软件架构中的生成AI：先别替换你的架构师！

此文章是系列之一，我们探索如何利用生成式人工智能来完成软件开发生命周期中的各个阶段。您可以阅读这篇关于实验方法和工具的文章。

软件架构建设非常重要，它确保开发出的软件符合业务需求，并使技术团队取得成功。本文章探讨了生成式人工智能，特别是 GPT，如何协助软件架构。

软件架构通常由不同职称的工程师处理，如软件架构师，首席工程师，工程师，技术主管或资深工程师，这取决于组织和团队结构。对于本文，我们将集体地称这些人为“软件架构师”。

软件架构师的主要职责

技术栈选择：选择技术栈，包括编程语言、框架、平台和数据库。
决策：为设计模式、编码规范和部署制定战略技术决策。
系统设计：设计软件系统的总体结构，以符合业务目标。
跨职能需求：将安全性、可扩展性、性能和可靠性等跨职能需求整合到软件设计中。
风险管理：识别和减轻系统中的潜在风险。
团队指导：指导和辅导开发团队，确保遵循定义的架构和编码标准。
利益相关者沟通：作为利益相关者之间的桥梁，传达系统的体系结构设计并解释技术方面。
文档：维护重要的技术文档，如设计规范和架构图。

生成式人工智能如何帮助软件架构师？

现在让我们探索一下生成式人工智能如何支持建筑师在他们的职责方面。

技术栈选择:

生成式人工智能可以在这个阶段发挥建设性作用，根据定义的要求推荐潜在的技术和可行的替代方案。

例如，考虑以下提示用于列举全面的技术栈，包括前端、后端、基础设施、安全工具和CI/CD管道。

我们使用Python借助OpenAI的聊天API，而不是直接使用ChatGPT进行更高效的提示。要了解更多关于这种方法的信息，请查看开发者的ChatGPT提示工程课程。

import openai
import os

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv())
openai.api_key = os.getenv('OPENAI_API_KEY')

def get_completion(prompt, model="gpt-3.5-turbo"):
   messages = [{"role": "user", "content": prompt}]
   response = openai.ChatCompletion.create(
       model=model,
       messages=messages,
       temperature=0
   )
   return response.choices[0].message["content"]

tech_stack_prompt = """
Your role is to act as a Software Architect assistant.

Requirements that needs to be met:
- Ecosystem: Node.js
- Cloud Provider: AWS
- Use a typed language
- Backend should be a RESTful API
- Use managed services provided by the cloud provider
- Use managed relational database provided by the cloud provider
- Prefer open source tools
- Do not suggest serverless functions such as AWS Lambda
- Prefer npm over yarn

Please suggest the below:
- Frontend Tech stack
   - Programming language
   - Framework
   - Build tool
   - Code coverage tool
   - Dependency management
   - Dependency vulnerability scanning
   - Static code analysis       
   - Unit testing
   - UI testing
- Backend API Tech stack
   - Programming language
   - Framework
   - Build tool
   - Code coverage tool
   - Static code analysis
   - Dependency management
   - Dependency vulnerability scanning
   - Unit testing
   - API testing framework
   - API documentation
- Database
- Secret management  
- Security
   - Container scanning tool
   - Static Application Security Testing (SAST) tool
   - Dynamic Application Security Testing (DAST) tool
   - Penetration testing tool
- Infrastructure
   - Infrastructure as code
   - Security compliance scanning
- Logging
- Monitoring
- CI/CD tool


For each of the above, please provide in the below format:
   <tool name>
   Description: <short description>
   Reason to choose: <reason> Pls note <reason> must not include generic words like popular or widely used or large community
   Alternatives: <alternatives>. <provide the reasons to not choose them. Must not contain the reason that it lack some of the advanced features>.


Output must be in markdown syntax with proper newlines and indentation that can be directly copied to a markdown file.
"""

response = get_completion(tech_stack_prompt)
print(response)

GPT提供了技术桟的详细建议（以下为部分输出）。该方法的优点是这些提示可以在整个组织中重复使用，这加快了架构师的工作。如上所示，技术桟是针对在AWS上托管的Node.js环境进行定制的。但是，此提示可以根据所需的生态系统和云服务提供商进行定制。

## Frontend Tech stack

### Programming language
TypeScript  
**Description:** TypeScript is a typed superset of JavaScript that compiles to plain JavaScript.  
**Reason to choose:** TypeScript provides type checking, which helps catch errors at compile time rather than runtime. This leads to more stable and maintainable code.  
**Alternatives:** JavaScript. JavaScript lacks type checking, which can lead to errors at runtime.

### Framework
React  
**Description:** React is a popular JavaScript library for building user interfaces.  
**Reason to choose:** React has a large and active community, which means there are many resources and plugins available. It also has a virtual DOM, which makes it fast and efficient.  
**Alternatives:** Vue.js, Angular. Vue.js is a newer framework with a smaller community. Angular is a more complex framework that can be difficult to learn.

### Build tool
Webpack  
**Description:** Webpack is a module bundler for JavaScript applications.  
**Reason to choose:** Webpack is highly configurable and can handle a wide range of tasks, such as bundling, minification, and code splitting. It also has a large and active community.  
**Alternatives:** Parcel, Rollup. Parcel is a simpler build tool that is easier to set up, but it lacks some of the advanced features of Webpack. Rollup is a more specialized build tool that is designed for libraries rather than applications.

### Code coverage tool
Istanbul  
**Description:** Istanbul is a code coverage tool for JavaScript applications.  
**Reason to choose:** Istanbul is widely used and has good integration with other tools, such as Jest. It also has a large and active community.  
**Alternatives:** nyc. nyc is a similar tool to Istanbul, but it is less widely used.

...
...

技术决策：

生成式人工智能可以通过呈现多种选项来支持建筑师。例如，在我们的实验中，我们使用这个提示来识别在 AWS 上为 React.js 前端使用各种部署策略。

deployment_options_prompt = """
What are the different ways to deploy the frontend react js application to AWS
   - Suggest at least 3 ways
   - For each way, provide the pros and cons
   
Suggest the best way among the 3 for the below requirements
   - For a small team of 3 developers
   - For faster deployment using AWS CloudFormation
   - Lower cost
   - Used by up to 1000 users
   - Around 100 concurrent users

Output should be in markdown syntax with proper newlines and indentation that can be directly copied to a markdown file.
"""

response = get_completion(deployment_options_prompt)
print(response)

GPT提供了相应的选项及其利弊和推荐的方法。

## Deploying React JS Application to AWS

There are several ways to deploy a React JS application to AWS. Here are three ways with their pros and cons:

### 1. Deploying to Amazon S3

#### Pros:
- Easy to set up and deploy
- Low cost
- Good for static websites

#### Cons:
- Limited functionality
- Not suitable for dynamic websites

### 2. Deploying to AWS Elastic Beanstalk

#### Pros:
- Easy to deploy and manage
- Supports multiple languages and frameworks
- Auto-scaling and load balancing

#### Cons:
- Higher cost than S3
- Limited control over infrastructure

### 3. Deploying to AWS EC2

#### Pros:
- Full control over infrastructure
- Can handle complex applications
- Can be cost-effective for larger applications

#### Cons:
- More complex to set up and manage
- Requires more technical expertise
- Higher cost than S3 and Elastic Beanstalk

### Best Way for the Given Requirements
Based on the requirements, the best way to deploy the React JS application to AWS would be to use AWS Elastic Beanstalk. It is easy to deploy and manage, supports auto-scaling and load balancing, and is cost-effective for a small team of 3 developers. It can handle up to 1000 users and around 100 concurrent users. Additionally, it can be accessed from anywhere in the world, making it suitable for a team working from different locations. Finally, AWS CloudFormation can be used to automate the deployment process, making it faster and more efficient.

系统设计：

像 GPT 这样的大型语言模型是根据无数的建筑实践进行训练的。因此，它们可以针对特定项目的要求提出适当的建筑设计建议。这不仅极大地缩短了技术解决方案设计所需的时间，还为建筑师提供了一个基础蓝图，以启动他们的设计。

例如，生成式AI可以通过正确的提示加速创建部署图的过程。在我们的实验中，我们使用下面的提示来使用DiagramGPT生成部署图。尽管生成的设计可能不是最好或最准确的，但它提供了一个快速的起点。

Please provide deployment diagram with all the below items

- React application deployed to s3 and exposed via cloudfront
- Backend nodejs service deployed using Elastic Beanstalk and communicate with AWS relation database
- Backend REST API exposed via API Gateway
- Cloudfront routing to s3 or api gateway based on path
- Route 53 in front of cloudfront
- Show the users accessing the route 53 from internet 
- All Components should be inside the AWS Cloud
- Arrows to represent the network flow between the components

跨职能要求：

生成式人工智能能够通过提供洞察和建议来帮助建筑师应对跨职能需求。值得注意的是，跨职能需求经常被忽视，特别是对于缺乏经验的或新手系统设计师。

在这种情况下，使用下面展示的提示作为指南可以帮助他们在建筑设计过程中导航这个关键方面，确保这些要求得到充分考虑。

cross_functional_prompt = """
 List all the cross-functional requirements (At least 15) that need to be followed in the overall system architecture

 Information about the System architecture:
 - Nodejs backend deployed in AWS Elastic Beanstalk
 - React frontend deployed in AWS S3
 - AWS RDS MySQL database

 Each cross-functional requirement should be in the below format:
 <requirement name>:
 Description: <Description of the requirement in detail>
 Best Practices: List of practices to follow to meet the requirement
 Example: List multiple examples of how the requirement is met
 Tools: List the tools that can be used to meet the requirement

 The output must be in markdown syntax with proper new lines and indentation that can be directly copied to a markdown file      
"""

response = get_completion(cross_functional_prompt)
print(response)

GPT 能够使用工具和示例提供关于各种跨部门需求的详细建议。部分输出如下：

## Cross-Functional Requirements
-----------------
### Scalability:
Description: The system should be able to handle an increase in load without affecting performance.  
Best Practices:
- Use horizontal scaling by adding more instances of the application.
- Use load balancers to distribute traffic evenly.
- Use caching to reduce the load on the database.

Example: 
- Use AWS Elastic Beanstalk to automatically scale the application based on traffic.
- Use AWS Auto Scaling to add or remove instances based on CPU utilization.

Tools: 
- AWS Elastic Beanstalk
- AWS Auto Scaling
-----------------
### Security:
Description: The system should be secure and protect against unauthorized access.  
Best Practices:
- Use HTTPS for all communication.
- Use encryption for sensitive data.
- Use strong passwords and two-factor authentication.

Example: 
- Use AWS Certificate Manager to obtain SSL/TLS certificates for HTTPS.
- Use AWS Key Management Service to encrypt and decrypt sensitive data.

Tools: 
- AWS Certificate Manager
- AWS Key Management Service
-----------------
### Performance:
Description: The system should be performant and respond quickly to user requests.  
Best Practices:
- Use caching to reduce the load on the database.
- Use CDNs to serve static assets.
- Use compression to reduce the size of responses.

Example: 
- Use AWS ElastiCache to cache frequently accessed data.
- Use AWS CloudFront to serve static assets.

Tools: 
- AWS ElastiCache
- AWS CloudFront
-----------------
### Monitoring:
...
### Availability:
...
### Reliability:
...
### Maintainability:
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### Cost:
...
### Compliance:
...
### Disaster Recovery:
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### Collaboration:
...
### Documentation:
...
### Performance Optimization:
...
### Accessibility:
...