How ryuk132/openkube-optimizer works
OpenKube Optimizer is a planned, read-only Kubernetes resource analysis CLI. Its intended workflow is to inspect explicitly named namespaces, compare workload CPU/memory allocations with recent utilization, and present explainable findings for human review. Currently, only immutable domain records and bounded quantity conversion are implemented; there is no CLI, Kubernetes access, analysis engine, or reporting. Planned stages below reflect README scope, not inspected runtime code.
Main entry points: openkube_optimizer Local CLI · models.py Domain records · quantities.py Quantity conversion
Components 11
Implemented domain
- Domain records
src/openkube_optimizer/domain/models.py - Quantity conversion
src/openkube_optimizer/domain/quantities.py
Planned analysis workflow
- Local CLI
src/openkube_optimizer - Namespace discovery
src/openkube_optimizer - Workload discovery
src/openkube_optimizer - Metrics collection
src/openkube_optimizer - Evidence analysis
src/openkube_optimizer
Planned recommendations and reports
- Investigation guidance
src/openkube_optimizer - Terminal and JSON reports
src/openkube_optimizer
Other components
- Engineer
- Kubernetes cluster
Connections 10
- Engineer → Local CLI: invokes
README.md - Local CLI → Namespace discovery: selects namespaces
README.md - Namespace discovery → Workload discovery: scopes discovery
README.md - Workload discovery → Kubernetes cluster: reads resources
README.md - Metrics collection → Kubernetes cluster: reads utilization
README.md - Local CLI → Metrics collection: requests metrics
README.md - Domain records → Quantity conversion: validates quantities
src/openkube_optimizer/domain/models.py - Evidence analysis → Domain records: uses facts
README.md - Evidence analysis → Investigation guidance: explains findings
README.md - Local CLI → Terminal and JSON reports: emits reports
README.md