Network Health Assessment

1) What is "network health" and why measure it

Network health is the state of an ecosystem's ability to consistently deliver target service levels (SLOs), security, cost efficiency, and predictable evolution during spikes, failures, and changes in demand.

• early identification of degradation and risks;
• fact-base management of tariffs, quotas, incentives and priorities;
• transparency for participants (nodes, providers, operators, creators, affiliates);
• podpitka治理 solutions and post-mortems.

2) Health domain map

1. Performance and availability: latency/throughput, error rate, finality, queues.
2. Robustness and robustness: MTBF/MTTR, backpressure, QoS degradation.
3. Security and trust: authentication/authorization, integrity incidents, slashing, fraud.
4. Economics and efficiency: cost-to-serve, margin/message, resource equity.
5. 治理 and processes: speed of parameter convergence, recoilless releases, reporting discipline.
6. Compliance and privacy: geo/age, sanctions, data storage/deletion, ZK proofs.

3) Taxonomy of metrics (reference)

3. 1 Performance (per QoS class)

Latency p50/p95/p99, TailAmplification = p99/p50.
Throughput (msgs/s, tx/s, GB/s DA), queue depth, consumer lag.
Success rate, timeouts/retries%, duplicate ratio, out-of-order%.
Finality lag (x-chain/bridge), challenge-окна.

3. 2 Reliability

SLA breaks/1k events, MTBF/MTTR, flap-rate balancers.
Backpressure recovery time, DLQ depth, replay success%.

3. 3 Safety

Integrity/theft incidents, suspicious signals/1k,

False Accept/Reject in compliance, key/signature collisions.
Slashing events, oracle discrepancies, MEV exposure (if applicable).

3. 4 Economics

Cost/Req, Cost/GB DA, margin/message, revenue/byte,

NRR/GRR, ARPU/ARPPU, share of repeat revenue,

FairnessIndex (Jain) по CPU/GPU/IO/egress, noisy neighbor index.

3. 5治理 and Processes

Success of releases without rollback, timing of approvals,

speed-tuning (convergence), coverage with benchmarks.

3. 6 Compliance and privacy

Proportion of verified DID/VC, geo/age locks,

response time to the regulator's request, storage/deletion incidents.

4) Composite "Network Health Index" (SSI)

IZS is a robust composite of sub-indices: Performance (PFI), Reliability (RLI), Security & Trust (STI), Economics (ECI), Governance (GVI), Compliance (CFI).

• robust z-score or robust min-max according to [P5, P95]; EWMA smoothing; tail winsorization.

[
\text{SubIndex}k=\sum_i w{k,i},\hat m_{k,i},\quad
\text{ИЗС}=\sum_k W_k,\text{SubIndex}k,\ \sum W_k=1,
]

where weights (W_k) and (w {k, i}) are stored in the Governance Registry and change according to the sunset procedure.

• Green: IS ≥ 0. 70 - growth of quotas/volumes, quality bonuses.
• Yellow: 0. 50–0. 70 - spot tuning, investigations.
• Red: <0. 50 - stopcocks, lowering limits, focus on MTTR/correction.

5) Threshold SLOs and gates

• Q4 API: success ≥ 99. 99%, p95 ≤ 200 ms, DLQ = 0.
• Q3 Messaging: violation of the order of ≤ 10⁻⁶/soobshch., p95 ≤ 500 ms.
• Bridge/Finality: false confirmations = 0; MTTR abnormalities ≤ 1 h.
• DA: final ≤ 3 × T _ block; throughput ≥ X GB/ч.
• Batch/Stream: window T fits with a margin ≥ 20%; lag ≤ 2×window.
• Security: integrity incidents = 0; FPR/FNR in the hallways.

Violation of SLO → automatic triggers (§ 8).

6) Data collection, quality and protection

Idempotence/dedup: ULID/trace, seen-tables with TTL.
E2E tracing: correlation 'x _ msg _ id' through domains/bridges/DA.
Anti-gaming: blind-run windows, hidden control tasks, synthetic samples.
Privacy: DID/VC, selective disclosures, ZK threshold proofs.
Reliability: event signatures, batch mercification, log audit.

7) Dashboards of "health"

Network Health Overview: SIS and sub-indices, contribution of metrics.
Latency & Tail: pXX, TailAmplification heatmap by domain/route.
Reliability Panel: SLA-брейки, MTTR, DLQ/Replay, backpressure.
Security & Trust: suspicious signals, slashing, oracle discrepancies.
Economy: Cost-to-Serve, margin/message, fairness on resources.
Finality & Bridge Risk: finality lag, challenge, bridge incidents.
Compliance: geo-blocks, age, reporting, regulator requests.

8) Policy hooks

SLO-gate: error budget overrun → ↓ quotas for Q0/Q1, priority Q4; enabling circuit-breakers.
Tariffs: TailAmplification growth with stable demand → ↑ price for "noisy" flows; sustainable → quality ↓ take-rate.
Risks: surge in Security/Compliance incidents → fail-closed, increase in S-pledges.
Incentives: domains with sustained PFI/RLI → volume/visibility bonus; violators - fines/clawback.
Релизы: regression detector → auto rollback/feature flag.

9) Incident management

1. Detection: p95/finality/error/cost anomalies.
2. Classification: Integrity/Availability/Performance/Compliance.
3. Isolation: trip per-route, queue drainage, limits, manual quorum.
4. Compensation: from the insurance pool according to RNFT policies.
5. Post-mortem: public report, signature update, adjustment of weights/limits.

10) Relationship to contracts and roles

RNFT rights: individual SLOs/limits for nodes/providers/affiliates.
R-reputation: modifier of access/votes and prices; sustainable → quality ↓ S requirements.
S-pledges: coverage of incidents, slashing in case of violations.

11) Formulas and landmarks

SuccessRate = 1 − (timeouts + errors)/requests

TailAmplification = p99/p50 (zadayet治理 corridors)

Cost/Req = Σ (resource × bid )/successful _ requests

FairnessIndex (Jain) = (Σ x) ²/( n· Σ x ²) by quota/resource

Headroom = (cap − current)/cap, FinalityScore = f(lag, variance, reorgs)

12) Implementation playbook (in steps)

1. Mapping of critical paths and QoS classes; SLO negotiation.
2. Telemetry scheme: tracing, metrics, policy logs, event passports.
3. Normalization: robust scales, EWMA windows, winsorization.
4. IZS v1. 0: starting weights, zone thresholds, sunset procedures.
5. Dashboards and alerts: error budgets, policy hooks triggers.
6. Benchmarks and chaos: regular runs, failover exercises.
7. Incidents: post-mortem templates, insurance fund, RNFT fines.
8. 治理: SLO/weights/corridors change process, quarterly revisions.
9. Automation: bundling with routing, quotas, tariffs and release gates.
10. Pilot → scaling: from one domain to a multichain.

13) KPI of the "health" program

Percentage of paths with green SLO ≥ X%; MTTR median ≤ Z h.
Decrease in TailAmplification by Δ at stable throughput.
Decrease in Cost/Req and DLQ depth without deterioration in success rate.
NRR/GRR growth with unchanged or better security.
Timeliness of reports (TTC report ≤ Y hours), coverage with benchmarks ≥ K%.
Fairness: FairnessIndex in the corridor, decline in "noisy neighbor" incidents.

14) Delivery checklist

• Defined SLOs/SLAs by QoS class and domain
• Implemented E2E tracing, idempotency and deadup
• Robust normalizations and s治理-weights were introduced
• Set up alerts, error budgets and auto triggers
• Performance/Reliability/Security/Economy/Compliance dashboards available
• Benchmarks and chaos runs work; post-mortems described
• Integrated RNFT, R/S policies and insurance fund
• Regular public report and balance revisions established

15) Glossary

IS: a composite of network health from sub-indices.
SLO/SLA: target/contractual service levels.
Error budget - The allowed error rate before reactions.
TailAmplification: delay tail amplification.
DLQ/Replay: Quarantine/Reprocessing.
Sunset procedure: temporary parameter changes with auto-rollback.

16) The bottom line

Network health assessment is not a "hindsight" report, but an operational control loop: robust metrics → composites → threshold SLOs → automatic actions → public reporting i治理. Such a system makes the ecosystem predictable, shock-resistant and honest for all roles - from nodes and providers to creators and operators.