Next‑Gen SoV

Appendix B. Practical KPIs & Telemetry Templates

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Jason St George. "Appendix B. Practical KPIs & Telemetry Templates" in Next‑Gen Store of Value: Privacy, Proofs, Compute. Version v1.0. /v/1.0/read/appendix/b-telemetry-templates/

Appendix B: Practical KPIs & Telemetry (Templates)

This appendix provides a practical checklist of key performance indicators and telemetry metrics organized by operational domain. These templates support the VerifyPrice, VerifyReach, and VerifySettle observability regime described in the main text.

Prover markets:

  • Queue depth, clearing price per proof type, cancellation rates, p50/p95 VerifyPrice.

Compute consensus pilots:

  • Matmul throughput (GFLOPs/s), verifier cost ratio, invalid-work rejection rate under adversarial load.

Privacy settlement:

  • Atomic swap success %, time-to-finality, stuck-flow causes, wallet UX friction metrics.

Decentralization & capture risk:

  • Nakamoto coeff. (by stake/hash/prover share); top-N concentration; Gini.
  • Entry latency: time-to-first-proof/mined-block for a new node.
  • Geographic/ASN diversity; % over Tor/VPN; relay/MEV-builder diversity.

Liveness & safety:

  • Reorg/orphan rate; effective finality time (p50/p95); incident MTTR/MTBF.
  • SLA attainment (% proofs/settlements meeting latency/uptime targets).
  • DoS/churn resilience: success % under adversarial load mixes.

Verify/produce economics:

  • Verifier cost ratio (verify/produce) by workload; energy per proof/inference.
  • Hardware mix & utilization (GPU/CPU/ASIC) vs. throughput; cost/FLOP ($/GFLOP-verified).
  • Failure taxonomy: prover faults, invalid proofs, circuit timeouts.

Privacy rails health:

  • Anonymity-set size & churn (shielded pool/epoch); linkability regressions found.
  • Swap slippage & fees (p50/p95); cross-venue route diversity; K-fail root causes.
  • UX friction: successful first-run rate, steps/clicks to complete, abandonment rate.

Bridges & cross-chain settlement:

  • Atomicity violations (0-conf leaks, partial completes); retry rate; liquidity depth per route.
  • Watchtower/guardian coverage; light-client verification share vs. multisig.

Provenance & policy demand:

  • C2PA attach rate, strip rate by platform; “verified views” share.
  • Proof volume indexed to policy milestones (EU AI Act dates); % budgeted vs. ad-hoc spend.

Security & abuse:

  • Sybil detection hit rate; staking/miner collusion alerts; MEV/censorship events.
  • Key/attestation hygiene: validator/prover key rotations, slashing/penalties.

Token & issuance telemetry:

  • Realized issuance vs. schedule; fee/burn coverage of security budget; % rewards tied to useful work.
  • Velocity vs. locked/collateralized supply; SoV signals (holder age bands, exchange outflows).

Customer success:

  • Enterprise proof spend: $/month, SLA breaches, churn; Net Proof Retention (NPR).
  • Time-to-integration (SDK→prod); support tickets per 1k proofs/settlements.

Hardware honesty:

  • Share of receipts tied to open or sampled hardware profiles (by workload and volume).
  • Lot-sampling coverage: percentage of lots and devices subject to destructive audits (SEM/optical imaging, side-channel tests), and maximum time since the last audit per profile.
  • Incidents and deprecations: count and severity of profile-level compromises, time-to-deprecation, and migration progress away from affected profiles.

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