Inline conda queue environments for Deadline Cloud customer-managed fleets
The samples repository includes the following inline conda queue
environments that run conda directly instead of using the
conda-queue-env-enter command:
- conda_queue_env_inline.yaml
-
Has nearly the same behavior as the console conda queue environment but runs conda directly. The behavior is to create a new conda virtual environment for every Open Job Description session that runs on a worker host, then delete the environment when the session completes. Conda keeps a cache of downloaded packages so it doesn't repeatedly re-download applications, but each session has the overhead of linking packages into the virtual environment.
Unlike the console queue environment, which uses
strictchannel priority, this inline queue environment usesflexiblechannel priority. - conda_queue_env_inline_improved_caching.yaml
-
Extends the inline conda queue environment with a mechanism to reuse conda virtual environments across multiple jobs. The default environment name uses the hash of the conda channels and packages, or you can explicitly set the name in the job. A parameter controls how long to use an environment before running a package update, so that activating a reused environment usually takes seconds.
To use these queue environments on customer-managed fleets, install
conda on the worker hosts (for example, in your AMI) and configure
conda activate to work in non-interactive bash shells. The
samples
README
