- Create an automated L0-support-like analytics solution for supportconfig data that is tiered across a customer's environment and SUSE environment (similar to a very modular AIOps Edge-Core approach). A pictorial overview of the ecosystem
- Monitor aspect (lower right) - Start data pipeline with trigger/hint/clue based collection of system's information (like supportconfig) plus some change-centric metadata, then aggregate for step-wise run analysis tool(s) to provide time-series observations and potential/suggested actions, all within the local environment.
- Analyzer aspect (middle and upper left): Create models from existing supplied data to provide "Nearest Neighbor" analysis to determine whether a submitted/collected dataset (supportconfig) looks like a current cert, SR, or bug.
Goals for this Hackweek
- Continue to collect more example data submissions for testing
- Iterate (and further automate) model and training dataset creation
- Iterate data/model version control and regression testing
- Augment more hint/clue modules to trigger data collection
- Iterate (and multi-package as RPM/containers) all components
- Iterate (and test) the customer side of data pipeline, adding time-series checks
- Be able to PoC demo an end-to-end usage of the above ecosystem
- Monitoring (mostly bash-centric)
- Analyzer (mostly python-centric)
- Peer review (customer, partner, support) of PoC demo
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This project is part of:
Hack Week 20
This project is one of its kind!