claude-skills/engineering-team/skills/tech-stack-evaluator/references/workflows.md

Technology Evaluation Workflows

Step-by-step workflows for common evaluation scenarios.

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Table of Contents

• Framework Comparison Workflow
• TCO Analysis Workflow
• Migration Assessment Workflow
• Security Evaluation Workflow
• Cloud Provider Selection Workflow

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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

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

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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

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

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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

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

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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

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

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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

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.

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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)