mlops-model-serving
0
总安装量
1
周安装量
安装命令
npx skills add https://github.com/kentoshimizu/sw-agent-skills --skill mlops-model-serving
Agent 安装分布
amp
1
cline
1
opencode
1
cursor
1
continue
1
kimi-cli
1
Skill 文档
Mlops Model Serving
Overview
Use this skill to deploy models with predictable latency/error behavior and controlled rollout risk.
Scope Boundaries
- Use this skill when the task matches the trigger condition described in
description. - Do not use this skill when the primary task falls outside this skill’s domain.
Shared References
- Serving SLO and rollout rules:
references/serving-slo-and-rollout-rules.md
Templates And Assets
- Serving readiness checklist:
assets/serving-readiness-checklist.md
Inputs To Gather
- Serving topology and traffic profile.
- Latency/error SLO and error budget constraints.
- Rollout strategy and rollback capability.
- Observability and incident response expectations.
Deliverables
- Serving architecture and rollout plan.
- SLO-aligned guardrails and alert thresholds.
- Readiness evidence and rollback criteria.
Workflow
- Define serving constraints and topology.
- Apply
references/serving-slo-and-rollout-rules.mdfor rollout policy. - Validate readiness with
assets/serving-readiness-checklist.md. - Execute staged rollout and monitor guardrails.
- Publish serving decision and residual risk ownership.
Quality Standard
- Serving SLOs are measurable and enforced.
- Rollout blast radius is controlled.
- Rollback decisions are objective and fast.
Failure Conditions
- Stop when serving cannot meet latency/reliability targets.
- Stop when rollback path is unverified.
- Escalate when rollout risk exceeds policy thresholds.