model-serving-kubernetes

model-serving-kubernetes is an MLOps & model serving skill for AI agents, published by BagelHole in the DevOps-Security-Agent-Skills repository on GitHub. Skillspace rates model-serving-kubernetes D (65/100) and it passed the safety scan; the rating is based on static analysis only.

Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. Includes canary deployments, autoscaling, model versioning, A/B testing, and GPU resource management for production model serving.

Grade
D
Quality
65 / 100
Safety
Passed
GitHub stars
1,090

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubBagelHole/DevOps-Security-Agent-Skills

Our review

Architecture
90 / 100
Maturity
Basic: a single SKILL.md
Security scan
Low-risk patterns
License
Not declared. Check the repository before reusing it.

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Category is a classifier prediction; no model has read this skill yet
  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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