Load or define data
Schema:
components — id (Mermaid-safe), name, dims (pillar names), maturity (0–5) or dimScores, optional reason, optional code (string), codeLanguage (e.g. python). edges — from, to (component ids). workflows — id, label, nodes (component ids). Optional groups — [{ id, name, nodes: [component ids] }] for Level 1/2. Optional codeSnippets — { "componentId": "code string" }. Level 4 (Code) shows snippets for components that have code or appear in codeSnippets.
0
Live requests (sim)
12 ms
Avg latency (sim)
20%
System pressure
200
Pressure propagation along path
Select a workflow to see how PPI pressure propagates. Pressure increases with simulated traffic (req/s). Nodes are tinted by pillar (dimension) and by pressure when a flow runs.
Performance
Production Readiness
Infrastructure Efficiency
Failure Resilience
PPI scoring (aligned with PPI-F Diagnostic): Reference maturity 0–5 per dimension;
Pressure = (5 − Maturity) / 5. Click a node to see per-dimension maturity and PPI pressure. Run full PPI-F assessment →
Component code
Example flows & interaction
Use the traffic slider to simulate load (live request counter and system pressure update). Select a workflow to animate the path and see pressure propagation. Click any node to see its PPI-F dimensions and maturity. High traffic adds a pulse animation to nodes; flow lines animate faster at higher traffic.
Performance
Latency, throughput, scalability. Pressure sources and invariants.
- API Gateway, services, caches, ETA/Maps
Production Readiness
Deployment, observability, propagation and levers.
- CI/CD, observability, config, health
Infrastructure Efficiency
Cost, utilization, right-sizing, cost-to-serve.
- Message queues, databases, pricing
Failure Resilience
Fault tolerance, fallbacks, circuit breakers.
- Retries, timeouts, failover, SLOs