We are kindly requesting classic confinement for daisytuner-cli:
- name: daisytuner-cli
- description: Daisytuner is a platform for continuous benchmarking and continuous tuning. With integrations into Gitlab and GitHub, users can continuously track the performance of classical software applications and neural networks. With the daisytuner-cli, we provide several command line tools to set up self-hosted runners for performance measurements on the users’ local machines.
- snapcraft: PRIVATE
- upstream: PRIVATE
- upstream-relation: Owner and maintainer. Verified Publisher.
- supported-category: public cloud agent / HPC orchestration
- reasoning: The cli tools install a cloud runner as a system daemon. When registered by the user with the platform (token-based), the runner listens for benchmarking jobs triggered by developers of the user via GitHub/GitLab. The runner executes those jobs by building and executing a docker image with several tools mounted into the container. This includes the system’s docker installation, devices (GPUs, TPUs, etc.), drivers (CUDA, ROCm, compilers), performance profiling tools (perf, py-spy, nvidia nsights), and special registers (MSR). The system must be set up by the user following our documentation on-premise.
I understand that strict confinement is generally preferred over classic.
I’ve tried the existing interfaces to make the snap to work under strict confinement.
Note that snappy-debug can be used to identify possible required interfaces. See Debugging snaps | Snapcraft documentation for more information.