Hierarchy of ecosystem levels

1) Why formalize levels

• gives agreements (SLO/SLA, API, data schemas, rights/limits);
• eliminates "complex monolith" → accelerates releases and scaling;
• Reduces cost of ownership (clear handoff, transparent error budgets)
• delayet治理 and auditing reproducible.

2) High-level map

1. L0 - Physics/Infrastructure. DC/clouds, L2/L3 networks, GPU/CPU, storage, POP/edge.
2. L1 - Transport/Routing. QUIC/HTTP/3, Latency Mesh, QoS, anycast, balancing.
3. L2 - Data Availability (DA) and Logs. Publications, butches, merkly roots, retention.
4. L3 - Execution and Status. Sequencers, VM/performers, consensus/finality.
5. L4 - Messages and Order. Splints, outbox/inbox, idempotency, causality by key.
6. L5 - Services/Microservices. Billing, catalogs, moderation, orchestrators, analytics.
7. L6 - Domains and Value Modules. Game/content domains, marketplaces, affiliates.
8. L7 - Economics and Incentives. Fares, RevShare, reward pools, insurance.
9. L8 - 治理/Politiki/Pravo. Voting, quorums, rule codification and sunset.
10. L9 - Community/Roles/Reputation. RNFT relationships, R/S, onboarding, appeals.

End-to-end loops: Safety/Compliance, Observability (logs/metrics/trails), Data Governance.

3) Interfaces between levels (contracts)

Each interface captures: APIs/schemas, invariants, SLOs, access policies, events/audits.

• Invariants: MTBF/MTTR, throughput, packet loss.
• SLO: p95 RTT by region, POP availability.
• Access: ABAC by role, egress limits.

• Invariants: guarantor of delivery to DA, publication windows.
• SLO: batch finalization ≤ N × T _ block, via input ≥ X GB/h.

• Invariants: immutability, hashes/roots, order of batches.
• SLO: reorg rate≈0, challenge windows documented.

• Invariants: strict-order per key, idempotence, deadup.
• SLO: out-of-order ≤ 10⁻⁶/soobshch.

• Invariants: event schemas, versions, retrai contract.
• SLO: success ≥ 99. 9–99. 99% per QoS.

• Invariants: domain APIs, business rule validators, migrations.
• SLO: backward compatibility ≥ X months, migrations with feature-flags.

• Invariants: measurability of value (NetRev, margin, Cost-to-Serve).
• SLO: calculation of payments ≤ T, accuracy ≥ 99. 95%.

• Invariants: transparent formulas, right of appeal.
• SLO: SLA propozala→apruva ≤ time, audit decision trail.

• Invariants: R/S vote modifiers, RNFT rights/penalties.
• SLO: TTC appeals ≤ T, publication of cadence reports.

4) Level invariants (minimum requirements)

Security: signatures/keys, immutable logs, integrity control.
Order/Finality: strictly by key; consideration of challenge windows.
Privacy/Compliance: DID/VC, ZK threshold proofs, geo/age/sanctions.
Observability: correlation 'x _ msg _ id' through L1...L7; passing events.
Evolution: schema versions, feature-flags, canary/shadow, rollback.

5) Anti-patterns and their medicines

End-to-end monolith: one service "knows everything." → Decomposition by L4/L5, event contracts.
Floating boundaries: "flip" responsibility. SLA → and RACI matrix on interfaces.
Hidden queues: manual retraction without contracts. → Outbox/Inbox + idempotency.
Mixing compliance with business logic: → Compliance Gate as a pass-through layer.
Version chaos: breaking API without migrations. → SemVer + feature flags, sunset procedures.

6) Maturity model

M0 - Spontaneity: monolith, manual processes, no SLO.
M1 - Layers named: base contracts, partial tracing.
M2 - Contracts formalized: events/schemes, error budgets, A/B releases.
M3 - Autonomous domains: independent releases, RNFT rights, R/S, cost-aware routing.
M4 - Total synergy: AI orchestration, inter-chain portability, public otchetnost治理.

Transitions: Each step requires: (1) interface contracts, (2) telemetry, (3) migration plan, (4) chaos tests.

7) Metrics and SLO by level (reference)

L0: MTBF/MTTR, power/cooling SLA, link loss.
L1: p50/p95/p99, TailAmplification(p99/p50), retry%, anycast hit-rate.
L2: DA throughput, finality lag, retention, proof availability.
L3: success/1k, reorg/orphan, deterministic replay, gas/step.
L4: duplicate ratio, out-of-order, DLQ depth, replay success.
L5: error budget burn, deploy success without rollback, p95 API.
L6: domain conversion, rule accuracy, listing/moderation time.
L7: NetRev, margin/message, Cost-to-Serve, payout accuracy.
L8: TTC proposals, share of sunset edits, trace audit.
L9: v治理 participation, R distribution, share of appeals and MTTR on them.

8) Economy between levels

Chargeback chain: who compensates for the incident? L3/L4 → insurance pool (S-pledges) → L7 clearing.
Pricing: L1/L2/L3 - per-req/per-GB; L5 — per-API; L6 — per-value event; L7 - tariffs and RevShare.
QF (Quality Factor): bonus/penalty on payments to providers for SLO.

9) Safety/Compliance (through layer)

Policies: geo, age, sanctions, export/retention.
ZK control: proof of thresholds without disclosure.
Audit: non-replaceable logs, merkly snapshots, external cadence audit.
Incidents: Stop taps, quorums, post mortems and signatures.

10) Observability and dashboards

Layer Overview: SLO/SLA heat map by level and region.
Interface Health: errors/latency at boundaries (Lk↔Lk+1).
Tail & Finality: p95/p99, finality lag, DLQ/replay.
Economy Panel: Cost-to-Serve, margin/event, QF by provider.
Governance: queue of proposals, apruva time, versions of scales.
Compliance: locks/red areas, reporting to regulator.

11) Implementation playbook

1. Inventory of the current architecture. Overlay services on the L0...L9.
2. Defining interfaces. For each pair of Lk↔Lk+1: API/schemes/SLO/audit.
3. End-to-end tracing. Embed 'x _ msg _ id' and event passports.
4. Data contracts. Schemas, versions, migrations (SemVer + feature-flags).
5. Safety and compliance circuits. DID/VC, ZK, export policies.
6. Economics. Tariffs per level, QF, insurance fund, RNFT rights.
7. 治理. Change procedures, quorums, sunset clauses, public reports.
8. Chaos/Game-days. DA/bridge/POP drop, price shocks, geo blocks.
9. Pilot. One domain → inter-chain escalation → scaling.
10. Retro-calibration. According to SLO/Economics/Incidents.

12) KPIs of successful hierarchization

Operating system: reduced MTTR/interface incidents, increased deploy-no-rollback.
Quality: p95/p99 ↓ with stable throughput; DLQ depth ↓, replay success ↑.
Economy: Cost-to-Serve ↓, margin/event ↑, predictability of payments.
治理: TTC props ↓, share of sunset edits on time ↑, transparency.
Compliance: 100% pass geo/age/sanctions, zero critical violations.
Growth: onboarding time of the new domain/ ↓ chain.

13) Delivery checklist

• L0...L9 Card and Layer Owners (RACI)
• Interface contracts (API/Schemas/SLO/Audit) executed
• End-to-end tracing and event passports implemented
• Compliance Gate and ZK circuits are connected
• Versioning/migration policies and feature-flags work
• Strata economics (tariffs/QF/escrow) described and tested
• Level/interface dashboards and alerts are active
• Chaos practices and post-mortems in cadence
• 治理 processes and public reporting established
• Pilot passed, recalibration complete

14) Glossary

DA (Data Availability): data publication/evidence layer.
Finality: irreversible state/transactions.
Outbox/Inbox: guaranteed delivery and idempotence.
RNFT: Relationship/Rights/Limits Contract and KPIs.
R/S: reputation of quality and economic guarantee of responsibility.
QF: multiplier of payments by quality.
Sunset: temporarily editing parameters with auto-rollback.
Tail Amplification: p99/p50 - the strength of the "tail" of delays.

15) The bottom line

The hierarchy of ecosystem levels is an operational map: where the boundaries of responsibility pass, which invariants should not be violated, and how to measure success. With clear interfaces, end-to-end observability, security and an economy-driven ecosystem, the ecosystem becomes scalable, predictable and sustainable - from hardware and routing to domain values, i治理 incentives.