# Technology Evaluation Workflows Step-by-step workflows for common evaluation scenarios. --- ## Table of Contents - [Framework Comparison Workflow](#framework-comparison-workflow) - [TCO Analysis Workflow](#tco-analysis-workflow) - [Migration Assessment Workflow](#migration-assessment-workflow) - [Security Evaluation Workflow](#security-evaluation-workflow) - [Cloud Provider Selection Workflow](#cloud-provider-selection-workflow) --- ## Framework Comparison Workflow Use this workflow when comparing frontend/backend frameworks or libraries. ### Step 1: Define Requirements 1. Identify the use case: - What type of application? (SaaS, e-commerce, real-time, etc.) - What scale? (users, requests, data volume) - What team size and skill level? 2. Set priorities (weights must sum to 100%): - Performance: ____% - Scalability: ____% - Developer Experience: ____% - Ecosystem: ____% - Learning Curve: ____% - Other: ____% 3. List constraints: - Budget limitations - Timeline requirements - Compliance needs - Existing infrastructure ### Step 2: Run Comparison ```bash python scripts/stack_comparator.py \ --technologies "React,Vue,Angular" \ --use-case "enterprise-saas" \ --weights "performance:20,ecosystem:25,scalability:20,developer_experience:35" ``` ### Step 3: Analyze Results 1. Review weighted total scores 2. Check confidence level (High/Medium/Low) 3. Examine strengths and weaknesses for each option 4. Review decision factors ### Step 4: Validate Recommendation 1. Match recommendation to your constraints 2. Consider team skills and hiring market 3. Evaluate ecosystem for your specific needs 4. Check corporate backing and long-term viability ### Step 5: Document Decision Record: - Final selection with rationale - Trade-offs accepted - Risks identified - Mitigation strategies --- ## TCO Analysis Workflow Use this workflow for comprehensive cost analysis over multiple years. ### Step 1: Gather Cost Data **Initial Costs:** - [ ] Licensing fees (if any) - [ ] Training hours per developer - [ ] Developer hourly rate - [ ] Migration costs - [ ] Setup and tooling costs **Operational Costs:** - [ ] Monthly hosting costs - [ ] Annual support contracts - [ ] Maintenance hours per developer per month **Scaling Parameters:** - [ ] Initial user count - [ ] Expected annual growth rate - [ ] Infrastructure scaling approach ### Step 2: Run TCO Calculator ```bash python scripts/tco_calculator.py \ --input assets/sample_input_tco.json \ --years 5 \ --output tco_report.json ``` ### Step 3: Analyze Cost Breakdown 1. Review initial vs. operational costs ratio 2. Examine year-over-year cost growth 3. Check cost per user trends 4. Identify scaling efficiency ### Step 4: Identify Optimization Opportunities Review: - Can hosting costs be reduced with reserved pricing? - Can automation reduce maintenance hours? - Are there cheaper alternatives for specific components? ### Step 5: Compare Multiple Options Run TCO analysis for each technology option: 1. Current state (baseline) 2. Option A 3. Option B Compare: - 5-year total cost - Break-even point - Risk-adjusted costs --- ## Migration Assessment Workflow Use this workflow when planning technology migrations. ### Step 1: Document Current State 1. Count lines of code 2. List all components/modules 3. Identify dependencies 4. Document current architecture 5. Note existing pain points ### Step 2: Define Target State 1. Target technology/framework 2. Target architecture 3. Expected benefits 4. Success criteria ### Step 3: Assess Team Readiness - How many developers have target technology experience? - What training is needed? - What is the team's capacity during migration? ### Step 4: Run Migration Analysis ```bash python scripts/migration_analyzer.py \ --from "angular-1.x" \ --to "react" \ --codebase-size 50000 \ --components 200 \ --team-size 6 ``` ### Step 5: Review Risk Assessment For each risk category: 1. Identify specific risks 2. Assess probability and impact 3. Define mitigation strategies 4. Assign risk owners ### Step 6: Plan Migration Phases 1. **Phase 1: Foundation** - Setup new infrastructure - Create migration utilities - Train team 2. **Phase 2: Incremental Migration** - Migrate by feature area - Maintain parallel systems - Continuous testing 3. **Phase 3: Completion** - Remove legacy code - Optimize performance - Complete documentation 4. **Phase 4: Stabilization** - Monitor production - Address issues - Gather metrics ### Step 7: Define Rollback Plan Document: - Trigger conditions for rollback - Rollback procedure - Data recovery steps - Communication plan --- ## Security Evaluation Workflow Use this workflow for security and compliance assessment. ### Step 1: Identify Requirements 1. List applicable compliance standards: - [ ] GDPR - [ ] SOC2 - [ ] HIPAA - [ ] PCI-DSS - [ ] Other: _____ 2. Define security priorities: - Data encryption requirements - Access control needs - Audit logging requirements - Incident response expectations ### Step 2: Gather Security Data For each technology: - [ ] CVE count (last 12 months) - [ ] CVE count (last 3 years) - [ ] Severity distribution - [ ] Average patch time - [ ] Security features list ### Step 3: Run Security Assessment ```bash python scripts/security_assessor.py \ --technology "express-js" \ --compliance "soc2,gdpr" \ --output security_report.json ``` ### Step 4: Analyze Results Review: 1. Overall security score 2. Vulnerability trends 3. Patch responsiveness 4. Compliance readiness per standard ### Step 5: Identify Gaps For each compliance standard: 1. List missing requirements 2. Estimate remediation effort 3. Identify workarounds if available 4. Calculate compliance cost ### Step 6: Make Risk-Based Decision Consider: - Acceptable risk level - Cost of remediation - Alternative technologies - Business impact of compliance gaps --- ## Cloud Provider Selection Workflow Use this workflow for AWS vs Azure vs GCP decisions. ### Step 1: Define Workload Requirements 1. Workload type: - [ ] Web application - [ ] API services - [ ] Data analytics - [ ] Machine learning - [ ] IoT - [ ] Other: _____ 2. Resource requirements: - Compute: ____ instances, ____ cores, ____ GB RAM - Storage: ____ TB, type (block/object/file) - Database: ____ type, ____ size - Network: ____ GB/month transfer 3. Special requirements: - [ ] GPU/TPU for ML - [ ] Edge computing - [ ] Multi-region - [ ] Specific compliance certifications ### Step 2: Evaluate Feature Availability For each provider, verify: - Required services exist - Service maturity level - Regional availability - SLA guarantees ### Step 3: Run Cost Comparison ```bash python scripts/tco_calculator.py \ --providers "aws,azure,gcp" \ --workload-config workload.json \ --years 3 ``` ### Step 4: Assess Ecosystem Fit Consider: - Team's existing expertise - Development tooling preferences - CI/CD integration - Monitoring and observability tools ### Step 5: Evaluate Vendor Lock-in For each provider: 1. List proprietary services you'll use 2. Estimate migration cost if switching 3. Identify portable alternatives 4. Calculate lock-in risk score ### Step 6: Make Final Selection Weight factors: - Cost: ____% - Features: ____% - Team expertise: ____% - Lock-in risk: ____% - Support quality: ____% Select provider with highest weighted score. --- ## Best Practices ### For All Evaluations 1. **Document assumptions** - Make all assumptions explicit 2. **Validate data** - Verify metrics from multiple sources 3. **Consider context** - Generic scores may not apply to your situation 4. **Include stakeholders** - Get input from team members who will use the technology 5. **Plan for change** - Technology landscapes evolve; plan for flexibility ### Common Pitfalls to Avoid 1. Over-weighting recent popularity vs. long-term stability 2. Ignoring team learning curve in timeline estimates 3. Underestimating migration complexity 4. Assuming vendor claims are accurate 5. Not accounting for hidden costs (training, hiring, technical debt)