Add storage-fsx-windows-sla-optimizer skill - #72
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Read-only SLA-readiness, availability, and cost review of Amazon FSx for Windows File Server across seven dimensions (deployment type, Active Directory health, throughput, storage headroom, backups, maintenance window, alarms), with usage-pattern trend analysis and a cost-optimization lens. Single- and multi-file-system (fleet) reviews route automatically. Fully covered by AIDevOpsAgentAccessPolicy; no additional IAM. Includes evals (16 functional cases + 8 trigger queries + fixtures) and updates llms.txt.
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Description
Adds a new read-only skill,
storage-fsx-windows-sla-optimizer, that performs astructured SLA-readiness and availability review of Amazon FSx for Windows File Server
file systems and surfaces cost-optimization opportunities.
Given one or more file-system IDs (or a region to discover them in), it evaluates each
file system across seven availability dimensions — deployment type (Single-AZ vs
Multi-AZ), Active Directory health, throughput capacity (peak-aware), storage headroom,
backups, maintenance window, and CloudWatch alarm coverage — and returns a rated report
(High / Medium / Low / Indeterminate) with prioritized findings and remediation. It adds
usage-pattern trend analysis (peak-aware throughput sizing, weekday/weekend profile, and
storage-growth projection) and flags heavily over-provisioned or idle capacity as 💰
advisory cost notes that never lower the SLA rating. Single- vs multi-file-system (fleet)
reviews route automatically by count.
The skill is strictly read-only: control-plane
Describe*/GetMetricDatacalls only, noSMB/data-plane access, no mutating operations. It is fully covered by the
AIDevOpsAgentAccessPolicymanaged policy and needs no additional IAM.Type of change
Testing
Validated two complementary ways.
1. Agent Skill Eval (
aws-samples/sample-agent-skill-eval) — the skill shipsevals/(16 functional cases + 8 trigger queries + mock fixtures) and a.skilleval.yaml.(with-skill ~92–98% across runs; without-skill ~70%). Includes fixture-based cases for
the trend engine (weekday-peaker, idle, storage-filler) and a MISCONFIGURED / Critical
AD case (
with=100% / without=0%).including deliberate near-miss negatives (S3 cost question; FSx for NetApp ONTAP).
default
claudeCLI was unavailable, so a pluggable runner was used). Token/tool-callmetadata isn't emitted by that runner, so the eval's process/efficiency sub-scores read
as 0; the outcome/style/trigger dimensions and the with/without delta are unaffected.
2. Manual AWS DevOps Agent testing — the skill was uploaded to an AgentSpace and run
against real FSx for Windows infrastructure (a purpose-built test fleet). Confirmed live:
a Medium multi-warning case, a High case (after adding alarm coverage), the 💰
cost-optimization lens on an over-provisioned file system, and a multi-file-system fleet
review (distribution summary + comparison matrix). The Critical/MISCONFIGURED path is
covered by the fixture-based eval case above (a live MISCONFIGURED state was not forced,
as FSx does not reliably flip lifecycle from network isolation alone).
llms.txtis updated with the skill entry. The auto-generated Skills Catalog picks theskill up from its SKILL.md frontmatter (
aws-devops-agent-skills.*metadata), so nomanual README table edit is required.
License confirmation