environment-deployment-strategy

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Original

English

🇨🇳

Translation

Chinese

Environment Deployment Strategy

环境部署策略

This is a reference pattern. Learn from the approach, adapt to your context — don't copy verbatim.

Problem: Need safe deployment practices that prevent accidental production deployments while enabling rapid development iteration.

Solution: Three-tier environment strategy with deployment restrictions.

这是一个参考模式。 请学习其思路，适配你自身的场景，不要逐字照搬。

问题：需要既能避免意外部署到生产环境，又能支持快速开发迭代的安全部署实践。

解决方案：带部署限制的三层环境策略。

Pattern

模式说明

Three Environments:

Local (
```
local
```
)
- Runs on developer machine
- Uses cloud resources from
```
dev
```
  environment
- Cannot be deployed (no cloud resources)
- Fast iteration, no deployment wait
Development (
```
dev
```
)
- Deployed to cloud
- Mirrors production architecture
- Can deploy via: Local script OR GitHub Actions (on merge to
```
dev
```
  branch)
- Used for testing and validation
Production (
```
prod
```
)
- Deployed to cloud
- Live customer-facing environment
- Can ONLY deploy via: GitHub Actions (on merge to
```
main
```
  branch)
- Never deployed from local machine

三类环境：

本地环境（
```
local
```
）
- 运行在开发者设备上
- 使用
```
dev
```
  环境的云资源
- 无需部署（无专属云资源）
- 迭代速度快，无部署等待时间
开发环境（
```
dev
```
）
- 部署在云端
- 与生产环境架构完全一致
- 可通过以下方式部署：本地脚本或合并代码到
```
dev
```
  分支时触发GitHub Actions
- 用于测试和功能验证
生产环境（
```
prod
```
）
- 部署在云端
- 面向用户的线上运行环境
- 仅可通过合并代码到
```
main
```
  分支时触发GitHub Actions部署
- 绝对不允许从本地机器直接部署

Why This Pattern?

该模式的优势

Benefits:

Safety: Production protected from accidental local deployments
Speed: Local development uses cloud dev resources (no local infrastructure)
Consistency: Dev mirrors prod, catches issues before production
Audit Trail: All prod deployments tracked in GitHub Actions logs
Rollback: Git history enables easy rollback

Prevents:

Accidental production deployments from developer machines
Untested code reaching production
Configuration drift between environments
"Works on my machine" issues

收益：

安全性：避免本地意外部署到生产环境
开发速度：本地开发直接使用云端开发环境资源，无需搭建本地基础设施
一致性：开发环境与生产环境架构一致，可在上线前提前发现问题
审计追溯：所有生产环境部署记录都保存在GitHub Actions日志中
回滚能力：Git历史记录支持快速回滚

可规避的问题：

开发者从本地机器意外部署到生产环境
未测试的代码上线到生产环境
不同环境之间的配置漂移
"在我本地能运行"类问题

Implementation

实现方式

Environment Configuration:

bash

undefined

环境配置：

bash

undefined

.env (local - not committed)

.env (本地环境 - 不提交到代码库)

ENVIRONMENT=local AWS_REGION=eu-central-1

Uses dev resources

开发环境资源

API_ENDPOINT=https://api-dev.example.com

.env.dev (committed template)

.env.dev (提交到代码库的模板)

ENVIRONMENT=dev AWS_REGION=eu-central-1 API_ENDPOINT=https://api-dev.example.com

.env.prod (committed template, secrets from SSM)

.env.prod (提交到代码库的模板，敏感信息从SSM获取)

ENVIRONMENT=prod AWS_REGION=eu-central-1 API_ENDPOINT=https://api.example.com


**Deployment Scripts**:

```json
// package.json
{
  "scripts": {
    "deploy:dev": "cdk deploy --all --context environment=dev",
    "deploy:prod": "echo 'ERROR: Production can only be deployed via GitHub Actions' && exit 1"
  }
}

GitHub Actions Workflow:

yaml

undefined

ENVIRONMENT=prod AWS_REGION=eu-central-1 API_ENDPOINT=https://api.example.com


**部署脚本**：

```json
// package.json
{
  "scripts": {
    "deploy:dev": "cdk deploy --all --context environment=dev",
    "deploy:prod": "echo 'ERROR: Production can only be deployed via GitHub Actions' && exit 1"
  }
}

GitHub Actions工作流：

yaml

undefined

.github/workflows/deploy.yml

name: Deploy

on: pull_request: types: [closed] branches: [dev, main]

jobs: deploy-dev: if: github.base_ref == 'dev' && github.event.pull_request.merged == true runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Deploy to Dev run: npm run deploy:dev

deploy-prod: if: github.base_ref == 'main' && github.event.pull_request.merged == true runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Deploy to Production run: cdk deploy --all --context environment=prod

---

name: Deploy

on: pull_request: types: [closed] branches: [dev, main]

jobs: deploy-dev: if: github.base_ref == 'dev' && github.event.pull_request.merged == true runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Deploy to Dev run: npm run deploy:dev

---

Deployment Flow

部署流程

Development Cycle:

1. Developer works locally (uses dev resources)
2. Commits to feature branch
3. Opens PR to dev branch
4. PR merged → GitHub Actions deploys to dev
5. Test in dev environment
6. Open PR from dev to main
7. PR merged → GitHub Actions deploys to prod

Local Development:

bash

undefined

开发周期：

1. 开发者在本地开发（使用开发环境资源）
2. 提交代码到功能分支
3. 提交PR到dev分支
4. PR合并 → GitHub Actions自动部署到开发环境
5. 在开发环境测试验证
6. 提交PR从dev分支到main分支
7. PR合并 → GitHub Actions自动部署到生产环境

本地开发：

bash

undefined

Developer runs frontend locally

开发者在本地运行前端

npm run dev

Frontend connects to dev API

前端连接到开发环境API

No infrastructure deployment needed

无需部署基础设施

Fast iteration

迭代速度快


**Dev Deployment** (two options):
```bash


**开发环境部署**（两种可选方式）：
```bash

Option 1: Local deployment (for quick testing)

方式1：本地部署（用于快速测试）

npm run deploy:dev

Option 2: GitHub Actions (on PR merge to dev)

方式2：GitHub Actions（PR合并到dev分支时自动触发）

Automatic, tracked, consistent

自动化、可追溯、一致性高


**Prod Deployment** (one option only):
```bash


**生产环境部署**（仅支持一种方式）：
```bash

Only via GitHub Actions (on PR merge to main)

仅可通过PR合并到main分支时触发GitHub Actions部署

Attempting local deployment fails with error message

尝试本地部署会直接报错终止

---

---

Resource Isolation

资源隔离

Separate Resources Per Environment:

typescript

// All resources include environment identifier
const bucket = new s3.Bucket(this, 'Bucket', {
  bucketName: `${PROJECT_ID}-data-${environment}` // dev or prod
});

const table = new dynamodb.Table(this, 'Table', {
  tableName: `${PROJECT_ID}-users-${environment}` // dev or prod
});

Why: Prevents dev and prod from sharing resources, avoiding data corruption and conflicts.

每个环境独立使用专属资源：

typescript

// 所有资源名称都包含环境标识
const bucket = new s3.Bucket(this, 'Bucket', {
  bucketName: `${PROJECT_ID}-data-${environment}` // dev 或 prod
});

const table = new dynamodb.Table(this, 'Table', {
  tableName: `${PROJECT_ID}-users-${environment}` // dev 或 prod
});

原因：避免开发环境和生产环境共享资源，防止数据损坏和资源冲突。

AWS CodePipeline Integration

AWS CodePipeline集成

Alternative: Use AWS CodePipeline instead of GitHub Actions

typescript

// Separate pipelines per environment
const devPipeline = new codepipeline.Pipeline(this, 'DevPipeline', {
  pipelineName: `${PROJECT_ID}-pipeline-dev`
});

const prodPipeline = new codepipeline.Pipeline(this, 'ProdPipeline', {
  pipelineName: `${PROJECT_ID}-pipeline-prod`
});

GitHub Actions trigger:

yaml

- name: Trigger Dev Pipeline
  run: aws codepipeline start-pipeline-execution --name ${PROJECT_ID}-pipeline-dev

- name: Trigger Prod Pipeline
  run: aws codepipeline start-pipeline-execution --name ${PROJECT_ID}-pipeline-prod

Benefits:

Build logs in AWS CloudWatch
IAM-based permissions (no GitHub secrets)
Integrated with AWS services

替代方案：使用AWS CodePipeline代替GitHub Actions

typescript

// 每个环境独立配置流水线
const devPipeline = new codepipeline.Pipeline(this, 'DevPipeline', {
  pipelineName: `${PROJECT_ID}-pipeline-dev`
});

const prodPipeline = new codepipeline.Pipeline(this, 'ProdPipeline', {
  pipelineName: `${PROJECT_ID}-pipeline-prod`
});

GitHub Actions触发配置：

yaml

- name: Trigger Dev Pipeline
  run: aws codepipeline start-pipeline-execution --name ${PROJECT_ID}-pipeline-dev

- name: Trigger Prod Pipeline
  run: aws codepipeline start-pipeline-execution --name ${PROJECT_ID}-pipeline-prod

优势：

构建日志存储在AWS CloudWatch
基于IAM的权限控制（无需配置GitHub密钥）
与AWS服务深度集成

Variations

变种模式

Two-Environment (simpler projects):

```
dev
```
- Development and testing
```
prod
```
- Production only

Four-Environment (enterprise):

```
local
```
- Developer machines
```
dev
```
- Development
```
staging
```
- Pre-production testing
```
prod
```
- Production

双环境模式（适用于小型项目）：

```
dev
```
- 开发和测试用
```
prod
```
- 仅生产环境

四环境模式（适用于企业级项目）：

```
local
```
- 开发者本地环境
```
dev
```
- 开发环境
```
staging
```
- 预发测试环境
```
prod
```
- 生产环境

Related Patterns

Progressive Improvement

持续优化

If the developer corrects a behavior that this skill should have prevented, suggest a specific amendment to this skill to prevent the same correction in the future.

如果开发者修正了本模式本应避免的问题，请提出具体的修改建议，避免同类问题再次发生。

environment-deployment-strategy

Original

Translation

Environment Deployment Strategy

环境部署策略

Pattern

模式说明

Why This Pattern?

该模式的优势

Implementation

实现方式

.env (local - not committed)

.env (本地环境 - 不提交到代码库)

Uses dev resources

开发环境资源

.env.dev (committed template)

.env.dev (提交到代码库的模板)

.env.prod (committed template, secrets from SSM)

.env.prod (提交到代码库的模板，敏感信息从SSM获取)

.github/workflows/deploy.yml

.github/workflows/deploy.yml

Deployment Flow

部署流程

Developer runs frontend locally

开发者在本地运行前端

Frontend connects to dev API

前端连接到开发环境API

No infrastructure deployment needed

无需部署基础设施

Fast iteration

迭代速度快

Option 1: Local deployment (for quick testing)

方式1：本地部署（用于快速测试）

Option 2: GitHub Actions (on PR merge to dev)

方式2：GitHub Actions（PR合并到dev分支时自动触发）

Automatic, tracked, consistent

自动化、可追溯、一致性高

Only via GitHub Actions (on PR merge to main)

仅可通过PR合并到main分支时触发GitHub Actions部署

Attempting local deployment fails with error message

尝试本地部署会直接报错终止

Resource Isolation

资源隔离

AWS CodePipeline Integration

AWS CodePipeline集成

Variations

变种模式

Related Patterns

相关模式

Progressive Improvement

持续优化