elaborate on these, having source code files become very long makes them difficult to maintain, understand, and re-use in future projects. Splitting them up makes your life much easier.

Going further, modularising your code is also an amazing paradigm to work with. I've broken many parts of my various codebases I've implemented for my PhD out as open-source projects on npm (the Node Package Manager) - most notably applause-cli, terrain50, terrain50-cli, nimrod-data-downloader, and twitter-academic-downloader.

By making them open-source, I'm not only making my research and methods more transparent and easier for others to independently verify, but I'm also allowing others to benefit from them (and potentially improve them) too! As they say, there's no need to re-invent the wheel.

Eventually, I will be making the AI models I'm implementing for my PhD open-source too - but this will take some time as I want to ensure that the models actually work before doing so (I've got 1 model I implemented fully and documented too, but in the end it has a critical bug that means the whole thing is useless.....).

Saving checkpoints from the training process of your model is also essential. I recommend doing so at the end of each epoch. As part of this, it's also useful to have a standard format for your output artefacts from the training process. Ideally, these artefacts can be used to identify precisely what dataset and hyperparameters that model and checkpoints were trained with.

At the moment, my models output something like this:

+ output_dir/
+ summary.txt       Summary of the layers of the model and their output shapes
+ metrics.tsv       TSV file containing training/validation loss/accuracy and epoch numbers
+ settings.toml     The TOML settings that the model was trained with
+ checkpoints/      Directory containing the checkpoints - 1 per epoch
+ checkpoint_e1_val_acc0.699.hdf5   Example checkpoint filename [Tensorflow for Python]
+ 0/            OR, if using Tensorflow.js instead of Tensorflow for Python, 1 directory per checkpoint
+ this_run.log      Logfile for this run [depends on where the program is being executed]

settings.toml leads me on to settings files. Personally I use TOML for mine, and I use 2 files:

• settings.default.toml - Contains all the default values of the settings, and is located alongside the code for my model
• example.toml - Custom settings that override values in the default settings file can be specified using my standard --config CLI argument.

Having a config file is handy when you have multiple dataset input files that rarely change. Generally speaking you want to ensure that you minimise the number of CLI arguments that you have to specify when running your model, as then it reduces cognitive load when you're training many variants of a model at once (I've found that wrangling dozens of different dataset files and model variants is hard enough to focus on and keep organised :P).

Analysis results are the final aspect here that it's important to keep organised - and the area in which I have the least experience. I've found it's important to keep track of which model checkpoint it was that the analysis was done with and which dataset said model was trained on. Keeping the entire chain of dataflow clear and easy to follow is difficult because the analysis one does is usually ad-hoc, and often has to be repeated many times on different model variants.

For this, so far I generate statistics and some graphs on the command line. If you're not already familiar with the terminal / command line of your machine, I can recommend checking out my earlier post Learn Your Terminal, which has a bunch of links to tutorials for this. In addition, jq is an amazing tool for manipulating JSON data. It's not installed by default on most systems, but it's available in most default repositories and well worth the install.

For some graphs, I use Gnuplot. Usually though this is only for more complex plots, as it takes a moment to write a .plt file to generate the graph I want in it.

I'm still looking for a good tool that makes it easy to generate basic graphs from the command line, so please get in touch if you've found one.

I'm also considering integrating some of the basic analysis into my model training program itself, such that it generates e.g. confusion matrices automatically as part of the training process. matplotlib seems to do the job here for plotting graphs in Python, but I have yet to find an equivalent library for Javascript. Again, if you've found one please get in touch by leaving a comment below.

### Conclusion

In this post, I've talked about some of the things I've found helpful so far while I've been training models. From using Git to output artefacts to implementing command line interfaces and wrangling datasets, implementing the core AI model itself is actually only a very small part of an AI project.

Hopefully this post has given you some insight into the process of developing an AI model / AI-powered system. While I've been doing some of these things since before I started my PhD (like Git), others have taken me a while to figure out - so I've noted them down here so that you don't have to spend ages figuring out the same things!

If you've got some good tips you'd like to share on developing AI models (or if you've found the tips here in this blog post helpful!), please do share them below.

## NAS Backups, Part 2: Btrfs send / receive

Hey there! In the first post of this series, I talked about my plan for a backup NAS to complement my main NAS. In this part, I'm going to show the pair of scripts I've developed to take care of backing up btrfs snapshots.

The first script is called snapshot-send.sh, and it:

1. Calculates which snapshot it is that requires sending
2. Uses SSH to remote into the backup NAS
3. Pipes the output of btrfs send to snapshot-receive.sh on the backup NAS that is called with sudo

Note there that while sudo is used for calling snapshot-receive.sh, the account it uses to SSH into the backup NAS, it doesn't have completely unrestricted sudo access. Instead, a sudo rule is used to restrict it to allow only specific commands to be called (without a password, as this is intended to be a completely automated and unattended system).

The second script is called snapshot-receive.sh, and it receives the output of btrfs send and pipes it to btrfs receive. It also has some extra logic to delete old snapshots and stuff like that.

Both of these are designed to be command line programs in their own right with a simple CLI, and useful error / help messages to assist in understanding it when I come back to it to fix an issue or extend it after many months.

### snapshot-send.sh

As described above, snapshot-send.sh sends btrfs snapshot to a remote host via SSH and the snapshot-receive.sh script.

Before we continue and look at it in detail, it is important to note that snapshot-send.sh depends on btrfs-snapshot-rotation. If you haven't already done so, you should set that up first before setting up my scripts here.

If you have btrfs-snapshot-rotation setup correctly, you should have something like this in your crontab:

# Btrfs automatic snapshots
0 * * * *       cronic /root/btrfs-snapshot-rotation/btrfs-snapshot /mnt/some_btrfs_filesystem/main /mnt/some_btrfs_filesystem/main/.snapshots hourly 8
0 2 * * *       cronic /root/btrfs-snapshot-rotation/btrfs-snapshot /mnt/some_btrfs_filesystem/main /mnt/some_btrfs_filesystem/main/.snapshots daily 4
0 2 * * 7       cronic /root/btrfs-snapshot-rotation/btrfs-snapshot /mnt/some_btrfs_filesystem/main /mnt/some_btrfs_filesystem/main/.snapshots weekly 4

I use cronic there to reduce unnecessary emails. I also have a subvolume there for the snapshots:

sudo btrfs subvolume create /mnt/some_btrfs_filesystem/main/.snapshots

Because Btrfs does not take take a snapshot of any child subvolumes when it takes a snapshot, I can use this to keep all my snapshots organised and associated with the subvolume they are snapshots of.

If done right, ls /mnt/some_btrfs_filesystem/main/.snapshots should result in something like this:

2021-07-25T02:00:01+00:00-@weekly  2021-08-17T07:00:01+00:00-@hourly
2021-08-01T02:00:01+00:00-@weekly  2021-08-17T08:00:01+00:00-@hourly
2021-08-08T02:00:01+00:00-@weekly  2021-08-17T09:00:01+00:00-@hourly
2021-08-14T02:00:01+00:00-@daily   2021-08-17T10:00:01+00:00-@hourly
2021-08-15T02:00:01+00:00-@daily   2021-08-17T11:00:01+00:00-@hourly
2021-08-15T02:00:01+00:00-@weekly  2021-08-17T12:00:01+00:00-@hourly
2021-08-16T02:00:01+00:00-@daily   2021-08-17T13:00:01+00:00-@hourly
2021-08-17T02:00:01+00:00-@daily   last_sent_@daily.txt
2021-08-17T06:00:01+00:00-@hourly

Ignore the last_sent_@daily.txt there for now - it's created by snapshot-send.sh so that it can remember the name of the snapshot it last sent. We'll talk about it later.

With that out of the way, let's start going through snapshot-send.sh! First up is the CLI and associated error handling:

#!/usr/bin/env bash
set -e;

dir_source="${1}"; tag_source="${2}";
tag_dest="${3}"; loc_ssh_key="${4}";
remote_host="${5}"; if [[ -z "${remote_host}" ]]; then
echo "This script sends btrfs snapshots to a remote host via SSH.
The script snapshot-receive must be present on the remote host in the PATH for this to work.
It pairs well with btrfs-snapshot-rotation: https://github.com/mmehnert/btrfs-snapshot-rotation
Usage:
snapshot-send.sh <snapshot_dir> <source_tag_name> <dest_tag_name> <ssh_key> <user@example.com>

Where:
<snapshot_dir> is the path to the directory containing the snapshots
<source_tag_name> is the tag name to look for (see btrfs-snapshot-rotation).
<dest_tag_name> is the tag name to use when sending to the remote. This must be unique across all snapshot rotations sent.
<ssh_key> is the path to the ssh private key
<user@example.com> is the user@host to connect to via SSH" >&2;
exit 0;
fi

# $EUID = effective uid if [[ "${EUID}" -ne 0 ]]; then
echo "Error: This script must be run as root (currently running as effective uid ${EUID})" >&2; exit 5; fi if [[ ! -e "${loc_ssh_key}" ]]; then
echo "Error: When looking for the ssh key, no file was found at '${loc_ssh_key}' (have you checked the spelling and file permissions?)." >&2; exit 1; fi if [[ ! -d "${dir_source}" ]]; then
echo "Error: No source directory located at '${dir_source}' (have you checked the spelling and permissions?)" >&2; exit 2; fi ############################################################################### Pretty simple stuff. snapshot-send.sh is called like so: snapshot-send.sh /absolute/path/to/snapshot_dir SOURCE_TAG DEST_TAG_NAME path/to/ssh_key user@example.com A few things to unpack here. • /absolute/path/to/snapshot_dir is the path to the directory (i.e. btrfs subvolume) containing the snapshots we want to read, as described above. • SOURCE_TAG: Given the directory (subvolume) name of a snapshot (e.g. 2021-08-17T02:00:01+00:00-@daily), then the source tag is the bit at the end after the at sign @ - e.g. daily. • DEST_TAG_NAME: The tag name to give the snapshot on the backup NAS. Useful, because you might have multiple subvolumes you snapshot with btrfs-snapshot-rotation and they all might have snapshots with the daily tag. • path/to/ssh_key: The path to the (unencrypted!) SSH key to use to SSH into the remote backup NAS. • user@example.com: The user and hostname of the backup NAS to SSH into. This is a good time to sort out the remote user we're going to SSH into (we'll sort out snapshot-receive.sh and the sudo rules in the next section below). Assuming that you already have a Btrfs filesystem setup and automounting on boot on the remote NAS, do this:  sudo useradd --system --home /absolute/path/to/btrfs-filesystem/backups backups sudo groupadd backup-senders sudo usermod -a -G backup-senders backups cd /absolute/path/to/btrfs-filesystem/backups sudo mkdir .ssh sudo touch .ssh/authorized_keys sudo chown -R backups:backups .ssh sudo chmod -R u=rwX,g=rX,o-rwx .ssh  Then, on the main NAS, generate the SSH key:  mkdir -p /root/backups && cd /root/backups ssh-keygen -t ed25519 -C backups@main-nas -f /root/backups/ssh_key_backup_nas_ed25519  Then, copy the generated SSH public key to the authorized_keys file on the backup NAS (located at /absolute/path/to/btrfs-filesystem/backups/.ssh/authorized_keys). Now that's sorted, let's continue with snapshot-send.sh. Next up are a few miscellaneous functions:  # The filepath to the last sent text file that contains the name of the snapshot that was last sent to the remote. # If this file doesn't exist, then we send a full snapshot to start with. # We need to keep track of this because we need this information to know which # snapshot we need to parent the latest snapshot from to send snapshots incrementally. filepath_last_sent="${dir_source}/last_sent_@${tag_source}.txt"; ## Logs a message to stderr. #$*    The message to log.
log_msg() {
echo "[ $(date +%Y-%m-%dT%H:%M:%S) ] remote/${HOSTNAME}: >>> ${*}"; } ## Lists all the currently available snapshots for the current source tag. list_snapshots() { find "${dir_source}" -maxdepth 1 ! -path "${dir_source}" -name "*@${tag_source}" -type d;
}

## Returns an exit code of 0 if we've sent a snapshot, or 1 if we haven't.
have_sent() {
if [[ ! -f "${filepath_last_sent}" ]]; then return 1; else return 0; fi } ## Fetches the directory name of the last snapshot sent to the remote with the given tag name. last_sent() { if [[ -f "${filepath_last_sent}" ]]; then
cat "${filepath_last_sent}"; fi } # Runs snapshot-receive on the remote host. do_ssh() { ssh -o "ServerAliveInterval=900" -i "${loc_ssh_key}" "${remote_host}" sudo snapshot-receive "${tag_dest}";
}

Particularly of note is the filepath_last_sent variable - this is set to the path to that text file I mentioned earlier.

Other than that it's all pretty well commented, so let's continue on. Next, we need to determine the name of the latest snapshot:

latest_snapshot="$(list_snapshots | sort | tail -n1)"; latest_snapshot_dirname="$(dirname "${latest_snapshot}")"; With this information in hand we can compare it to the last snapshot name we sent. We store this in the text file mentioned above - the path to which is stored in the filepath_last_sent variable. if [[ "$(dirname "${latest_snapshot_dirname}")" == "$(cat "${filepath_last_sent}")" ]]; then if [[ -z "${FORCE_SEND}" ]]; then
echo "We've sent the latest snapshot '${latest_snapshot_dirname}' already and the FORCE_SEND environment variable is empty or not specified, skipping"; exit 0; else echo "We've sent it already, but sending it again since the FORCE_SEND environment variable is specified"; fi fi If the latest snapshot has the same name as the one we last send, we exit out - unless the FORCE_SEND environment variable is specified (to allow for an easy way to fix stuff if it goes wrong on the other end). Now, we can actually send the snapshot to the remote:  if ! have_sent; then log_msg "Sending initial snapshot$(dirname "${latest_snapshot}")"; btrfs send "${latest_snapshot}" | do_ssh;
else
parent_snapshot="${dir_source}/$(last_sent)";
if [[ ! -d "${parent_snapshot}" ]]; then echo "Error: Failed to locate parent snapshot at '${parent_snapshot}'" >&2;
exit 3;
fi

log_msg "Sending incremental snapshot $(dirname "${latest_snapshot}") parent $(last_sent)"; btrfs send -p "${parent_snapshot}" "${latest_snapshot}" | do_ssh; fi have_sent simply determines if we have previously sent a snapshot before. We know this by checking the filepath_last_sent text file. If we haven't, then we send a full snapshot rather than an incremental one. If we're sending an incremental one, then we find the parent snapshot (i.e. the one we last sent). If we can't find it, we generate an error (it's because of this that you need to store at least 2 snapshots at a time with btrfs-snapshot-rotation). After sending a snapshot, we need to update the filepath_last_sent text file: log_msg "Updating state information"; basename "${latest_snapshot}" >"${filepath_last_sent}"; log_msg "Snapshot sent successfully"; ....and that concludes snapshot-send.sh! Once you've finished reading this blog post and testing your setup, put your snapshot-send.sh calls in a script in /etc/cron.daily or something. ### snapshot-receive.sh Next up is the receiving end of the system. The CLI for this script is much simpler, on account of sudo rules only allowing exact and specific commands (no wildcards or regex of any kind). I put snapshot-receive.sh in /usr/local/sbin and called it snapshot-receive. Let's get started: #!/usr/bin/env bash # This script wraps btrfs receive so that it can be called by non-root users. # It should be saved to '/usr/local/sbin/snapshot-receive' (without quotes, of course). # The following entry needs to be put in the sudoers file: # # %backup-senders ALL=(ALL) NOPASSWD: /usr/local/sbin/snapshot-receive TAG_NAME # # ....replacing TAG_NAME with the name of tag you want to allow. You'll need 1 line in your sudoers file per tag you want to allow. # Edit your sudoers file like this: # sudo visudo # The ABSOLUTE path to the target directory to receive to. target_dir="CHANGE_ME"; # The maximum number of backups to keep. max_backups="7"; # Allow only alphanumeric characters in the tag tag="$(echo "${1}" | tr -cd '[:alnum:]-_')"; snapshot-receive.sh only takes a single argument, and that's the tag it should use for the snapshot being received:  sudo snapshot-receive DEST_TAG_NAME  The target directory it should save snapshots to is stored as a variable at the top of the file (the target_dir there). You should change this based on your specific setup. It goes without saying, but the target directory needs to be a directory on a btrfs filesystem (preferable raid1, though as I've said before btrfs raid1 is a misnomer). We also ensure that the tag contains only safe characters for security. max_backups is the maximum number of snapshots to keep. Any older snapshots will be deleted. Next, ime error handling: ############################################################################### #$EUID = effective uid
if [[ "${EUID}" -ne 0 ]]; then echo "Error: This script must be run as root (currently running as effective uid${EUID})" >&2;
exit 5;
fi

if [[ -z "${tag}" ]]; then echo "Error: No tag specified. It should be specified as the 1st and only argument, and may only contain alphanumeric characters." >&2; echo "Example:" >&2; echo " snapshot-receive TAG_NAME_HERE" >&2; exit 4; fi Nothing too exciting. Continuing on, a pair of useful helper functions:  ############################################################################### ## Logs a message to stderr. #$*    The message to log.
log_msg() {
echo "[ $(date +%Y-%m-%dT%H:%M:%S) ] remote/${HOSTNAME}: >>> ${*}"; } list_backups() { find "${target_dir}/${tag}" -maxdepth 1 ! -path "${target_dir}/${tag}" -type d; } list_backups lists the snapshots with the given tag, and log_msg logs messages to stdout (not stderr unless there's an error, because otherwise cronic will dutifully send you an email every time the scripts execute). Next up, more error handling: ############################################################################### if [[ "${target_dir}" == "CHANGE_ME" ]]; then
echo "Error: target_dir was not changed from the default value." >&2;
exit 1;
fi

if [[ ! -d "${target_dir}" ]]; then echo "Error: No directory was found at '${target_dir}'." >&2;
exit 2;
fi

if [[ ! -d "${target_dir}/${tag}" ]]; then
log_msg "Creating new directory at ${target_dir}/${tag}";
mkdir "${target_dir}/${tag}";
fi

We check:

• That the target directory was changed from the default CHANGE_ME value
• That the target directory exists

We also create a subdirectory for the given tag if it doesn't exist already.

With the preamble completed, we can actually receive the snapshot:

log_msg "Launching btrfs in chroot mode";

time nice ionice -c Idle btrfs receive --chroot "${target_dir}/${tag}";

We use nice and ionice to reduce the priority of the receive to the lowest possible level. If you're using a Raspberry Pi (I have a Raspberry Pi 4 with 4GB RAM) like I am, this is important for stability (Pis tend to fall over otherwise). Don't worry if you experience some system crashes on your Pi when transferring the first snapshot - I've found that incremental snapshots don't cause the same issue.

We also use the chroot option there for increased security.

Now that the snapshot is transferred, we can delete old snapshots if we have too many:

backups_count="$(echo -e "$(list_backups)" | wc -l)";

log_msg "Btrfs finished, we now have ${backups_count} backups:"; list_backups; while [[ "${backups_count}" -gt "${max_backups}" ]]; do oldest_backup="$(list_backups | sort | head -n1)";
log_msg "Maximum number backups is ${max_backups}, requesting removal of backup for$(dirname "${oldest_backup}")"; btrfs subvolume delete "${oldest_backup}";

backups_count="$(echo -e "$(list_backups)" | wc -l)";
done

log_msg "Done, any removed backups will be deleted in the background";

Sorted! The only thing left to do here is to setup those sudo rules. Let's do that now. Execute sudoedit /etc/sudoers, and enter the following:

%backup-senders ALL=(ALL) NOPASSWD: /usr/local/sbin/snapshot-receive TAG_NAME

Replace TAG_NAME with the DEST_TAG_NAME you're using. You'll need 1 entry in /etc/sudoers for each DEST_TAG_NAME you're using.

We assign the rights to the backup-senders group we created earlier, of which the user we are going to SSH in with is a member. This make the system more flexible should we want to extend it later.

Warning: A mistake in /etc/sudoers can leave you unable to use sudo! Make sure you have a root shell open in the background and that you test sudo again after making changes to ensure you haven't made a mistake.

That completes the setup of snapshot-receive.sh.

### Conclusion

With snapshot-send.sh and snapshot-receive.sh, we now have a system for transferring snapshots from 1 host to another via SSH. If combined with full disk encryption (e.g. with LUKS), this provides a secure backup system with a number of desirable qualities:

• The main NAS can't access the backups on the backup NAS (in case fo ransomware)
• Backups are encrypted during transfer (via SSH)
• Backups are encrypted at rest (LUKS)

To further secure the backup NAS, one could:

• Automatically start / shutdown the backup NAS (though with full disk encryption when it boots up it would require manual intervention)

At the bottom of this post I've included the full scripts for you to copy and paste.

As it turns out, there will be 1 more post in this series, which will cover generating multiple streams of backups (e.g. weekly, monthly) from a single stream of e.g. daily backups on my backup NAS.

### Full scripts

#### snapshot-send.sh

#!/usr/bin/env bash
set -e;

dir_source="${1}"; tag_source="${2}";
tag_dest="${3}"; loc_ssh_key="${4}";
remote_host="${5}"; if [[ -z "${remote_host}" ]]; then
echo "This script sends btrfs snapshots to a remote host via SSH.
The script snapshot-receive must be present on the remote host in the PATH for this to work.
It pairs well with btrfs-snapshot-rotation: https://github.com/mmehnert/btrfs-snapshot-rotation
Usage:
snapshot-send.sh <snapshot_dir> <source_tag_name> <dest_tag_name> <ssh_key> <user@example.com>

Where:
<snapshot_dir> is the path to the directory containing the snapshots
<source_tag_name> is the tag name to look for (see btrfs-snapshot-rotation).
<dest_tag_name> is the tag name to use when sending to the remote. This must be unique across all snapshot rotations sent.
<ssh_key> is the path to the ssh private key
<user@example.com> is the user@host to connect to via SSH" >&2;
exit 0;
fi

# $EUID = effective uid if [[ "${EUID}" -ne 0 ]]; then
echo "Error: This script must be run as root (currently running as effective uid ${EUID})" >&2; exit 5; fi if [[ ! -e "${loc_ssh_key}" ]]; then
echo "Error: When looking for the ssh key, no file was found at '${loc_ssh_key}' (have you checked the spelling and file permissions?)." >&2; exit 1; fi if [[ ! -d "${dir_source}" ]]; then
echo "Error: No source directory located at '${dir_source}' (have you checked the spelling and permissions?)" >&2; exit 2; fi ############################################################################### # The filepath to the last sent text file that contains the name of the snapshot that was last sent to the remote. # If this file doesn't exist, then we send a full snapshot to start with. # We need to keep track of this because we need this information to know which # snapshot we need to parent the latest snapshot from to send snapshots incrementally. filepath_last_sent="${dir_source}/last_sent_@${tag_source}.txt"; ## Logs a message to stderr. #$*    The message to log.
log_msg() {
echo "[ $(date +%Y-%m-%dT%H:%M:%S) ] remote/${HOSTNAME}: >>> ${*}"; } ## Lists all the currently available snapshots for the current source tag. list_snapshots() { find "${dir_source}" -maxdepth 1 ! -path "${dir_source}" -name "*@${tag_source}" -type d;
}

## Returns an exit code of 0 if we've sent a snapshot, or 1 if we haven't.
have_sent() {
if [[ ! -f "${filepath_last_sent}" ]]; then return 1; else return 0; fi } ## Fetches the directory name of the last snapshot sent to the remote with the given tag name. last_sent() { if [[ -f "${filepath_last_sent}" ]]; then
cat "${filepath_last_sent}"; fi } do_ssh() { ssh -o "ServerAliveInterval=900" -i "${loc_ssh_key}" "${remote_host}" sudo snapshot-receive "${tag_dest}";
}

latest_snapshot="$(list_snapshots | sort | tail -n1)"; latest_snapshot_dirname="$(dirname "${latest_snapshot}")"; if [[ "$(dirname "${latest_snapshot_dirname}")" == "$(cat "${filepath_last_sent}")" ]]; then if [[ -z "${FORCE_SEND}" ]]; then
echo "We've sent the latest snapshot '${latest_snapshot_dirname}' already and the FORCE_SEND environment variable is empty or not specified, skipping"; exit 0; else echo "We've sent it already, but sending it again since the FORCE_SEND environment variable is specified"; fi fi if ! have_sent; then log_msg "Sending initial snapshot$(dirname "${latest_snapshot}")"; btrfs send "${latest_snapshot}" | do_ssh;
else
parent_snapshot="${dir_source}/$(last_sent)";
if [[ ! -d "${parent_snapshot}" ]]; then echo "Error: Failed to locate parent snapshot at '${parent_snapshot}'" >&2;
exit 3;
fi

log_msg "Sending incremental snapshot $(dirname "${latest_snapshot}") parent $(last_sent)"; btrfs send -p "${parent_snapshot}" "${latest_snapshot}" | do_ssh; fi log_msg "Updating state information"; basename "${latest_snapshot}" >"${filepath_last_sent}"; log_msg "Snapshot sent successfully"; #### snapshot-receive.sh #!/usr/bin/env bash # This script wraps btrfs receive so that it can be called by non-root users. # It should be saved to '/usr/local/sbin/snapshot-receive' (without quotes, of course). # The following entry needs to be put in the sudoers file: # # %backup-senders ALL=(ALL) NOPASSWD: /usr/local/sbin/snapshot-receive TAG_NAME # # ....replacing TAG_NAME with the name of tag you want to allow. You'll need 1 line in your sudoers file per tag you want to allow. # Edit your sudoers file like this: # sudo visudo # The ABSOLUTE path to the target directory to receive to. target_dir="CHANGE_ME"; # The maximum number of backups to keep. max_backups="7"; # Allow only alphanumeric characters in the tag tag="$(echo "${1}" | tr -cd '[:alnum:]-_')"; ############################################################################### #$EUID = effective uid
if [[ "${EUID}" -ne 0 ]]; then echo "Error: This script must be run as root (currently running as effective uid${EUID})" >&2;
exit 5;
fi

if [[ -z "${tag}" ]]; then echo "Error: No tag specified. It should be specified as the 1st and only argument, and may only contain alphanumeric characters." >&2; echo "Example:" >&2; echo " snapshot-receive TAG_NAME_HERE" >&2; exit 4; fi ############################################################################### ## Logs a message to stderr. #$*    The message to log.
log_msg() {
echo "[ $(date +%Y-%m-%dT%H:%M:%S) ] remote/${HOSTNAME}: >>> ${*}"; } list_backups() { find "${target_dir}/${tag}" -maxdepth 1 ! -path "${target_dir}/${tag}" -type d; } ############################################################################### if [[ "${target_dir}" == "CHANGE_ME" ]]; then
echo "Error: target_dir was not changed from the default value." >&2;
exit 1;
fi

if [[ ! -d "${target_dir}" ]]; then echo "Error: No directory was found at '${target_dir}'." >&2;
exit 2;
fi

if [[ ! -d "${target_dir}/${tag}" ]]; then
log_msg "Creating new directory at ${target_dir}/${tag}";
mkdir "${target_dir}/${tag}";
fi

log_msg "Launching btrfs in chroot mode";

time nice ionice -c Idle btrfs receive --chroot "${target_dir}/${tag}";

backups_count="$(echo -e "$(list_backups)" | wc -l)";

log_msg "Btrfs finished, we now have ${backups_count} backups:"; list_backups; while [[ "${backups_count}" -gt "${max_backups}" ]]; do oldest_backup="$(list_backups | sort | head -n1)";
log_msg "Maximum number backups is ${max_backups}, requesting removal of backup for$(dirname "${oldest_backup}")"; btrfs subvolume delete "${oldest_backup}";

backups_count="$(echo -e "$(list_backups)" | wc -l)";
done

log_msg "Done, any removed backups will be deleted in the background";

## NAS Backups, Part 1: Overview

After building my nice NAS, the next thing on my sysadmin todo list was to ensure it is backed up. In this miniseries (probably 2 posts), I'm going to talk about the backup NAS that I've built. As of the time of typing, it is sucessfully backing up my Btrfs subvolumes.

In this first post, I'm going to give an overview of the hardware I'm using and the backup system I've put together. In future posts, I'll go into detail as to how the system works, and which areas I still need to work on moving forwards.

Personally, I find that the 3-2-1 backup strategy is a good rule of thumb:

• 3 copies of the data
• 2 different media
• 1 off-site

What this means is tha you should have 3 copies of your data, with 2 local copies and one remote copy in a different geographical location. To achieve this, I have solved first the problem of the local backup copy, since it's a lot easier and less complicated than the remote one. Although I've talked about backups before (see also), in this case my solution is slightly different - partly due to the amount of data involved, and partly due to additional security measures I'm trying to get into place.

### Hardware

For hardware, I'm using a Raspberry Pi 4 with 4GB RAM (the same as the rest of my cluster), along with 2 x 4 TB USB 3 external hard drives. This is a fairly low-cost and low-performance solution. I don't particularly care how long it takes the backup to complete, and it's relatively cheap to replace if it fails without being unreliable (Raspberry Pis are tough little things).

Here's a diagram of how I've wired it up:

(Can't see the above? Try a direct link to the SVG. Created with drawio.)

I use USB Y-cables to power the hard rives directly from the USB power supply, as the Pi is unlikely to be able to supply enough power for mulitple external hard drives on it's own.

Important Note: As I've discovered with a different unrelated host on my network, if you do this you can back-power the Pi through the USB Y cable, and potentially corrupt the microSD card by doing so. Make sure you switch off the entire USB power supply at once, rather than unplug just the Pi's power cable!

For a power supply, I'm using an Anker 10 port device (though I bought through Amazon, since I wasn't aware that Anker had their own website) - the same one that powers my Pi cluster.

### Strategy

To do the backup itself I'm using the fact that I store my data in Btrfs subvolumes and the btrfs send / btrfs receive commands to send my subvolumes to the remote backup host over SSH. This has a number of benefits:

1. The host doing the backing up has no access to the resulting backups (so if it gets infected it can't also infect the backups)
2. The backups are read-only Btrfs snapshots (so if the backup NAS gets infected my backups can't be altered without first creating a read-write snapshot)
3. Backups are done incrementally to save time, but a full backup is done automatically on the first run (or if the local metadata is missing)

While my previous backup solution using Restic for the server that sent you this web page has point #3 on my list above, it doesn't have points 1 and 2.

Restic does encrypt backups at rest though, which the system I'm setting up doesn't do unless you use LUKS to encrypt the underlying disks that Btrfs stores it's data on. More on that in the future, as I have tentative plans to deal with my off-site backup problem using a similar technique to that which I've used here that also encrypts data at rest when a backup isn't taking place.

In the next post, I'll be diving into the implementation details for the backup system I've created and explaining it in more detail - including sharing the pair of scripts that I've developed that do the heavy lifting.

## Installing Python, Keras, and Tensorflow from source

I found myself in the interesting position recently of needing to compile Python from source. The reasoning behind this is complicated, but it boils down to a need to use Python with Tensorflow / Keras for some natural language processing AI, as Tensorflow.js isn't going to cut it for the next stage of my PhD.

The target upon which I'm aiming to be running things currently is Viper, my University's high-performance computer (HPC). Unfortunately, the version of Python on said HPC is rather old, which necessitated obtaining a later version. Since I obviously don't have sudo permissions on Viper, I couldn't use the default system package manager. Incredibly, pre-compiled Python binaries are not distributed for Linux either, which meant that I ended up compiling from source.

I am going to be assuming that you have a directory at $HOME/software in which we will be working. In there, there should be a number of subdirectories: • bin: For binaries, already added to your PATH • lib: For library files - we'll be configuring this correctly in this guide • repos: For git repositories we clone Make sure you have your snacks - this was a long ride to figure out and write - and it's an equally long ride to follow. I recommend reading this all the way through before actually executing anything to get an overall idea as to the process you'll be following and the assumptions I've made to keep this post a reasonable length. ### Setting up Before we begin, we need some dependencies: • gcc - The compiler • git - For checking out the cpython git repository • readline - An optional dependency of cpython (presumably for the REPL) On Viper, we can load these like so: module load utilities/multi module load gcc/10.2.0 module load readline/7.0 ### Compiling openssl We also need to clone the openssl git repo and build it from source: cd ~/software/repos git clone git://git.openssl.org/openssl.git; # Clone the git repo cd openssl; # cd into it git checkout OpenSSL_1_1_1-stable; # Checkout the latest stable branch (do git branch -a to list all branches; Python will complain at you during build if you choose the wrong one and tell you what versions it supports) ./config; # Configure openssl ready for compilation make -j "$(nproc)"                              # Build openssl

With openssl compiled, we need to copy the resulting binaries to our ~/software/lib directory:

cp lib*.so* ~/software/lib;
# We're done, cd back to the parent directory
cd ..;

To finish up openssl, we need to update some environment variables to let the C++ compiler and linker know about it, but we'll talk about those after dealing with another dependency that Python requires.

### Compiling libffi

libffi is another dependency of Python that's needed if you want to use Tensorflow. To start, go to the libgffi GitHub releases page in your web browser, and copy the URL for the latest release file. It should look something like this:

Then, download it to the target system:

cd ~/software/lib
curl -OL URL_HERE

Note that we do it this way, because otherwise we'd have to run the autogen.sh script which requires yet more dependencies that you're unlikely to have installed.

Then extract it and delete the tar.gz file:

tar -xzf libffi-3.3.tar.gz
rm libffi-3.3.tar.gz

Now, we can configure and compile it:

./configure --prefix=$HOME/software make -j "$(nproc)"

Before we install it, we need to create a quick alias:

cd ~/software;
ln -s lib lib64;
cd -;

libffi for some reason likes to install to the lib64 directory, rather than our pre-existing lib directory, so creating an alias makes it so that it installs to the right place.

### Updating the environment

Now that we've dealt with the dependencies, we now need to update our environment so that the compiler knows where to find them. Do that like so:

export LD_LIBRARY_PATH="$HOME/software/lib:${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"; export LDFLAGS="-L$HOME/software/lib -L$HOME/software/include$LDFLAGS";
export CPPFLAGS="-I$HOME/software/include -I$HOME/software/repos/openssl/include -I$HOME/software/repos/openssl/include/openssl$CPPFLAGS"

It is also advisable to update your ~/.bashrc with these settings, as you may need to come back and recompile a different version of Python in the future.

Personally, I have a file at ~/software/setup.sh which I run with source $HOME/software/setuop.sh in my ~/.bashrc file to keep things neat and tidy. ### Compiling Python Now that we have openssl and libffi compiled, we can turn our attention to Python. First, clone the cpython git repo: git clone https://github.com/python/cpython.git cd cpython; Then, checkout the latest tag. This essentially checks out the latest stable release: git checkout "$(git tag | grep -ivP '[ab]|rc' | tail -n1)"

Important: If you're intention is to use tensorflow, check the Tensorflow Install page for supported Python versions. It's probable that it doesn't yet support the latest version of Python, so you might need to checkout a different tag here. For some reason, Python is really bad at propagating new versions out to the community quickly.

Before we can start the compilation process, we need to configure it. We're going for performance, so execute the configure script like so:

./configure --with-lto --enable-optimizations --with-openssl=/absolute/path/to/openssl_repo_dir

Replace /absolute/path/to/openssl_repo with the absolute path to the above openssl repo.

Now, we're ready to compile Python. Do that like so:

make -j "$(nproc)" This will take a while, but once it's done it should have built Python successfully. For a sanity check, we can also test it like so: make -j "$(nproc)" test

The Python binary compiled should be called simply python, and be located in the root of the git repository. Now that we've compiled it, we need to make a few tweaks to ensure that our shell uses our newly compiled version by default and not the older version from the host system. Personally, I keep my ~/bin folder under version control, so I install host-specific to ~/software, and put ~/software/bin in my PATH like so:

export PATH=$HOME/software/bin With this in mind, we need to create some symbolic links in ~/software/bin that point to our new Python installation: cd$HOME/software/bin;
ln -s relative/path/to/python_binary python
ln -s relative/path/to/python_binary python3
ln -s relative/path/to/python_binary python3.9

Replace relative/path/to/python_binary with the relative path tot he Python binary we compiled above.

To finish up the Python installation, we need to get pip up and running, the Python package manager. We can do this using the inbuilt ensurepip module, which can bootstrap a pip installation for us:

python -m ensurepip --user

This bootstraps pip into our local user directory. This is probably what you want, since if you try and install directly the shebang incorrectly points to the system's version of Python, which doesn't exist.

Then, update your ~/.bash_aliases and add the following:

export LD_LIBRARY_PATH=/absolute/path/to/openssl_repo_dir/lib:$LD_LIBRARY_PATH; alias pip='python -m pip' alias pip3='python -m pip' ...replacing /absolute/path/to/openssl_repo_dir with the path to the openssl git repo we cloned earlier. The next stage is to use virtualenv to locally install our Python packages that we want to use for our project. This is good practice, because it keeps our dependencies locally installed to a single project, so they don't clash with different versions in other projects. Before we can use virtualenv though, we have to install it: pip install virtualenv Unfortunately, Python / pip is not very clever at detecting the actual Python installation location, so in order to actually use virtualenv, we have to use a wrapper script - because the [shebang]() in the main ~/.local/bin/virtualenv entrypoint does not use /usr/bin/env to auto-detect the python binary location. Save the following to ~/software/bin (or any other location that's in your PATH ahead of ~/.local/bin): #!/usr/bin/env bash exec python ~/.local/bin/virtualenv "$@"

For example:

# Write the script to disk
nano ~/software/bin/virtualenv;
# chmod it to make it executable
chmod +x ~/software/bin/virtualenv

### Installing Keras and tensorflow-gpu

With all that out of the way, we can finally use virtualenv to install Keras and tensorflow-gpu. Let's create a new directory and create a virtual environment to install our packages in:

mkdir tensorflow-test
cd tensorflow-test;
virtualenv "$PWD"; source bin/activate; Now, we can install Tensorflow & Keras: pip install tensorflow-gpu It's worth noting here that Keras is a dependency of Tensorflow. Tensorflow has a number of alternate package names you might want to install instead depending on your situation: • tensorflow: Stable tensorflow without GPU support - i.e. it runs on the CPU instead. • tf-nightly-gpu: Nightly tensorflow for the GPU. Useful if your version of Python is newer than the version of Python supported by Tensorflow Once you're done in the virtual environment, exit it like this: deactivate Phew, that was a huge amount of work! Hopefully this sheds some light on the maddenly complicated process of compiling Python from source. If you run into issues, you're welcome to comment below and I'll try to help you out - but you might be better off asking the Python community instead, as they've likely got more experience with Python than I have. ### Sources and further reading ## applause-cli: A Node.js CLI handling library Continuing in the theme of things I've forgotten to talk about, I'd like to post about another package I've released a little while ago. I've been building a number of command line interfaces for my PhD, so I thought it would be best to use a library for this function. I found [clap](), but it didn't quite do what I wanted - so I wrote my own inspired by it. Soon enough I needed to use the code in several different projects, so I abstracted the logic for it out and called it applause-cli, which you can now find on npm. It has no dependencies, and it allows you do define a set of arguments and have it parsed out the values from a given input array of items automatically. Here's an example of how it works: import Program from 'applause-cli'; let program = new Program("path/to/package.json"); program.argument("food", "Specifies the food to find.", "apple") .argument("count", "The number of items to find", 1, "number"); program.parse(process.argv.slice(2)); // Might return { food: "banana", count: 6 } I even have automated documentation generated with documentation and uploaded to my website via Continuous Integration: https://starbeamrainbowlabs.com/code/applause-cli/. I've worked pretty hard on the documentation for this library actually - it even has integrated examples to show you how to use each function! The library can also automatically generate help output from the provided information when the --help argument is detected too - though I have yet to improve the output if a subcommand is called (e.g. mycommand dostuff --help) - this is on my todo list :-) Here's an example of the help text it automatically generates: If this looks like something you'd be interested in using, I recommend checking out the npm package here: https://www.npmjs.com/package/applause-cli For the curious, applause-cli is open-source under the MPL-2.0 licence. Find the code here: https://github.com/sbrl/applause-cli. ## NAS, Part 4: Time machines | Automatic snapshotting with btrfs-snapshot In the last part in this series, I compared ZFS with Btrfs. I ended up choosing Btrfs because it was easier to install and came with a number of advantages. Since last time, I've now put Btrfs to work and have about ~1.3 TiB of data stored in it (much of which is from various devices across the network automatically backing up to it). Before we continue, here's a list of the parts in the series so far: In this post, I'm going to talk about the automatic snapshotting I've setup. Btrfs supports creating snapshots, which are defined as subvolumes that are seeded with data from another subvolume (boundaries between subvolumes are not crossed). Most of the time, these are created to be read-only. In addition because of the copy-on-write system Btrfs uses, a snapshot takes no disk space on its own (other than that required to store the fact that it exists) - it only starts to consume disk space when files that it contains are modified in the original subvolume. To this end, we can efficiently keep a rotating series of snapshots to serve as an initial safety net should a someone accidentally delete a file. Of course, we can't assume that snapshots will be ok as the only backup (I use Restic for that - I'm in the process of reconfiguring it for my new setup) - but they are still useful things to have. To take a Btrfs snapshot, you can do this: sudo btrfs subvolume snapshot -r path/to/source_subvolume path/to/target The problem here, of course, is that you also need a way to delete old snapshots too. While I could roll my own solution for this, I figured that someone has already solved this problem - so it might save me some effort if I look for a pre-existing solution first. After doing a bit of searching without success, I asked on Reddit, and the helpful folks there gave me a number of suggestions: Of these 3, snapper seemed to be the most popular. From some reading, it appeared to be powerful and flexible - at the cost of being easy to understand. btrbk seemed to be feature-packed too, but in the end I decided on btrfs-snapshot. btrfs-snapshot is designed to be used with cron. For example, I have something like this for one of my subvolumes in root user's crontab: 0 * * * * /root/btrfs-snapshot-rotation/btrfs-snapshot path/to/subvolume path/to/subvolume/.snapshots hourly 8 0 2 * * * /root/btrfs-snapshot-rotation/btrfs-snapshot path/to/subvolume path/to/subvolume/.snapshots daily 4 0 2 * * 7 /root/btrfs-snapshot-rotation/btrfs-snapshot path/to/subvolume path/to/subvolume/.snapshots weekly 4 Given a subvolume at path/to/subvolume, it creates the following snapshots in a nested subvolume in path/to/subvolume/.snapshots (which needs to be created manually: sudo btrfs subvolume create path/to/subvolume/.snapshots): • 8 x hourly snapshots • 4 x daily snapshots • 4 x weekly snapshots I find the system so beautifully simple and easy to understand. This is important for me in a system like this, as it has to be easy for me to understand when I inevitably come back to it months or even years later when I've forgotten how it works. The arguments to btrfs-snapshot are easy to understand, and are in the form path/to/source path/to/target tag_name number_of_snapshots_to_keep. This has the added bonus that if a user deletes a file accidentally in our shared drive, they can retrieve it on their own from the .snapshots directory - without my intervention. With this in place and the data (mostly) moved over, my NAS project is almost complete. The final task I have left to do is to setup a proper backup system with Restic to either a remote (e.g. Backblaze B2) or offline location (such as an external HDD). The latter might prove to be a problem though, since the maximum amount of data I can store right now is 5.5 TiB and is only going to grow from there. Portable external hard drives I've seen online don't appear to go up that high, so I suspect I'll need to choose another plan. Should I encounter some interesting issues when setting this final backup step up, I'll make an additional post in this series. If not though, this will probably be the last entry in this series. If you have any questions about my setup, please comment below! I'll dod my best to answer any questions. ## Digitising old audio CDs on a Linux Server A number of people I know own a number of audio / music CDs. This is great, but unfortunately increasingly laptops aren't coming with an optical drive any more, which makes listening to said CDs challenging. To this end, making a digital copy to add to their personal digital music collections would be an ideal solution. Recently, I build a new storage NAS (which I'm still in the process of deciding on a filesystem for, but I think I might be going with btrfs + raid1), and the Fractal Design Node 804 case I used has a dedicated space for a slimline DVD writer (e.g. like the one you might find in a car). I've found this to be rather convenient for making digital copies of old audio CDs, and wanted to share the process by which I do it in case you'd like to do it too. To start, I'm using Ubuntu Server 20.04. This may work on other distributions too, but there are a whole bunch of packages you'll need to install - the names and commands for which you may need to convert for your distribution. To make the digital copies, we'll be using abcde. I can't find an updated website for it, but it stands for "A Better CD Encoder". It neatly automates much of the manual labor of digitising CDs - including the downloading of metadata from the Internet. To tidy things up after abcde has run to completion, we'll be using ffmpeg for conversion and eyeD3 for mp3 metadata manipulation. To get started, let's install some stuff! sudo apt install --no-install-recommends abcde sudo apt install ffmpeg mkcue eyed3 flac glyrc cdparanoia imagemagick Lots of dependencies here. Many of them are required by abcde for various features we'll be making use of. Next, insert the audio CD into the DVD drive. abcde assumes your DVD drive is located at /dev/sr0 I think, so if it's different you'll have to adjust the flags you pass to it. Once done, we can call abcde and get it to make a digital copy of our CD. I recommend here that you cd to a new blank directory, as abcde creates 1 subdirectory of the current working directory for each album it copies. When you're ready, start abcde: abcde -o flac -B -b Here, we call abcde and ask it to save the digital copy as flac files. The reason we do this and not mp3 directly is that I've observed abcde gets rather confused with the metadata that way. By saving to flac files first, we can ensure the metadata is saved correctly. The arguments above do the following: • -o flac: Save to flac files • -B: Automatically embed the album art into the saved music files if possible • -b: Preserve the relative volume differences between tracks in the album (if replaygain is enabled, which by default I don't think it is) It will ask you a number of questions interactively. Once you've answered them, it will get to work copying the audio from the CD. When it's done, everything should be good to go! However flac files can be large, so something more manageable is usually desired. For this, we can mass-convert our flac files to MP3. This can be done like so: find -iname '*.flac' -type f -print0 | nice -n20 xargs -P "$(nproc)" --null --verbose -n1 -I{} sh -c 'old="{}"; new="${old%.*}.mp3"; ffmpeg -i "${old}" -ab 320k -map_metadata 0 -id3v2_version 3 "${new}";'; There's a lot to unpack here! Before I do though, let's turn it into a bash function real quick which we can put in ~/.bash_aliases for example to make it easy to invoke in the future: # Usage: # flac2mp3 # flac2mp3 path/to/directory flac2mp3() { dir="${1}";
if [[ -z "${dir}" ]]; then dir="."; fi find "${dir}" -iname '*.flac' -type f -print0 | nice -n20 xargs -P "$(nproc)" --null --verbose -n1 -I{} sh -c 'old="{}"; new="${old%.*}.mp3"; ffmpeg -i "${old}" -ab 320k -map_metadata 0 -id3v2_version 3 "${new}";';
}

Ah, that's better. Now, let's deconstruct it and figure out how it works. First, we have a dir variable which, by default, is set to the current working directory.

Next, we use the one-liner from before to mass-convert all flac files in the target directory recursively to mp3. It's perhaps easier to digest if we separate it out int multiple lines:

find "${dir}" -iname '*.flac' -type f -print0 # Recursively find all flac files, delimiting them with NULL (\0) characters | nice -n20 # Push the task into the background xargs # for each line of input, execute a command --null # Lines are delimited by NULL (\0) characters --verbose # Print the command that is about to be executed -P "$(nproc)" # Parallelise across as many cores as the machine has
-n1 # Only pass 1 line to the command to be executed
-I{} # Replace {} with the filename in question
sh -c ' # Run this command
old="{}"; # The flac filename
new="${old%.*}.mp3"; # Replace the .flac file extension with .mp3 ffmpeg # Call ffmpeg to convert it to mp3 -i "${old}" # Input the flac file
-ab 320k # Encode to 320kbps, the max supported by ffmpeg
-map_metadata 0 # Copy all the metadata
-id3v2_version 3 # Set the metadata tags version (may not be necessary)
-c:v copy -disposition:v:0 attached_pic # Copy the album art if it exists
"${new}"; # Output to mp3 '; # End of command to be executed Obviously it won't actually work when exploded and commented like this, but hopefully it gives a sense of how it functions. I recommend checking that the album art has been transferred over. The -c:v copy -disposition:v:0 attached_pic bit in particular is required to ensure this happens (see this Unix Stack Exchange answer to a question I asked). Sometimes abcde is unable to locate album art too, so you may need to find and download it yourself. If so, then this one-liner may come in handy: find , -type f -iname '*.mp3' -print0 | xargs -0 -P "$(nproc)" eyeD3 --add-image "path/to/album_art.jpeg:FRONT_COVER:";

Replace path/to/album_art.jpeg with the path to the album art. Wrapping it in a bash function ready for ~/.bash_aliases makes it easier to use:

mp3cover() {
cover="${1}"; dir="${2}";

if [[ -z "${cover}" ]] || [[ -z "${dir}" ]]; then
echo "Usage:" >&2;
echo "    mp3cover path/to/cover_image.jpg path/to/album_dir";
return 0;
fi

find "${dir}" -type f -iname '*.mp3' -print0 | xargs -0 -P "$(nproc)" eyeD3 --add-image "\${cover}:FRONT_COVER:"
}

Use it like this:

mp3cover path/to/cover_image.jpg path/to/album_dir

By this point, you should have successfully managed to make a digital copy of an audio CD. If you're experiencing issues, comment below and I'll try to help out.

Note that if you experience any issues with copy protection (I think this is only DVDs / films and not audio CDs, which I don't intend to investigate), I can't and won't help you, because it's there for a reason (even if I don't like it) and it's illegal to remove it - so please don't comment in this specific case.

## Resizing Encrypted LVM Partitions on Linux

I found recently that I needed to resize some partitions on my new laptop as the Ubuntu installer helpfully decided to create only a 1GB swap partition, which is nowhere near enough for hibernation (you need a swap partition that's at least as big as your computer's RAM in order to hibernate). Unfortunately resizing my swap partition didn't allow me to hibernate successfully in the end, but I thought I'd still document the process here for future reference should I need to do it again in the future.

The key problem with resizing one's root partition is that you can't resize it without unmounting it, and you can't unmount it without turning off your computer. To get around this, we need to use a live distribution of Ubuntu. It doesn't actually matter how you boot into this - personally my preferred method is by using a multiboot USB flash drive, but you could just as well flash the latest ubuntu ISO to a flash drive directly.

Before you start though, it's worth mentioning that you really should have a solid backup strategy. While everything will probably be fine, there is a chance that you'll make a mistake and wind up loosing a lot of data. My favourite website that illustrates this is The Tao of Backup. Everyone who uses a computer (technically minded or not) should read it. Another way to remember it is the 3-2-1 rule: 3 backups, in 2 locations, with 1 off-site (i.e. in a different physical location).

Anyway, once you've booted into a live Ubuntu environment, open the terminal, and start a root shell. Your live distribution should come with LUKS and LVM already, but just in case it doesn't execute the following:

sudo apt update && sudo apt install -y lvm2 cryptsetup

I've talked about LVM recently when I was setting up an LVM-managed partition on an extra data hard drive for my research data. If you've read that post, then the process here may feel a little familiar to you. In this case, we're interacting with a pre-existing LVM setup that's encrypted with LUKS instead of setting up a new one. The overall process look a bit like this:

With this in mind, let's get started. The first order of business is unlocking the LUKS encryption on the drive. This is done like so:

sudo modprobe dm-crypt
sudo cryptsetup luksOpen /dev/nvme0n1p3 crypt1

The first command there ensures that the LUKS kernel module is loaded if it isn't already, and the second unlocks the LUKS-encrypted drive. Replace /dev/nvme0n1p3 with the path to your LVM partition - e.g. /dev/sda1 for instance. The second command will prompt you for the password to unlock the drive.

It's worth mentioning here before continuing the difference between physical partitions and LVM partitions. Physical partitions are those found in the partition table on the physical disk itself, that you may find in a partition manage like GParted.

LVM partitions - for the purpose of this blog post - are those exposed by LVM. They are virtual partitions that don't have a physical counterpart on disk and are handled internally by LVM. As far as I know, you can't ask LVM easily where it stores them on disk - this is calculated and managed automatically for you.

In order to access our logical LVM partitions, the next step is to bring up LVM. To do this, we need to get LVM to re-scan the available physical partitions since we've just unlocked the one we want it to use:

sudo vgscan --mknodes

Then, we activate it:

sudo vgchange -ay

At this point, we can now do our maintenance and make any changes we need to. A good command to remember here is lvdisplay, which lists all the available LVM partitions and their paths:

sudo lvdisplay

In my case, I have /dev/vgubuntu/root and /dev/vgubuntu/swap_1. tldr-pages (for which I'm a maintainer) has a number of great LVM-related pages that were contributed relatively recently which are really helpful here. For example, to resize a logical LVM partition to be a specific size, do something like this:

sudo lvresize -L 32G /dev/vgubuntu/root

To extend a partition to fill all the remaining available free space, do something like this:

sudo lvextend -l +100%FREE /dev/vgubuntu/root

After resizing a partition, don't forget to run resize2fs. It ensures that the ext4 filesystem on top matches the same size as the logical LVM partition:

sudo resize2fs /dev/vgubuntu/root

In all of the above, replace /dev/vgubuntu/root with the path to your logical LVM partition in question of course.

Once you're done making changes, we need to stop LVM and close the LUKS encrypted disk to ensure all the changes are saved properly and to avoid any issues. This is done like so:

sudo vgchange -an
sudo cryptsetup luksClose crypt1

With that, you're done! You can now reboot / shutdown from inside the live Ubuntu environment and boot back into your main operating system. All done!

Found this helpful? Encountering issues? Comment below! It really helps my motivation.

Art by Mythdael