Tykky

Tykky is a set of tools which wrap installations inside an Apptainer/Singularity container to improve startup times, reduce IO load, and lessen the number of files on large parallel filesystems.

Intro

This is a tool to create installations using existing containers. The basic idea is to install software through a container, convert this into a filesystem image and mount this filesystem image when running the container.

The main goal is to reduce the number of files on disk, and reduce the IO load when installations are started. If you are not running on a parallel filesystem with a lot of users and load, the points might not be that relevant. Only tested and developed on Lustre so benefits might be different on other parallel filesystems

The tool originally started as a way to package conda installations using container, as they cause a significant load on the filesystem. The idea being that using the tool should be very simple and as similar as possible to an un-containerized installation (drop in replacement for the majority of cases). This means that we try to hide the container as much as possible from the end-user.

It's singularity based, but nothing inherently prohibits usage of some other runtime (granted singularity is quite hardcoded atm ). All which is needed is the ability to mount filesystem images and control over bind mounts

Design choices

Containers are used for two main things:

• Automatic mounting and demounting of filesystem-image
• Per process private (mount) namespace

From the point of view of the parallel filesystem, the image just looks like one single file -> much less load on the parallel filesystem. (I'm not a Lustre expert so I don't know if it's more the OST,OSS or MDT being saved) The image could be mounted using other tools, but then we would have to keep track of unmounting it all kinds of error handling -> things we get for free using a container. The private namespaces means that we don't have to worry about conflicts between multiple users, finding folders where to mount or breaking software which does not want to be moved.

Existing containers are used as this provides an easier way to interface with the host software environment and a user does not have to have singularity build access on the HPC machine ( user namespaces might be temporarily disabled on a system due to security reasons ).

The tool generates a lot of wrappers with some relatively nasty tricks. This is so that most things which should work without a container works within the container and the installation looks like a normal installation to the end-user

The tool is also explicitly meant to allow intertwining with the host software environment. For this there are two basic modes of operation:

1. Mount everything from the host

• All host paths will be mounted, used when it makes sense and compatibility can be assumend
• Internally there are some additional variables so exclude paths
• Note! due to this the default container should always be the same as the host system.

2. Mount specified defaults

• defaults set in config

Current version of the tools is written using bash + python. At some point it could be worthwile to rewrite the whole thing in some language which can be statically compiled for maximum robustness e.g GO/rust/C++ or whatever.

Limitations

What things break / work differently when compared to a normal installation

• ssh commands will drop you out of the container, there is a fix for this, but then some pre commands have to be run to start any required ssh services
• you can't start other containers (singularity can not be nested), Ugly hack is to ssh to localhost, but that makes environment management tricky and requires sshd to be running on the current node.
• Resolving binary paths will result in paths which do not exist outside the container. As the image is mounted on a directory which is not present on the host. Bind mounts are always applied after the image mount which means an image mount can not mask a directory on disk, without us dropping the whole preceeding path from the mount point list. There is a fix for this as a PR for apptainer (as of 1.2.2022) but we do not rely on this as the future is unclear if singularityCE or apptainer will become dominant. The workaround is to mount all directories on the same level as each component of the image mount path -> possibly very expensive -> not done automatically.
• A bit untested, but running one container per core when you have 128 of them can lead to the compute node feeling a bit unwell.

Basic program structure

Starting from command invocation Users will use commands under bin

1. bin files are symlinks to frontends/containerize
2. containerize is the main script which runs all the steps and is responsible for cleanup
3. Based on the used symlink different a corresponding python script is going to be called from frontends
4. This frontend parses the user input and sets a lot of tool specific defaults.
   • The python interpreter used is hardcoded during the tools installation.
   • A user config is created
5. The user config and the default config are both passed to construct.py
   • The default config has been defined during installation
   • Some values are overridable other are set.
   • The construct will produce a _vars.sh file which will be sources by subsequent steps
   • Current handling of environment variables in config is not standardized. pre_install,post_install and extra_envs will not be expanded in any way. build_tmpdir_base will be expanded and checked to be a valid directory during config construction. The rest will be expanded using os.path.expandvars note that this will leave unset variables as is.
   • All non-special variables from the yaml will be uppercased, prefixed with CW_ and dumped to the _vars.sh arrays are turned to bash arrays.
6. containersize makes sure that the installation dir exist.
7. pre.sh Fetch container either by downloading or copying from disk. When modifying installations, will also copy the squashfs image
8. create_inst Run installation script through the container based on some template in templates, after which the installation is compressed into a squashfs image.
   • The installation can be isolated or mount the complete host filesystem.
   • When modifying an existing installation, the whole installation has to be copied wich might take a while
9. generate_wrappers (This is where most tricks live) Generate wrappers for the installation so that they can be used as normal installations. The wrappers:
   • Defines common variables such as image name, container name
   • Defines runtime bind mounts
   • Unset singularity envs if not actually inside a container (e.g srun called from container -> some SINGULARITY are still active)
   • Extra symlink layer in _bin to tricks the likes of dask to generate valid executable paths
   • Copy venv definition when wrapping python venv
   • Activates conda if a conda env is wrapped
   • set executable argv0 to enable python virtual envs.
10. post.sh
    • Copy build files to final installatio file
    • Save used build files to <install_dir>/share

NOTE

Permissions for installation files are determined by the current umask and permissions for the target installation folder! Files inside the the squashfs are set to world readable to allow copying when installations are updated by other that the original creator. Limit access by setting correct permissions on on the sqfs image itself. This behavior can be disabled by setting CW_NO_FIX_PERM

BASH MAGIC

/usr/bin/singularity --silent exec -B $DIR/../$SQFS_IMAGE:$INSTALLATION_PATH:image-src=/ $DIR/../$CONTAINER_IMAGE  bash -c "eval \"\$(/CSC_CONTAINER/miniforge/bin/conda shell.bash hook )\"  && conda activate env1 &>/dev/null &&  exec -a $_O_SOURCE $DIR/python $( test $# -eq 0 || printf " %q" "$@" )"

• exec -a is there to enable creating virtual environments as otherwise the venv symlink -> tykky wrapper -> executable in container chain is broken and python does not consider itself to be a venv.
• bash -c is required when conda is involved as we have to initialize the environment for some commands to work properly. Also partially due to exec being a builtin instead of a binary.
• $( test $# -eq 0 || printf " %q" "$@" ) without printf special characters will not be escaped correctly and the command will error out. printf will print an empty string '' if no arguments so we need to be quiet in that case.

Implemented Frontends

• conda-containerize
• Wrap new conda installation or edit existing
• requires a conda YML file as input
• pip-containerize
• Wrap new venv installation or edit existing
• Will by default use currently available python
• Option to also use slim container image (will then not mount full host)
• wrap-container
• Generate wrappers for existing container. Mainly so that applications in existing containers can be used "almost" as a normal installation.
• Full host will not be mounted
• wrap-install
• Wrap an installation on disk to a container.
• Useful for containerizing existing installations which can not be re-installed
• Option to mount in exact place, so that external and internal paths are identical. This will however require dropping the top parent path mount so only works when no dependencies required. E.g wrap-install --mask -w bin /appl/soft/prog --prefix Dir will not mount /appl at all. Understand the implications of this before using this frontend. For manual workaround and more explanation see limitations section.

All tools support -h/--help for displaying info some have subcommands.

Examples

• conda-containerize new --prefix /path/to_install conda_env.yaml

  • Where conda_env.yaml

  channels:
    - conda-forge
  dependencies:
    - numpy
  

• conda-containerize update --post-install post.sh /path/to_install

  • Where post.sh

  conda install scipy  --channel conda-forge
  pip install pyyaml 
  

• pip-containerize new --prefix /path/to_install req.txt

  • Where req.txt

  numpy 
  

• wrap-container --wrapper-paths /opt/prog/bin --prefix /path/to_install /path/to/container

• wrap-install --wrapper-paths bin --mask --prefix /path/to/install /program/on/disk

Installation

Preferably use system python + pip and run install.sh with the desired config as argument. Available configs are in configs folder

bash install.sh <config>

This will symlink the config to default_config, install pyyaml locally in the repository and hardcode the used python interpreter. This is so that the tool can be used to construct environments which use a completely different python.

If you are not satisfied with the config you can simply edit the config under default_config or supply a custom config file path using CW_GLOBAL_YAML.

Special vars

These can be set before starting the tool

CW_GLOBAL_YAML path to config to use

CW_ENABLE_CONDARC enable user condarc during installation

CW_DEBUG_KEEP_FILES Don't delete build files when failing.

CW_FORCE_CONDA_ACTIVATE Force conda to be activated even if called through a virtual environment.

CW_LOG_LEVEL How verbosely to report program actions

• 0 only error
• 1 only warnings
• 2 general (default)
• >2 debug

Activating and Deactivating wrapped environments

A tykky convenience shell function is provided to mimic the conda activate and deactivate helpers. To use it, you must load those functions into your shell with:

source etc/profile.d/tykky

Then you may activate a tykky installation with

tykky activate <env_dir>

If you define the environment variable TYKKY_PATH, environments may also be found by name inside that colon-separated list of paths in TYKKY_PATH.

You may deactivate the tykky environment in your shell with:

tykky deactivate

Alternatively, you may also manually add <env_dir>/bin to your $PATH.

Misc features ideas

• Keep container name based on src name

Notes

SINGULARITY_BIND handled after -B ordering within both matter! -> nested bind mounts possible. Note that while loop devices can be mounted on bind mounts, any extra bind mounts will be applied after extra loop device (image mounts) so to mask dirs on disk with an image mount, the path can not be bind mounted. (exception is a default $HOME mount, which is applied before loop device mounts). Note that this has been fixed in apptainer and you can now apply image mounts over bind mounts.

Convoluted path modifications in py scripts

The idea is that everything works even if a completely different python environment is active, we also avoid having any extra envs set while parsing the conf to allow for very "creative" usages of the tool

wrap-install

Technically updating masked disk installations is not an issue, but let's not do that until there is a specific request. The tool now drops the full path leading to the target from the bind list, if more binds are needed a yaml input needs to be constructed.