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技能库 智客分类:运维与云 infrastructure

Infrastructure

Kubernetes号、主机、集装箱和提供云的遥测船进入Grafana Cloud——`k8s-监测' K8s集群的Helm图(量子+日志+痕迹+事件+成本),合金"prometheus.exporter.unix"用于Linux主机,cAdvisor+多克发现用于容器,和Cloud Watch / Azure Monitor / Google Cloud 监控数据源设置. 将新集群或 VM 机队装入 Grafana Cloud 时使用, 选择右边 K8s刮取,接通kube-state-meters + node-exporter + cAdvisor,提醒"PodCrashLooping"/节点内存/PVC容量,或拉出AWS / Azure / GCP云度量衡——即使用户表示"监视我的集群","发送K8s度量衡到Grafana","scrape EC2度量衡","集群座舱记录",或"安装监测方向图"而不命名"k8s-监测"或"合金".

4657 安装量

官方网址:skills.sh

技能介绍

先看中文介绍;官方 description 原文单独保留,不改写 SKILL.md。

做什么

Kubernetes号、主机、集装箱和提供云的遥测船进入Grafana Cloud——`k8s-监测' K8s集群的Helm图(计量+日志+痕迹+事件+成本),合金"prometheus.exporter.unix"用于Linux主机,cAdvisor+多克发现用于容器,和CloudWatch/AzureMonitor/Google云监测数据源设置

何时用

搭载一个新的集群或VM舰队前往格拉法纳克云,选择右边 K8s 刮去、 接线 kube- state- meters + node- exporter + cAdvisor, 提醒“ PodCrashLooping” / 节点内存 / PVC 容量, 或拉出 AWS / Azure / GCP 云度量度值—— 即使用户

代理如何加载

按 Agent Skills 渐进披露:启动时只加载 name 与 description(约 100 token);任务匹配后才读入整份 SKILL.md 正文;scripts/、references/、assets/ 仅在需要时再读。 本文件正文结构:Grafana Cloud Infrastructure Monitoring、Prerequisites、Common Workflows、1. Onboard a Kubernetes cluster (k8s-monitoring chart)、1. Create the namespace + secret、2. Install — values.yaml in references/k8s-monitoring-values.md。 其中含规范建议的小节:分步指令。

文件分析

文件分析:除 SKILL.md 外,正文引用了 references/k8s-monitoring-values.md、references/clouds-and-hosts.md,属于带资源的技能包,这些文件按需再读。

官方 description(原文)

Ship Kubernetes, host, container, and cloud-provider telemetry into Grafana Cloud — `k8s-monitoring` Helm chart for K8s clusters (metrics + logs + traces + events + cost), Alloy `prometheus.exporter.unix` for Linux hosts, cAdvisor + Docker discovery for containers, and CloudWatch / Azure Monitor / Google Cloud Monitoring datasource setup. Use when onboarding a new cluster or VM fleet to Grafana Cloud, picking the right Helm values for K8s scraping, wiring kube-state-metrics + node-exporter + cAdvisor, alerting on `PodCrashLooping` / node memory / PVC capacity, or pulling AWS / Azure / GCP cloud metrics — even when the user says "monitor my cluster", "send K8s metrics to Grafana", "scrape EC2 metrics", "cluster pod logs", or "install the monitoring helm chart" without naming `k8s-monitoring` or Alloy.

Grafana Cloud Infrastructure MonitoringPrerequisitesCommon Workflows1. Onboard a Kubernetes cluster (k8s-monitoring chart)1. Create the namespace + secret2. Install — values.yaml in references/k8s-monitoring-values.md3. Verify every pod is RunningExpect alloy-*, kube-state-metrics-*, node-exporter-*, etc. all Ready.4. Verify no error logs in the metrics/logs/traces Alloys5. Verify telemetry landed in Grafana CloudPromQL on the metrics datasource (should be > 0):sum(up{cluster="production-us-east"})

· 许可:Apache-2.0

来源分类:skills.sh agent-skill

SKILL.md 与 Agent 调用

官方规范 ↗
name
infrastructure
description
Ship Kubernetes, host, container, and cloud-provider telemetry into Grafana Cloud — `k8s-monitoring` Helm chart for K8s clusters (metrics + logs + traces + events + cost), Alloy `prometheus.exporter.unix` for Linux hosts, cAdvisor + Docker discovery for containers, and CloudWatch / Azure Monitor / Google Cloud Monitoring datasource setup. Use when onboarding a new cluster or VM fleet to Grafana Cloud, picking the right Helm values for K8s scraping, wiring kube-state-metrics + node-exporter + cAdvisor, alerting on `PodCrashLooping` / node memory / PVC capacity, or pulling AWS / Azure / GCP cloud metrics — even when the user says "monitor my cluster", "send K8s metrics to Grafana", "scrape EC2 metrics", "cluster pod logs", or "install the monitoring helm chart" without naming `k8s-monitoring` or Alloy.
许可
Apache-2.0
  1. 发现技能客户端向 Agent 提供名称与描述目录。
  2. 匹配与调用用户指定或任务匹配后,载入 SKILL.md 指令。
  3. 按需加载按步骤读取参考文档、使用脚本与素材。
指令中引用的文件 · 2
  • references/k8s-monitoring-values.md
  • references/clouds-and-hosts.md

以下路径提取自原文;文件是否齐全请以来源仓库中的完整目录为准。

具体调用语法与可用工具以目标 Agent 客户端为准。 查看调用机制说明 ↗

安装这个技能

Skills CLI ↗

先选择目标 Agent 和安装范围,保留技能包的附属文件,安装后检查客户端能否发现该技能。

该技能引用了附属文件,请从来源获取完整目录;仅复制 SKILL.md 可能缺少依赖。

交给 Agent 安装

复制安装指令给支持 Agent Skills 的代理,确认其中的目标目录与客户端匹配。

把 Agent Skill「infrastructure」安装到我的项目:SKILL.md 原文与官方 description 见 https://zicq.com/zh/skills/skl-194fa957e5056f1d-Infrastructure.html
请存为 .cursor/skills/infrastructure/SKILL.md 或 .claude/skills/infrastructure/SKILL.md,frontmatter 的 name 与 description 保持原样,不要改写。
该技能还带 scripts/、references/、assets/ 等文件,请从 https://github.com/grafana/skills 取完整目录,不要只建一个 SKILL.md。

GitHub 完整包 ↗

终端安装 · Skills CLI

需要 Node.js 与 npx。先查看仓库技能列表,确认实际名称。

npx skills add 'https://github.com/grafana/skills' --list

npx skills add 'https://github.com/grafana/skills' --skill 'infrastructure'

CLI 会交互选择目标 Agent,默认安装到项目;用户级安装使用 -g。先通过查看命令核对仓库内容,再用 npx skills list 检查已安装技能。

阅读排版
--- name: infrastructure license: Apache-2.0 description: Ship Kubernetes, host, container, and cloud-provider telemetry into Grafana Cloud — `k8s-monitoring` Helm chart for K8s clusters (metrics + logs + traces + events + cost), Alloy `prometheus.exporter.unix` for Linux hosts, cAdvisor + Docker discovery for containers, and CloudWatch / Azure Monitor / Google Cloud Monitoring datasource setup. Use when onboarding a new cluster or VM fleet to Grafana Cloud, picking the right Helm values for K8s scraping, wiring kube-state-metrics + node-exporter + cAdvisor, alerting on `PodCrashLooping` / node memory / PVC capacity, or pulling AWS / Azure / GCP cloud metrics — even when the user says "monitor my cluster", "send K8s metrics to Grafana", "scrape EC2 metrics", "cluster pod logs", or "install the monitoring helm chart" without naming `k8s-monitoring` or Alloy. --- # Grafana Cloud Infrastructure Monitoring > **Docs**: https://grafana.com/docs/grafana-cloud/monitor-infrastructure/ K8s + host + container + cloud-provider telemetry, mostly via the `grafana/k8s-monitoring` Helm chart or Alloy. ## Prerequisites - Grafana Cloud stack with Prometheus / Loki / Tempo endpoints + API key (`metrics:write`, `logs:write`, `traces:write`) - For Kubernetes: a cluster + `helm` 3.x + `kubectl` context pointing at it - For hosts / Docker: Alloy installed on the node ## Common Workflows ### 1. Onboard a Kubernetes cluster (k8s-monitoring chart) ```bash # 1. Create the namespace + secret kubectl create namespace monitoring kubectl create secret generic grafana-cloud-secret \ -n monitoring --from-literal=api-key= # 2. Install — values.yaml in references/k8s-monitoring-values.md helm repo add grafana https://grafana.github.io/helm-charts && helm repo update helm install k8s-monitoring grafana/k8s-monitoring \ --version 4.1.4 -n monitoring -f values.yaml # 3. Verify every pod is Running kubectl get pods -n monitoring # Expect alloy-*, kube-state-metrics-*, node-exporter-*, etc. all Ready. # 4. Verify no error logs in the metrics/logs/traces Alloys kubectl -n monitoring logs deploy/k8s-monitoring-alloy-metrics --tail=50 | grep -iE 'error|level=err' || echo "clean" # 5. Verify telemetry landed in Grafana Cloud # PromQL on the metrics datasource (should be > 0): # sum(up{cluster="production-us-east"}) # LogQL on Loki: # sum(count_over_time({cluster="production-us-east"}[5m])) ``` Full `values.yaml`, key PromQL, dashboard IDs (15520, 1860, 14282…), and alert rules: [`references/k8s-monitoring-values.md`](references/k8s-monitoring-values.md). ### 2. Monitor a Linux host ```alloy # 1. /etc/alloy/config.alloy — see references/clouds-and-hosts.md for the full block prometheus.exporter.unix "host" { rootfs_path = "/" } prometheus.scrape "node" { targets = prometheus.exporter.unix.host.targets forward_to = [prometheus.remote_write.cloud.receiver] } ``` ```bash # 2. Reload Alloy and verify the unix exporter is up systemctl reload alloy curl -s http://localhost:12345/api/v0/web/components | jq '.[] | select(.id|contains("prometheus.exporter.unix"))' # 3. Verify in Grafana Cloud — open the "Node Exporter Full" dashboard (ID 1860) # and pick your host from the `instance` dropdown. ``` ### 3. Pull AWS / Azure / GCP metrics Provision the datasource (full YAML in [`references/clouds-and-hosts.md`](references/clouds-and-hosts.md)), then: ```bash # 1. After provisioning, restart Grafana to pick up the file # 2. Verify the datasource — Grafana → Connections → Data sources → "Test" # Expect "Successfully queried the CloudWatch metrics API" (or equivalent). # 3. Confirm a query — Explore → datasource → metric e.g. # CloudWatch namespace AWS/EC2 metric CPUUtilization, last 1h. ``` ## Troubleshooting - chart installed but no metrics in Cloud → check the `grafana-cloud-secret` `api-key` value; check Alloy logs for `401` - `kube-state-metrics` pod Pending → likely RBAC; reapply the chart's CRDs/CRBs - Node-exporter pod CrashLoopBackOff → typically `hostNetwork: true` collision with the host's :9100; change the port - CloudWatch "Access denied" → IAM role missing `cloudwatch:GetMetricData`, `cloudwatch:ListMetrics` ## Resources - [`grafana/k8s-monitoring` chart](https://github.com/grafana/k8s-monitoring-helm) - [Monitor Infrastructure docs](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/) - [CloudWatch datasource](https://grafana.com/docs/grafana/latest/datasources/aws-cloudwatch/) - [Azure Monitor datasource](https://grafana.com/docs/grafana/latest/datasources/azure-monitor/) - [Google Cloud Monitoring datasource](https://grafana.com/docs/grafana/latest/datasources/google-cloud-monitoring/)

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