TARDIS - The Transparent Adaptive Resource Dynamic Integration System
Welcome to the TARDIS documentation!
TARDIS resource manager is available via PyPI, so you can use
pip to install
TARDIS and all its dependencies.
python3 -m pip install cobald-tardis
Configuration of COBalD
In order to run
COBalD configuration is needed. Details about the available options and syntax can
be found in the COBalD component configuration documentation.
The pools to be
TARDIS are created by a factory function
create_composite_pool(), which is registered as a
COBalD YAML plugin
and, therefore, can be included using the
!TardisPoolFactory YAML tag.
pipeline: # Makes decision to add remove resources based utilisation and allocation - !LinearController low_utilisation: 0.90 high_allocation: 0.90 rate: 1 # Limits the demand for a resource - !Limiter minimum: 1 # Log changes - !Logger name: 'changes' # Factory function to create composite resource pool - !TardisPoolFactory configuration: 'tardis.yml'
Configuration of TARDIS
In addition to the above mentioned
COBalD configuration a
TARDIS configuration is necessary as well,
which is provided to the factory function
its configuration parameter.
TARDIS YAML configuration supports the following sections:
Configuration of the Plugins to use (see Plugins)
The overlay batch system to use (see BatchSystemAdapter)
List of sites to create (see Generic Site Configuration)
Configuration options for each site (see Generic Site Configuration)
Plugins: SqliteRegistry: db_file: drone_registry.db BatchSystem: adapter: FakeBatchSystem allocation: 1.0 utilisation: !PeriodicValue period: 3600 amplitude: 0.5 offset: 0.5 phase: 0. machine_status: Available Sites: - name: Fake adapter: FakeSite quota: 8000 # CPU core quota Fake: api_response_delay: !RandomGauss mu: 0.1 sigma: 0.01 resource_boot_time: !RandomGauss mu: 60 sigma: 10 MachineTypes: - m1.infinity MachineTypeConfiguration: m1.infinity: MachineMetaData: m1.infinity: Cores: 8 Memory: 16 Disk: 160
Alternatively a unified
TARDIS configuration can be used. In this case, the
part of the configuration is represented by a
In case of the unified configuration you can currently not use the yaml tag
!TardisPoolFactory to initialize
the pool factory, please use the COBalD legacy object initialisation
__type__: tardis.resources.poolfactory.create_composite_pool instead!
pipeline: # Makes decision to add remove resources based utilisation and allocation - !LinearController low_utilisation: 0.90 high_allocation: 0.90 rate: 1 # Limits the demand for a resource - !Limiter minimum: 1 # Log changes - !Logger name: 'changes' # Factory function to create composite resource pool - __type__: tardis.resources.poolfactory.create_composite_pool tardis: Plugins: SqliteRegistry: db_file: drone_registry.db BatchSystem: adapter: FakeBatchSystem allocation: 1.0 utilization: !PeriodicValue period: 3600 amplitude: 0.5 offset: 0.5 phase: 0. machine_status: Available Sites: - name: Fake adapter: FakeSite quota: 8000 # CPU core quota Fake: api_response_delay: !RandomGauss mu: 0.1 sigma: 0.01 resource_boot_time: !RandomGauss mu: 60 sigma: 10 MachineTypes: - m1.infinity MachineTypeConfiguration: m1.infinity: MachineMetaData: m1.infinity: Cores: 8 Memory: 16 Disk: 160
Start-up your instance
To start-up your instance you can run the following command:
python3 -m cobald.daemon cobald.yml
However, it is recommended to start
COBalD using systemd as decribed in the
COBalD Systemd Configuration documentation.
Running your instance in Docker
For your convenience and to try out
TARDIS ready to use docker containers are provided via Dockerhub.
To start a demo setup managing fake resources and a fake batch system simply run the following command.
docker run matterminers/cobald-tardis:latest
To run your own
TARDIS configuration you can run the following command.
docker run --mount type=bind,source=</your_path/cobald.yml>,target=/srv/cobald.yml matterminers/cobald-tardis:latest
To use the Sqlite Database to persistently store the state of your resources you can export an entire path to the container by running the following command.
docker run -v </your_path>:/srv matterminers/cobald-tardis:latest
This path must contain a valid cobald.yml file. The persistent database will then be stored on the local machine.
Running your instance using HTCondor as overlay batch system in Docker
For your convenience and for systems without pre-compiled HTCondor support a ready to use docker container is provided via Dockerhub.
You can configure
TARDIS as described in this documentation and bind mount the directory containing
the configuration into the containers /srv directory.
This path must contain at least a valid cobald.yml file.
docker run -v $PWD/configuration:/srv matterminers/cobald-tardis-htcondor:latest
HTCondor Token Support
Starting with the production release series 9.0, HTCondor introduces a new security configuration, which is no longer host-based. The security configuration is now user-based and requires authentication to access the HTCondor pool. This is also true for read-only operations such as condor_status. Therefore, this docker image supports the IDTOKENS authentication method introduced with the HTCondor 9.0 series.
In order to use ID tokens, add any tokens provided by the operator of the overlay batch system to a tokens.d directory and bind mount it to /etc/condor/tokens.d. HTCondor is automatically using them to authenticate against the pool.
docker run -v $PWD/configuration:/srv -v $PWD/tokens.d:/etc/condor/tokens.d matterminers/cobald-tardis-htcondor:latest
TARDIS uses the condor_status command, the token added needs at least the ALLOW_READ
privilege to access the HTCondor Collector and to query the status of resources.
TARDIS uses the condor_drain command to release under utilized resources.
Therefore, a second token to access the HTCondor StartD of the Drone is needed.
Usually, both tokens are provided by the operator of the HTCondor overlay batch system.