Implementation Strategy Recommendations

Based on organizational profiles:
# Decision framework implementation

class ToolSelectionFramework:
    def __init__(self, org_profile: Dict):
        self.org_profile = org_profile
        self.weights = self.define_weights()
        
    def define_weights(self) -> Dict:
        """Define importance weights based on org type"""
        if self.org_profile['type'] == 'startup':
            return {
                'cost': 0.4,
                'ease_of_use': 0.3,
                'features': 0.2,
                'support': 0.1
            }
        elif self.org_profile['type'] == 'enterprise':
            return {
                'cost': 0.1,
                'ease_of_use': 0.2,
                'features': 0.3,
                'support': 0.4
            }
        else:  # mid-market
            return {
                'cost': 0.25,
                'ease_of_use': 0.25,
                'features': 0.25,
                'support': 0.25
            }
    
    def score_tools(self) -> Dict:
        """Score each tool based on organizational needs"""
        trivy_scores = {
            'cost': 10,  # Free
            'ease_of_use': 7,  # Simple but requires setup
            'features': 6,  # Good but basic
            'support': 4   # Community only
        }
        
        snyk_scores = {
            'cost': 4,  # Paid
            'ease_of_use': 9,  # Excellent UX
            'features': 10,  # Comprehensive
            'support': 9   # Commercial support
        }
        
        # Calculate weighted scores
        trivy_total = sum(
            trivy_scores[factor] * self.weights[factor] 
            for factor in self.weights
        )
        
        snyk_total = sum(
            snyk_scores[factor] * self.weights[factor] 
            for factor in self.weights
        )
        
        return {
            'trivy': trivy_total,
            'snyk': snyk_total,
            'recommendation': 'Trivy' if trivy_total > snyk_total else 'Snyk',
            'confidence': abs(trivy_total - snyk_total) / max(trivy_total, snyk_total)
        }
    
    def generate_implementation_plan(self) -> Dict:
        """Generate specific implementation recommendations"""
        scores = self.score_tools()
        
        if scores['recommendation'] == 'Trivy':
            return {
                'primary_tool': 'Trivy',
                'implementation_steps': [
                    'Deploy Trivy in CI/CD pipelines',
                    'Set up Trivy-Operator for Kubernetes',
                    'Establish vulnerability database update schedule',
                    'Create custom policies for severity thresholds',
                    'Integrate with existing monitoring'
                ],
                'consider_snyk_for': [
                    'Developer IDE integration',
                    'Automated PR generation',
                    'Advanced reporting needs'
                ]
            }
        else:
            return {
                'primary_tool': 'Snyk',
                'implementation_steps': [
                    'Roll out Snyk CLI to development teams',
                    'Integrate with source control',
                    'Configure continuous monitoring',
                    'Set up automated fix PRs',
                    'Establish security policies'
                ],
                'consider_trivy_for': [
                    'Air-gapped environments',
                    'High-volume batch scanning',
                    'Cost optimization'
                ]
            }