Scaling and Deployment

This page is operational guidance for running Arkade Intents at volume: what the relay layer can absorb, where the real limits are, and how relays, solvers, and applications should deploy. It describes deployment choices, not new wire behavior — the wire contract remains the RFQ protocol, and directions that would change it are collected in Future Work.

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The Relay Is Not the Bottleneck

An addressed swap costs four to six relay events of roughly a kilobyte each: request, quote, and best-effort status. Funding, filling, and claiming never touch the relay. Under an aggressive profile — every user swapping twice a day, all cross-corridor, peak traffic ten times the average: Concurrent sockets assume connect-on-demand clients: they track active negotiations — swaps per second times the ~30-second session — not user count. A single production-grade relay ingests thousands of events per second and holds hundreds of thousands of sockets. Cryptography sits three orders of magnitude below the line: one solver core clears several hundred full verify-decrypt-price-sign cycles per second with generous overhead. The ephemeral negotiation kinds also mean the relay stores nothing for the hot path — an expired negotiation leaves no disk behind.

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What Binds First

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Deployment Guidance

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Relays

Run dedicated RFQ relays, not general-purpose public ones — the conclusion every production machine-to-machine Nostr protocol reached:

• Gate reads and writes with NIP-42 AUTH, and serve a p-tagged addressed event only to its tagged recipient — this also stops the who-quotes-whom graph from being public.
• Require authors, #p, or #t on every subscription; reject open-ended queries.
• Rate-limit per pubkey and source address in the relay’s write policy.
• Run at least two independent operators, geo-spread and mirrored. Publish addressed traffic to two or more relays and deduplicate by event id — the working defense against a relay selectively delaying one solver’s quotes to steer flow.

Solver cards already carry the relay list per rendezvous, so all of this is deployment policy, not a wire change.

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Solvers

• Hold persistent, backoff-managed connections to the transaction stream, and reconcile from the indexer after every gap — the stream replays nothing. Alert on gap-minutes: that is capital at risk, not UX.
• Treat price-cache freshness as a pricing decision. Quote risk scales with feed staleness plus the validity window; shortening either is worth orders of magnitude more than any network optimization (see the arithmetic below).
• Shed load with rfq_refusal — it is penalty-free and already in the wire. Signed refusals are also attribution: applications can keep per-solver fill and refusal statistics as a selection input.
• Refresh price feeds on a timer, never synchronously on an unauthenticated event.

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Applications

• Connect on demand and hold nothing open between swaps. The protocol was built for it: correlation by RFQ identifier across reconnects, best-effort status, contract and destination-network evidence authoritative.
• Follow the transport requirements, and deduplicate by event id — multi-relay publication delivers duplicates by design.
• Warm the relay connection when the swap UI opens. A cold cross-continent handshake costs 200–330 ms — the largest avoidable latency in the flow, fixed by connection timing, not server placement.

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Co-Location

The answer splits by how the fill is won.

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Quoted routes: proximity is noise

Every quantity a datacenter removes is 100–1000× smaller than the protocol’s own time constants — validity windows of tens of seconds, price caches of seconds, claim headroom and refund horizons of hours: The economics agree. A quote is a free option for the user across feed staleness plus the validity window — roughly 45 seconds at reference defaults, costing a solver several basis points of break-even spread at typical BTC volatility. Full co-location trims about 0.2 s of that window, worth about 0.01 bps. Cutting the price cache from 15 s to 1 s is worth about 0.8 bps — eighty times more — and tightening the validity window from 30 s to 10 s another ~1.6 bps. Where proximity matters for pricing, it is solver to price feed and hedging venue, not solver to relay or user.

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Raced fills: proximity is real

An intra-Arkade swap is filled by whichever solver spends the funded contract first, discovered from the transaction stream — a pure latency race, and cancellation races the fill the same way. Solver-to-arkd latency decides who wins, so solver fill infrastructure will rationally sit near the operator. Published-request bidding is a milder race for the application’s selection — one more argument for bounded panels and deadline-based selection over speed.