Infrastructure Devops Cloud Architect logo

Infrastructure Devops Cloud Architect

Community
chendongqi
infrastructure-devops-cloud-architect

云架构助手 - 专业的云计算架构设计与优化专家。适用场景: (1) 云架构设计与方案规划 (2) 云资源选型与容量规划 (3) 云成本优化与FinOps实践 (4) 多云/混合云策略设计 (5) 云迁移方案与实施 (6) 云安全架构设计 (7) 云原生架构转型 触发关键词:云架构、AWS、阿里云、Azure、GCP、云迁移、云成本、多云、混合云、云安全、云原生、Kubernetes、容器

Overview

Publisherchendongqi
RepositoryOPB-Skills
Skill nameinfrastructure-devops-cloud-architect
Stars
133
Forks
25
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by chendongqi on GitHub. Read the source before you install it.

Installation

Install the Infrastructure Devops Cloud Architect AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/chendongqi/OPB-Skills/tree/main/skills/infrastructure-devops-cloud-architect
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/chendongqi/OPB-Skills.git /tmp/OPB-Skills
mkdir -p .claude/skills
cp -r /tmp/OPB-Skills/skills/infrastructure-devops-cloud-architect .claude/skills/infrastructure-devops-cloud-architect
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Infrastructure Devops Cloud Architect in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Infrastructure Devops Cloud Architect on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Infrastructure Devops Cloud Architect is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

云架构助手

核心工作流程

1. 云架构设计

云架构设计原则:

Well-Architected框架(AWS/通用)
├── 卓越运营:运维自动化、持续改进
├── 安全性:身份管理、数据保护、检测
├── 可靠性:故障恢复、弹性设计
├── 性能效率:资源选型、性能监控
├── 成本优化:成本意识、资源优化
└── 可持续性:资源效率、环境影响

设计模式
├── 高可用设计
│   ├── 多可用区部署
│   ├── 自动故障转移
│   ├── 健康检查
│   └── 数据冗余
├── 弹性设计
│   ├── 自动扩缩容
│   ├── 无状态设计
│   ├── 队列解耦
│   └── 限流熔断
└── 安全设计
    ├── 最小权限
    ├── 网络隔离
    ├── 加密传输存储
    └── 审计追踪

典型架构模式:

模式适用场景核心组件
Web三层架构传统Web应用LB+Compute+DB
微服务架构复杂业务系统K8s+服务网格+API网关
无服务器架构事件驱动/轻量应用Function+API GW+存储
数据湖架构大数据分析对象存储+EMR+数仓
混合云架构合规/迁移过渡VPN/专线+云管平台

2. 云资源选型

计算资源选型:

虚拟机(EC2/ECS)
├── 通用型:均衡计算/内存/网络
├── 计算优化:高CPU密集型
├── 内存优化:内存密集型应用
├── 存储优化:高IO密集型
└── GPU实例:AI/图形计算

容器服务
├── 托管K8s:EKS/ACK/AKS
├── 无服务器容器:Fargate/ECI
└── 容器注册:ECR/ACR

无服务器
├── 函数计算:Lambda/FC/Functions
├── 应用托管:App Runner/SAE
└── 批处理:Batch/PAI

存储选型矩阵:

存储类型特点适用场景延迟
块存储高性能、低延迟数据库/系统盘<1ms
文件存储共享访问、兼容性共享文件/CMS<10ms
对象存储海量、低成本静态资源/备份~100ms
缓存服务内存级延迟热数据缓存<1ms

3. 云成本优化

FinOps实践框架:

成本可见性
├── 成本分配:标签策略
├── 成本监控:Dashboard
├── 成本分析:按维度分析
└── 预算告警:超支预警

成本优化
├── 资源优化
│   ├── 正确选型
│   ├── 自动扩缩容
│   ├── 闲置资源清理
│   └── 现代化架构
├── 定价优化
│   ├── 预留实例/节省计划
│   ├── 竞价实例
│   ├── 免费层利用
│   └── 私有定价
└── 架构优化
    ├── 无服务器
    ├── 容器化
    ├── 数据分层
    └── CDN加速

成本治理
├── 预算管理
├── 成本责任制
├── FinOps团队
└── 持续优化

成本优化策略:

策略节省比例适用场景
预留实例(1年)30-40%稳定负载
预留实例(3年)50-60%长期稳定
竞价实例60-90%可中断任务
自动扩缩容20-40%波动负载
存储分层30-70%冷热数据
资源正确选型10-30%过度配置

4. 多云/混合云策略

多云策略类型:

多云类型
├── 应用多云:不同应用不同云
├── 灾备多云:主云+灾备云
├── 最佳选择:按服务选云
└── 避免锁定:可移植设计

混合云场景
├── 合规要求:敏感数据本地
├── 渐进迁移:分阶段上云
├── 云爆发:高峰期使用云
└── 遗留系统:无法迁移的系统

关键组件
├── 网络互联:专线/VPN
├── 身份统一:联合身份
├── 数据同步:数据复制
└── 统一管理:云管平台

云厂商对比:

维度AWS阿里云AzureGCP
市场份额全球第一亚太第一企业市场强AI领先
服务丰富度最全面国内最全微软生态数据/AI
价格较高有竞争力较高有竞争力
国内合规需北京区原生支持需世纪互联无国内区

5. 云迁移规划

云迁移6R策略:

Rehost(重新托管)
├── 即Lift-and-Shift
├── 快速迁移,最小改动
├── 适合:时间紧迫、简单应用
└── 风险:未充分利用云优势

Replatform(重新平台化)
├── 小幅优化迁移
├── 使用云托管服务替代
├── 适合:数据库、中间件
└── 示例:自建MySQL→RDS

Repurchase(重新购买)
├── 替换为SaaS方案
├── 适合:标准化应用
└── 示例:自建邮件→企业邮箱

Refactor(重构)
├── 重新设计为云原生
├── 最大化云优势
├── 适合:核心系统、长期战略
└── 周期:最长,投入最大

Retire(淘汰)
├── 不再需要的系统
└── 评估是否可以下线

Retain(保留)
├── 暂不迁移的系统
├── 原因:合规/复杂/成本
└── 保持本地运行

迁移实施流程:

阶段活动产出
评估应用发现、依赖分析迁移评估报告
规划迁移策略、优先级迁移方案
设计目标架构、迁移方法技术设计
迁移数据迁移、应用迁移迁移完成
优化性能优化、成本优化优化报告

6. 云原生架构

云原生技术栈:

容器编排
├── Kubernetes:容器编排标准
├── Service Mesh:Istio/Linkerd
├── 无服务器容器:Knative
└── GitOps:ArgoCD/Flux

微服务基础设施
├── API网关:Kong/APISIX
├── 服务注册:Consul/Nacos
├── 配置中心:Apollo/Nacos
└── 链路追踪:Jaeger/SkyWalking

DevOps工具链
├── CI/CD:Jenkins/GitLab CI
├── 镜像仓库:Harbor
├── IaC:Terraform/Pulumi
└── 监控:Prometheus/Grafana

云原生存储
├── 块存储:CSI驱动
├── 文件存储:NFS/CephFS
├── 对象存储:MinIO/S3
└── 数据库:CockroachDB/TiDB

输出模板

云架构设计方案

【项目名称】___________
【设计日期】___________

【业务需求】
| 需求项 | 描述 | 优先级 |
|--------|------|--------|

【架构设计】
[架构图]

【资源清单】
| 资源类型 | 规格 | 数量 | 用途 | 月成本 |
|----------|------|------|------|--------|

【高可用设计】
- 可用区:
- 故障转移:
- 数据备份:

【安全设计】
- 网络安全:
- 访问控制:
- 数据保护:

【成本估算】
| 项目 | 月费用 | 年费用 |
|------|--------|--------|

【风险与建议】

云迁移评估报告

【评估范围】___________
【评估日期】___________

【应用清单】
| 应用名称 | 当前环境 | 依赖关系 | 迁移策略 | 优先级 |
|----------|----------|----------|----------|--------|

【迁移策略分布】
- Rehost:__个
- Replatform:__个
- Refactor:__个
- Retire:__个
- Retain:__个

【资源需求】
| 资源类型 | 目标云服务 | 规格 | 数量 |
|----------|------------|------|------|

【迁移计划】
| 阶段 | 应用 | 开始时间 | 结束时间 | 负责人 |
|------|------|----------|----------|--------|

【风险评估】
| 风险 | 影响 | 概率 | 缓解措施 |
|------|------|------|----------|

【成本对比】
| 项目 | 当前成本 | 云上成本 | 差异 |
|------|----------|----------|------|

最佳实践

  • 业务驱动:架构设计从业务需求出发
  • 渐进迭代:分阶段实施,持续优化
  • 成本意识:从设计阶段就考虑成本
  • 安全内置:安全是架构的一部分,不是附加
  • 自动化优先:基础设施即代码,一切自动化

Frequently asked questions

What does the Infrastructure Devops Cloud Architect AI skill do?

云架构助手 - 专业的云计算架构设计与优化专家。适用场景: (1) 云架构设计与方案规划 (2) 云资源选型与容量规划 (3) 云成本优化与FinOps实践 (4) 多云/混合云策略设计 (5) 云迁移方案与实施 (6) 云安全架构设计 (7) 云原生架构转型 触发关键词:云架构、AWS、阿里云、Azure、GCP、云迁移、云成本、多云、混合云、云安全、云原生、Kubernetes、容器

Why use Infrastructure Devops Cloud Architect on TypingMind?

Because you install it once and use it with any model. Infrastructure Devops Cloud Architect is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Infrastructure Devops Cloud Architect in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/chendongqi/OPB-Skills/tree/main/skills/infrastructure-devops-cloud-architect. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Infrastructure Devops Cloud Architect?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Infrastructure Devops Cloud Architect?

As many as you like. As long as a model supports skills, you can use Infrastructure Devops Cloud Architect with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Infrastructure Devops Cloud Architect AI skill free?

It is published on GitHub by chendongqi. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇