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BMAD-METHOD/bmad-system/INTEGRATION_GUIDE.md

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# Enhanced BMAD System Integration Guide
## 🔗 Complete Integration Reference
This guide provides comprehensive instructions for integrating the Enhanced BMAD System with various development environments, tools, and workflows.
## 1. 🎯 Claude Code Integration
### Basic Integration
```javascript
// Initialize BMAD in Claude Code session
const bmadSystem = {
mode: "enhanced",
autonomy_level: "collaborative",
learning_enabled: true,
optimization_targets: ["quality", "speed", "maintainability"]
};
// Start BMAD-powered development session
function initializeBMAD() {
return `
Enhanced BMAD System initialized for Claude Code.
Configuration:
- Autonomy Level: ${bmadSystem.autonomy_level}
- Learning: ${bmadSystem.learning_enabled ? 'Enabled' : 'Disabled'}
- Optimization: ${bmadSystem.optimization_targets.join(', ')}
Ready for intelligent development assistance.
`;
}
```
### Advanced Claude Code Integration
```python
# Python interface for BMAD-Claude Code integration
class BMADClaudeCodeInterface:
def __init__(self, config=None):
self.config = config or {
"autonomy_level": "collaborative",
"learning_rate": "adaptive",
"quality_gates": True,
"safety_checks": True,
"multi_llm_enabled": False
}
async def process_request(self, user_request, context=None):
"""Process user request with BMAD intelligence"""
# Analyze request complexity and requirements
analysis = await self.analyze_request(user_request, context)
# Route to appropriate BMAD module
if analysis["type"] == "code_development":
return await self.autonomous_development_engine.process(
user_request, analysis
)
elif analysis["type"] == "architecture_design":
return await self.enterprise_architecture_platform.design(
user_request, analysis
)
elif analysis["type"] == "optimization_request":
return await self.self_optimization_engine.optimize(
user_request, analysis
)
# Default to intelligent assistance
return await self.provide_intelligent_assistance(user_request, analysis)
```
### Session Configuration Examples
#### For Individual Developers
```
Configure BMAD for personal development:
- Autonomy: Collaborative (you and AI work together)
- Learning: Enabled (adapts to your coding style)
- Safety: High (prevents dangerous operations)
- Optimization: Focus on code quality and learning
Please help me with [your development task]
```
#### For Teams
```
Configure BMAD for team development:
- Autonomy: Supervised (AI works, team reviews)
- Standards: Enforce team coding standards
- Integration: Connect with team's CI/CD pipeline
- Collaboration: Enable shared learning across team
Team project: [project description]
```
#### For Enterprise
```
Configure BMAD for enterprise development:
- Autonomy: Guided/Collaborative (enterprise constraints)
- Compliance: Enable all regulatory frameworks
- Security: Zero-trust architecture
- Governance: Full enterprise governance
- Monitoring: Complete analytics and reporting
Enterprise requirements: [requirements document]
```
## 2. 🤖 Multi-LLM Integration
### LLM Orchestration Configuration
```python
class MultiLLMOrchestrator:
def __init__(self):
self.llm_capabilities = {
"claude": {
"strengths": ["reasoning", "analysis", "architecture"],
"best_for": ["complex_logic", "system_design", "documentation"],
"cost_tier": "premium"
},
"gpt4": {
"strengths": ["code_generation", "completion", "translation"],
"best_for": ["rapid_prototyping", "code_completion", "refactoring"],
"cost_tier": "high"
},
"gemini": {
"strengths": ["multimodal", "search", "data_analysis"],
"best_for": ["image_processing", "data_science", "research"],
"cost_tier": "medium"
},
"deepseek": {
"strengths": ["code_understanding", "optimization"],
"best_for": ["code_review", "performance_optimization"],
"cost_tier": "low"
}
}
async def route_request(self, request, context):
"""Intelligently route request to best LLM"""
request_analysis = await self.analyze_request_type(request)
# Select optimal LLM based on task type and constraints
selected_llm = await self.select_optimal_llm(
request_analysis,
cost_constraint=context.get("budget"),
quality_requirement=context.get("quality_level"),
speed_requirement=context.get("urgency")
)
return await self.execute_with_llm(selected_llm, request, context)
```
### Configuration Examples
#### Cost-Optimized Strategy
```yaml
bmad_multi_llm_config:
strategy: "cost_optimized"
primary_llm: "deepseek" # Low cost for routine tasks
fallback_llm: "claude" # High quality for complex tasks
routing_rules:
- if: "simple_code_generation"
use: "deepseek"
- if: "complex_reasoning"
use: "claude"
- if: "data_analysis"
use: "gemini"
```
#### Quality-First Strategy
```yaml
bmad_multi_llm_config:
strategy: "quality_first"
primary_llm: "claude" # Highest quality reasoning
secondary_llm: "gpt4" # Fast code generation
validation_llm: "gemini" # Cross-validation
routing_rules:
- if: "architecture_design"
use: "claude"
- if: "rapid_prototyping"
use: "gpt4"
- if: "validation_required"
use: ["claude", "gemini"] # Consensus approach
```
#### Balanced Strategy
```yaml
bmad_multi_llm_config:
strategy: "balanced"
models:
- name: "claude"
weight: 0.4
specializations: ["reasoning", "architecture"]
- name: "gpt4"
weight: 0.3
specializations: ["code_generation", "completion"]
- name: "gemini"
weight: 0.2
specializations: ["data_analysis", "research"]
- name: "deepseek"
weight: 0.1
specializations: ["optimization", "review"]
```
## 3. 🛠️ Development Tool Integration
### IDE Integration
#### VS Code Extension
```javascript
// VS Code extension for BMAD integration
class BMADVSCodeExtension {
constructor() {
this.bmadInterface = new BMADInterface();
}
async activate(context) {
// Register BMAD commands
const commands = [
'bmad.analyzeCode',
'bmad.generateTests',
'bmad.optimizePerformance',
'bmad.refactorCode',
'bmad.generateDocumentation'
];
commands.forEach(command => {
const disposable = vscode.commands.registerCommand(
command,
this.handleBMADCommand.bind(this)
);
context.subscriptions.push(disposable);
});
// Setup real-time code assistance
this.setupRealTimeAssistance();
}
async handleBMADCommand(command, ...args) {
const activeEditor = vscode.window.activeTextEditor;
if (!activeEditor) return;
const document = activeEditor.document;
const selectedText = document.getText(activeEditor.selection);
const result = await this.bmadInterface.processCommand({
command: command,
code: selectedText,
context: await this.getContextInfo(document)
});
await this.applyResult(result, activeEditor);
}
}
```
#### JetBrains Plugin
```kotlin
// JetBrains IDEA plugin for BMAD
class BMADPlugin : ApplicationComponent {
private val bmadService = BMADService()
override fun initComponent() {
// Register BMAD actions
val actionManager = ActionManager.getInstance()
actionManager.registerAction(
"BMAD.AnalyzeCode",
BMADAnalyzeAction(bmadService)
)
actionManager.registerAction(
"BMAD.OptimizeCode",
BMADOptimizeAction(bmadService)
)
// Setup background analysis
setupBackgroundAnalysis()
}
private fun setupBackgroundAnalysis() {
EditorFactory.getInstance().addEditorFactoryListener(
object : EditorFactoryListener {
override fun editorCreated(event: EditorFactoryEvent) {
val editor = event.editor
setupBMADAssistance(editor)
}
}
)
}
}
```
### Git Integration
```python
class BMADGitIntegration:
"""Integrate BMAD with Git workflows"""
def __init__(self, repo_path):
self.repo = git.Repo(repo_path)
self.bmad = BMADSystem()
async def analyze_commit(self, commit_hash):
"""Analyze commit with BMAD intelligence"""
commit = self.repo.commit(commit_hash)
analysis = await self.bmad.analyze_code_changes(
changed_files=commit.stats.files,
diff=commit.diff(),
commit_message=commit.message
)
return {
"quality_score": analysis.quality_score,
"potential_issues": analysis.issues,
"suggestions": analysis.suggestions,
"test_coverage_impact": analysis.test_impact
}
async def generate_commit_message(self, staged_changes):
"""Generate intelligent commit message"""
return await self.bmad.generate_commit_message(
changes=staged_changes,
style="conventional_commits",
include_breaking_changes=True
)
async def review_pull_request(self, pr_number):
"""Automated PR review with BMAD"""
pr_data = await self.get_pr_data(pr_number)
review = await self.bmad.review_pull_request(
pr_data=pr_data,
check_standards=True,
security_scan=True,
performance_analysis=True
)
return review
```
### CI/CD Integration
#### GitHub Actions
```yaml
# .github/workflows/bmad-analysis.yml
name: BMAD Code Analysis
on:
pull_request:
branches: [ main, develop ]
push:
branches: [ main ]
jobs:
bmad-analysis:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Setup BMAD Environment
uses: bmad-system/setup-action@v1
with:
bmad-version: 'latest'
llm-provider: 'claude'
autonomy-level: 'supervised'
- name: Run BMAD Code Analysis
run: |
bmad analyze --comprehensive \
--output-format json \
--quality-gates \
--security-scan \
--performance-check
- name: BMAD Optimization Recommendations
run: |
bmad optimize --analyze-only \
--recommendations-file optimization-report.md
- name: Comment PR with BMAD Results
if: github.event_name == 'pull_request'
uses: bmad-system/comment-action@v1
with:
analysis-file: 'bmad-analysis.json'
optimization-file: 'optimization-report.md'
```
#### Jenkins Pipeline
```groovy
// Jenkinsfile with BMAD integration
pipeline {
agent any
stages {
stage('BMAD Analysis') {
steps {
script {
// Initialize BMAD
sh '''
bmad init --pipeline-mode
bmad configure --llm claude --autonomy supervised
'''
// Run comprehensive analysis
def analysis = sh(
script: 'bmad analyze --comprehensive --json',
returnStdout: true
).trim()
// Parse results
def results = readJSON text: analysis
// Set build status based on quality gates
if (results.quality_score < 0.8) {
currentBuild.result = 'UNSTABLE'
error("BMAD quality gates failed: ${results.quality_score}")
}
}
}
}
stage('BMAD Optimization') {
when {
branch 'main'
}
steps {
sh '''
bmad optimize --execute \
--approve-safe-changes \
--create-optimization-pr
'''
}
}
}
post {
always {
// Archive BMAD reports
archiveArtifacts artifacts: 'bmad-reports/**'
// Publish quality metrics
publishHTML([
allowMissing: false,
alwaysLinkToLastBuild: true,
keepAll: true,
reportDir: 'bmad-reports',
reportFiles: 'quality-report.html',
reportName: 'BMAD Quality Report'
])
}
}
}
```
## 4. 🏢 Enterprise Integration
### Enterprise Architecture Integration
```python
class EnterpriseIntegration:
"""Enterprise-level BMAD integration"""
def __init__(self, enterprise_config):
self.config = enterprise_config
self.bmad = BMADEnterpriseSystem(self.config)
async def setup_enterprise_governance(self):
"""Setup enterprise governance framework"""
governance_config = {
"compliance_frameworks": ["SOX", "GDPR", "ISO27001"],
"approval_workflows": self.config.approval_workflows,
"security_policies": self.config.security_policies,
"audit_requirements": self.config.audit_requirements
}
await self.bmad.governance.configure(governance_config)
async def integrate_with_enterprise_systems(self):
"""Integrate with existing enterprise systems"""
integrations = [
self.integrate_with_ldap(),
self.integrate_with_erp(),
self.integrate_with_monitoring(),
self.integrate_with_security_tools()
]
await asyncio.gather(*integrations)
async def setup_multi_tenant_architecture(self):
"""Setup multi-tenant BMAD deployment"""
tenant_config = {
"isolation_level": "strict",
"data_residency": self.config.data_residency_requirements,
"customization_level": "high",
"scaling_strategy": "auto"
}
await self.bmad.multi_tenant.configure(tenant_config)
```
### SSO Integration
```python
class BMADSSOIntegration:
"""Single Sign-On integration for BMAD"""
def __init__(self, sso_provider):
self.sso_provider = sso_provider
async def configure_saml_integration(self, saml_config):
"""Configure SAML-based SSO"""
return {
"identity_provider": saml_config.idp_url,
"service_provider": "bmad-system",
"attribute_mapping": {
"email": "http://schemas.xmlsoap.org/ws/2005/05/identity/claims/emailaddress",
"name": "http://schemas.xmlsoap.org/ws/2005/05/identity/claims/name",
"roles": "http://schemas.microsoft.com/ws/2008/06/identity/claims/role"
},
"encryption_certificate": saml_config.encryption_cert
}
async def configure_oauth_integration(self, oauth_config):
"""Configure OAuth 2.0 / OpenID Connect"""
return {
"authorization_endpoint": oauth_config.auth_url,
"token_endpoint": oauth_config.token_url,
"userinfo_endpoint": oauth_config.userinfo_url,
"client_id": oauth_config.client_id,
"scopes": ["openid", "profile", "email", "bmad-access"]
}
```
## 5. 📊 Monitoring and Analytics Integration
### Observability Setup
```python
class BMADObservability:
"""Comprehensive observability for BMAD system"""
def __init__(self):
self.metrics_collector = MetricsCollector()
self.trace_collector = TraceCollector()
self.log_aggregator = LogAggregator()
async def setup_monitoring(self, monitoring_config):
"""Setup comprehensive monitoring"""
# Metrics collection
await self.setup_metrics_collection(monitoring_config.metrics)
# Distributed tracing
await self.setup_distributed_tracing(monitoring_config.tracing)
# Log aggregation
await self.setup_log_aggregation(monitoring_config.logging)
# Alerting
await self.setup_alerting(monitoring_config.alerting)
async def create_dashboards(self):
"""Create monitoring dashboards"""
dashboards = [
await self.create_system_health_dashboard(),
await self.create_performance_dashboard(),
await self.create_cost_optimization_dashboard(),
await self.create_quality_metrics_dashboard()
]
return dashboards
```
### Performance Metrics
```python
# Key performance indicators for BMAD system
BMAD_METRICS = {
"development_velocity": {
"features_per_sprint": "gauge",
"story_points_completed": "counter",
"cycle_time": "histogram",
"lead_time": "histogram"
},
"code_quality": {
"bug_density": "gauge",
"code_coverage": "gauge",
"technical_debt_ratio": "gauge",
"maintainability_index": "gauge"
},
"system_performance": {
"response_time": "histogram",
"throughput": "gauge",
"error_rate": "gauge",
"availability": "gauge"
},
"cost_metrics": {
"development_cost_per_feature": "gauge",
"infrastructure_cost": "gauge",
"licensing_cost": "gauge",
"total_cost_of_ownership": "gauge"
}
}
```
## 6. 🔧 Configuration Templates
### Development Environment
```yaml
# bmad-dev-config.yml
bmad_config:
environment: "development"
autonomy_level: "collaborative"
features:
learning: true
optimization: true
quality_gates: true
security_scanning: false
integrations:
ide: "vscode"
git: true
testing_framework: "jest"
constraints:
no_production_changes: true
require_code_review: false
max_file_size_changes: "1000_lines"
```
### Production Environment
```yaml
# bmad-prod-config.yml
bmad_config:
environment: "production"
autonomy_level: "supervised"
features:
learning: true
optimization: true
quality_gates: true
security_scanning: true
compliance_checking: true
integrations:
monitoring: "datadog"
alerting: "pagerduty"
security: "snyk"
constraints:
require_approval: true
security_review_required: true
rollback_capability: true
audit_trail: true
```
### Enterprise Environment
```yaml
# bmad-enterprise-config.yml
bmad_config:
environment: "enterprise"
autonomy_level: "guided"
governance:
compliance_frameworks: ["SOX", "GDPR", "HIPAA"]
approval_workflows: "mandatory"
security_policies: "strict"
enterprise_features:
multi_tenancy: true
sso_integration: true
audit_logging: true
cost_optimization: true
integration_tier: "enterprise"
support_tier: "premium"
```
## 🎯 Integration Best Practices
### 1. Start Small and Scale
- Begin with basic Claude Code integration
- Gradually increase autonomy levels
- Add enterprise features as needed
### 2. Security First
- Always implement proper authentication
- Use secure communication channels
- Regularly audit access and permissions
### 3. Monitor Everything
- Track system performance metrics
- Monitor development velocity improvements
- Measure ROI and cost savings
### 4. Continuous Learning
- Enable BMAD learning features
- Regularly review and adjust configurations
- Share learnings across teams
### 5. Compliance Awareness
- Understand regulatory requirements
- Configure appropriate compliance frameworks
- Maintain audit trails
This integration guide provides the foundation for successfully implementing the Enhanced BMAD System in any environment or workflow.
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