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CI/CD Pipeline

Overview

The AIDDDMAP CI/CD pipeline ensures consistent, reliable, and automated deployment of updates while maintaining high code quality and security standards.

Pipeline Structure

1. Continuous Integration

graph TD
    A[Code Push] --> B[Lint Check]
    B --> C[Type Check]
    C --> D[Unit Tests]
    D --> E[Integration Tests]
    E --> F[Build Check]

Automated Checks

  • ESLint & Prettier: Code style and formatting
  • TypeScript: Type checking
  • Jest: Unit testing
  • Cypress: Integration testing
  • Build Verification: Ensures successful compilation

2. Continuous Deployment

graph TD
    A[Merge to Main] --> B[Build Docker Image]
    B --> C[Run Security Scan]
    C --> D[Deploy to Staging]
    D --> E[E2E Tests]
    E --> F[Deploy to Production]

Environment Setup

Development Environment

# Install dependencies
npm install

# Run development server
npm run dev

# Run tests
npm run test

# Run linting
npm run lint

Staging Environment

  • Automatically deployed on successful PR merge
  • Accessible at staging.aidddmap.com
  • Full test suite runs before promotion

Production Environment

  • Deployed after staging validation
  • Blue-green deployment strategy
  • Automated rollback capability

Testing Framework

1. Unit Tests

// Example test structure
describe("DataCuratorAgent", () => {
  it("should validate dataset schema", async () => {
    const agent = new DataCuratorAgent();
    const result = await agent.validateSchema(mockDataset);
    expect(result.isValid).toBe(true);
  });
});

2. Integration Tests

// Example integration test
describe("IDAT Workflow", () => {
  it("should process dataset through encryption", async () => {
    const workflow = new DataWorkflow();
    await workflow.addDataset(testData);
    await workflow.encrypt();
    expect(workflow.status).toBe("encrypted");
  });
});

3. E2E Tests

// Example Cypress test
describe("Data Publishing Flow", () => {
  it("should publish dataset to marketplace", () => {
    cy.login(testUser);
    cy.uploadDataset("test.csv");
    cy.clickPublish();
    cy.get('[data-testid="success-message"]').should("be.visible");
  });
});

Deployment Process

1. Docker Build

# Example Dockerfile configuration
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
RUN npm run build
EXPOSE 3000
CMD ["npm", "start"]

2. Kubernetes Deployment

# Example deployment configuration
apiVersion: apps/v1
kind: Deployment
metadata:
  name: aidddmap
spec:
  replicas: 3
  selector:
    matchLabels:
      app: aidddmap
  template:
    metadata:
      labels:
        app: aidddmap
    spec:
      containers:
        - name: aidddmap
          image: aidddmap:latest
          ports:
            - containerPort: 3000

Monitoring & Alerts

1. Metrics Collection

  • Application performance metrics
  • Error rates and latency
  • Resource utilization
  • User activity metrics

2. Alert Configuration

# Example alert rule
alerts:
  - name: HighErrorRate
    condition: error_rate > 1%
    duration: 5m
    severity: critical
    notification:
      - slack: #alerts
      - email: devops@aidddmap.com

Security Checks

1. Automated Security Scans

  • Dependencies vulnerability check
  • Docker image scanning
  • Static code analysis
  • Secret detection

2. Compliance Verification

  • GDPR compliance checks
  • Data privacy requirements
  • Security best practices

Documentation Updates

1. Automated Documentation

  • API documentation generation
  • Changelog updates
  • Dependency documentation

2. Manual Documentation

  • Feature documentation
  • User guides
  • Architecture updates

Rollback Procedures

1. Automated Rollback

# Example rollback script
#!/bin/bash
if [ $DEPLOY_STATUS -ne 0 ]; then
  kubectl rollout undo deployment/aidddmap
  notify_team "Deployment rolled back due to errors"
fi

2. Manual Rollback

Steps for manual intervention:

  1. Identify the issue
  2. Execute rollback command
  3. Verify system stability
  4. Document the incident

Best Practices

1. Code Review

  • Required approvals: 2
  • Security review for sensitive changes
  • Performance impact assessment
  • Documentation review

2. Branch Strategy

graph LR
    A[feature] --> B[develop]
    C[bugfix] --> B
    B --> D[staging]
    D --> E[main]

3. Version Control

# Example versioning workflow
git checkout -b feature/new-feature
# Make changes
git commit -m "feat: add new feature"
# Push and create PR
git push origin feature/new-feature

Troubleshooting

Common Issues

  1. Failed builds
  2. Test failures
  3. Deployment issues
  4. Performance problems

Resolution Steps

  1. Check logs
  2. Review metrics
  3. Analyze error patterns
  4. Escalate if needed

Contact Information

DevOps Team

Documentation Team