跳到正文
cccskills
免费在 GitHub 公开

managing-aws-fsx

Use when working with Aws Fsx — aWS FSx file system management and health analysis. Covers FSx for Lustre, Windows File Server, NetApp ONTAP, and OpenZFS file systems, volumes, backups, data repository associations, and storage capacity metrics. Use when inspecting FSx file systems, debugging performance issues, reviewing backup configurations, or analyzing storage utilization.

中文简介正在准备中。当前显示原文说明。

集成工具AWS
查看安装方法

包含的文件(1)

  • SKILL.md5.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

AWS FSx Management Skill

Analyze and manage AWS FSx file systems across all types (Lustre, Windows, ONTAP, OpenZFS).

MANDATORY: Discovery-First Pattern

Always list file systems before querying specific resources.

Phase 1: Discovery

#!/bin/bash
export AWS_PAGER=""

echo "=== FSx File Systems ==="
aws fsx describe-file-systems --output text \
  --query 'FileSystems[].[FileSystemId,FileSystemType,Lifecycle,StorageCapacity,StorageType,DNSName]' | head -20

echo ""
echo "=== FSx Volumes ==="
aws fsx describe-volumes --output text \
  --query 'Volumes[].[VolumeId,Name,VolumeType,Lifecycle,FileSystemId]' 2>/dev/null | head -20

echo ""
echo "=== Storage Virtual Machines (ONTAP) ==="
aws fsx describe-storage-virtual-machines --output text \
  --query 'StorageVirtualMachines[].[StorageVirtualMachineId,Name,Lifecycle,FileSystemId]' 2>/dev/null | head -15

Phase 2: Analysis

#!/bin/bash
export AWS_PAGER=""

END_TIME=$(date -u +"%Y-%m-%dT%H:%M:%S")
START_TIME=$(date -u -d "7 days ago" +"%Y-%m-%dT%H:%M:%S" 2>/dev/null || date -u -v-7d +"%Y-%m-%dT%H:%M:%S")

echo "=== File System Details ==="
for fs_id in $(aws fsx describe-file-systems --output text --query 'FileSystems[].FileSystemId'); do
  aws fsx describe-file-systems --file-system-ids "$fs_id" --output text \
    --query 'FileSystems[].[FileSystemId,FileSystemType,StorageCapacity,Lifecycle,SubnetIds[0],VpcId]' &
done
wait

echo ""
echo "=== FSx Backups ==="
aws fsx describe-backups --output text \
  --query 'Backups[].[BackupId,FileSystemId,Type,Lifecycle,CreationTime]' | head -15

echo ""
echo "=== Data Repository Associations (Lustre) ==="
aws fsx describe-data-repository-associations --output text \
  --query 'Associations[].[AssociationId,FileSystemId,Lifecycle,DataRepositoryPath,FileSystemPath]' 2>/dev/null | head -10

echo ""
echo "=== Data Repository Tasks ==="
aws fsx describe-data-repository-tasks --output text \
  --query 'DataRepositoryTasks[:5].[TaskId,FileSystemId,Lifecycle,Type,StartTime]' 2>/dev/null

echo ""
echo "=== Storage Metrics ==="
for fs_id in $(aws fsx describe-file-systems --output text --query 'FileSystems[].FileSystemId'); do
  {
    free_storage=$(aws cloudwatch get-metric-statistics --namespace AWS/FSx --metric-name FreeStorageCapacity \
      --dimensions Name=FileSystemId,Value="$fs_id" \
      --start-time "$START_TIME" --end-time "$END_TIME" --period 604800 --statistics Average \
      --output text --query 'Datapoints[0].Average')
    printf "%s\tFreeStorage:%s\n" "$fs_id" "${free_storage:-N/A}"
  } &
done
wait

echo ""
echo "=== File System Tags ==="
for fs_id in $(aws fsx describe-file-systems --output text --query 'FileSystems[].FileSystemId'); do
  aws fsx describe-file-systems --file-system-ids "$fs_id" --output text \
    --query "FileSystems[].Tags[?Key!='aws:cloudformation:stack-id'].[\"$fs_id\",Key,Value]" 2>/dev/null &
done
wait | head -15

Output Format

  • Target ≤50 lines per output
  • Use --output text --query for all commands
  • Tab-delimited fields: FileSystemId, Type, StorageCapacity, Lifecycle
  • Convert storage values to GB/TB with awk when appropriate
  • Never dump full file system configurations -- extract key fields only

Anti-Hallucination Rules

  1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
  2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
  3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
  4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
  5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

ShortcutCounterWhy
"I'll skip discovery and check known resources"Always run Phase 1 discovery firstResource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"Follow the full discovery → analysis flowQuick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"Audit configuration explicitlyDefaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"Always check relevant metrics when availableAPI/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"Try the command and report the actual errorAssumed permission failures prevent useful investigation; actual errors are informative

Common Pitfalls

  • File system types: LUSTRE, WINDOWS, ONTAP, OPENZFS -- each has different APIs and metrics
  • Lifecycle states: AVAILABLE, CREATING, FAILED, DELETING, MISCONFIGURED, UPDATING -- only AVAILABLE is healthy
  • ONTAP volumes: ONTAP uses SVMs and volumes -- query volumes separately from file systems
  • Lustre S3 integration: Data repository associations link Lustre to S3 -- check association lifecycle
  • Storage capacity: FSx for Windows and ONTAP support storage capacity scaling -- check AdministrativeActions
  • Backup types: AUTOMATIC (scheduled), USER_INITIATED, AWS_BACKUP -- check retention policies
  • Throughput capacity: Separate from storage -- can be scaled independently on Windows and ONTAP
  • Multi-AZ: Windows File Server supports Multi-AZ -- check DeploymentType (SINGLE_AZ vs MULTI_AZ)

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.

中文简介正在准备中。当前显示原文说明。

cloudthinker-ai/CloudSkills62026年4月5日 更新

Use when working with Alloydb — google AlloyDB instance analysis, query insights, columnar engine optimization, maintenance windows, and cluster health.

中文简介正在准备中。当前显示原文说明。

cloudthinker-ai/CloudSkills62026年4月5日 更新

Use when working with Aqua — aqua Security platform analysis. Covers container runtime protection, image assurance policies, compliance frameworks, vulnerability management, workload protection, and registry scanning. Use when analyzing container security posture, reviewing image compliance, investigating runtime alerts, or auditing security policies.

中文简介正在准备中。当前显示原文说明。

cloudthinker-ai/CloudSkills62026年4月5日 更新

Use when working with Bigquery — google BigQuery job analysis, slot utilization, cost analysis, dataset management, and query optimization.

中文简介正在准备中。当前显示原文说明。

cloudthinker-ai/CloudSkills62026年4月5日 更新

Use when working with Cassandra — apache Cassandra keyspace analysis, compaction strategies, repair status, nodetool operations, and cluster health monitoring.

中文简介正在准备中。当前显示原文说明。

cloudthinker-ai/CloudSkills62026年4月5日 更新

Use when working with Checkov — checkov infrastructure-as-code security scanning. Covers Terraform, CloudFormation, Kubernetes, and Dockerfile scanning, policy management, custom checks, compliance frameworks, and suppression management. Use when scanning IaC for security misconfigurations, evaluating compliance, managing custom policies, or reviewing scan results.

中文简介正在准备中。当前显示原文说明。

cloudthinker-ai/CloudSkills62026年4月5日 更新

查看 cloudthinker-ai 的全部技能

报告此技能的问题