vac:dst:ift:2025q2-dst-tooling
Description
We will create tools to help DST efficiency. These tools can be composed of utilities for Kubernetes, or any other kind that fits the necessities of DST and other projects. As projects might share common necessities, this tasks will be considered as a scaffold for DST tools, adapting the tools for each project if it needs. Among tools that can be useful, we consider deployment utilities to facilitate the launch of experiments, general log parser for project analysis, and any other kind of utilities that may appear depending on the needs of the projects.
Background
Narratives
These efforts will support the Conduit of Expertise narrative by accelerating DST/IFT Improvements, providing measurable insights to enhance developer experience within and beyond the IFT ecosystem. Also, ideally these tools can be shared across projects, reinforcing cross project collaboration.
Task list
Python deployment scaffold
- fully qualified name:
vac:dst:ift:2025q2-dst-tooling:python-deployment-scaffold - owner: Pearson
- status: 0%
- start-date: 2025/05/12
- end-date: 2025/05/23
Description
Design and code an initial structure to create deployments in a Kubernetes environment with Python. Taking as initial example nWaku deployments in bash, create a system where statefulset can be deployed and controlled/configured easily. Take into account that this should remain a general tool, considering other kind of deployments (PODs) with any other pieces of software that might run inside. This should substitute the usage of bash scripts, allowing a better configuration and usability. Note that the deployment/s should also be controlled by the user if required, in the future. Apart from the configuration of the deployment, it should be considered a way to continue the workflow with the next steps of the experiments (scraping and plotting). If possible, adapt this to be able to run it from inside and outside the cluster.
Deliverables
- PRs:
- Related Documents: