Draft: Module 4 - Evolutionary Architecture

Outcome-driven design, fitness evaluation, and architectural health.

Overview

This module teaches how to use Sruja for evolutionary architecture—designing systems that can adapt to changing requirements while maintaining architectural integrity.

Lessons

Lesson 1: Fitness Functions & Health Metrics

How to define and measure architectural fitness

• What are fitness functions
• Defining outcome-driven requirements
• Health metrics dashboard
• Automated fitness evaluation

Lesson 2: Architectural Health Scoring

Quantifying system health over time

• Health score components
• Trend analysis
• Threshold configuration
• Reporting patterns

Lesson 3: Continuous Evolution Workflow

Integrating evolution into development workflow

• Maturation phases (Instrumentation → Context Hints → Infra Discovery)
• Evolution command and reporting
• Drift detection and resolution
• Autonomous optimization loops

Learning Outcomes

• ✅ Define fitness functions for architectural outcomes
• ✅ Configure and interpret health metrics
• ✅ Use Sruja evolution commands
• ✅ Implement continuous architectural health monitoring

Prerequisites

• Completed Production Architecture Modules 1-3
• Familiarity with Sruja validation and policies
• Understanding of observability concepts

Estimated Time

2-3 hours

Raw Thoughts from Analysis

v0.42.0 Features to Cover:

• sruja evolution - outcome-driven evolutionary architectures
• sruja health / health status dashboard
• fitness evaluation
• enterprise graph health metrics

Related Concepts:

• Outcome-driven architecture
• Architectural fitness functions
• Health metrics aggregation
• Evolutionary vs traditional architecture
• Sruja maturation phases (Instrumentation, Context Hints, Infra Discovery)

Lesson Ideas:

1. Fitness Functions & Health Metrics

   • Define fitness function: fitness(cpu_utilization < 80%, availability > 99.9%, latency_p99 < 200ms)
   • Show how to express these in Sruja
   • Demo health scoring dashboard
   • Hands-on: Define fitness for a sample system

2. Architectural Health Scoring

   • Graph health metrics from v0.42.0
   • Community detection (from v0.41.0)
   • Threshold configuration
   • Health trend visualization

3. Continuous Evolution

   • Sruja maturation phases workflow
   • Using sruja evolution command
   • Drift detection and --fix
   • Autonomous optimization loop pattern (from agentic memory)