If I Migrate My Rollup From Single Proof to Continuous Aggregation, How Do I Keep Auditability and Instant Finality?

Summary: Moving from “one batch → one proof” to continuous proof aggregation cuts L1 costs and unlocks higher proving throughput. Here’s a concrete, 2026‑ready playbook to preserve end‑to‑end auditability and keep sub‑second UX finality while you upgrade contracts, DA, prover ops, and sequencing.

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Executive context: why teams are migrating in 2025–2026

• Ethereum’s Pectra mainnet upgrade (May 7, 2025) added BLS12‑381 precompiles (EIP‑2537), repriced calldata (EIP‑7623), and raised blob throughput (EIP‑7691), materially changing the cost/perf tradeoffs for verification and DA. (blog.ethereum.org)
• Fusaka (Dec 3, 2025) activated PeerDAS (EIP‑7594) and introduced “Blob‑Parameter‑Only” (BPO) forks that already lifted blob target/max to 10/15 (Dec 9, 2025) and 14/21 (Jan 7, 2026), expanding the blob budget for rollups. (blog.ethereum.org)
• Verification is decoupling from the EVM: decentralized proof‑verification layers (e.g., Aligned AVS on EigenLayer) batch/aggregate results and attest on L1, cutting per‑proof gas 90–99% and lifting throughput to thousands of proofs/sec. (blog.alignedlayer.com)
• Sequencing UX is converging on “instant” preconfirmations: OP Stack chains are rolling out Flashbots’ infrastructure (e.g., Flashblocks/Rollup‑Boost) for ~200 ms confirmations while preserving L1 settlement. (coindesk.com)

The upshot: continuous aggregation (recursively composing many proofs into a rolling, verifiable chain) lets you prove more, pay less, and post less often—if you engineer for auditability and UX finality from day one.

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Definitions we’ll use

• Single‑proof model: each L2 batch/block has an L1‑verified proof.
• Continuous aggregation: you produce proofs for small steps (blocks/batches), recursively fold them into a rolling accumulator, and periodically settle a single proof that attests to a contiguous L2 range.

Cryptographically, you can realize this with folding/IVC (e.g., Nova/HyperNova) or recursion inside zkVMs (e.g., SP1), then optionally wrap into a succinct outer proof for L1. (eprint.iacr.org)

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Goal 1 — Preserve auditability after you stop posting one proof per batch

Auditability means any third party can: (a) reconstruct L2 from on‑chain data, and (b) verify that a posted proof (aggregated or not) corresponds to exactly the stated L2 block range and data.

Here’s how to keep that property when you aggregate continuously.

1. Publish an “audit chain” of per‑batch commitments in L1 events and inside the recursive proof

• For every L2 block i, emit an L1 event with:
  • batch_index i
  • l2_block_hash, tx_data_commitment (e.g., Merkle/KZG root of transactions or state diff)
  • a rolling accumulator root A_i = H(A_{i-1} || l2_block_hash || tx_root || i)
• Make the aggregated proof’s public inputs include A_start, A_end, and the exact [L2_start, L2_end] range. The verifier contract stores a mapping of proven intervals and accumulator edges so auditors can match event logs to the proved range.
  This gives auditors two check paths: (1) replay L2 from DA and recompute A_end, or (2) spot‑check inclusion of any batch in the accumulator via logged commitments.

1. Keep DA genuinely public and reconstructible

• Prefer Ethereum blobs (EIP‑4844/PeerDAS) for rollup data; blob size is 128 KiB, retention ≈18 days. PeerDAS allows higher throughput without overburdening nodes, and BPO forks are already scaling target/max blobs beyond 2025’s 6/9. Budget blob posting cadence so every batch’s data is in L1 blobspace during your proving window. (eips.ethereum.org)
• With Pectra’s EIP‑7691, daily max blob capacity is now materially higher; model your pipeline around the 10/15 and 14/21 BPO steps for Q4 2025–Q1 2026. (eip.fun)
• If you use alt‑DA, wire a DA‑verifier/bridge that attests on L1 to data availability during the challenge window per L2BEAT’s guidance, or you’ll degrade auditability and Stage classification. (forum.l2beat.com)

1. Version your circuits and verifying keys on‑chain

• Store circuit commitments (hash of proving/verifying keys) and bind them to proven intervals. Emit an upgrade event with a grace period; keep the old path live until the new circuits have overlapping coverage. This keeps audits unambiguous across upgrades.

1. Expose “proven range” state for wallets, bridges, and indexers

• Add a solidity API like:
  • function provenRange() returns (uint256 l2Start, uint256 l2End, bytes32 A_end)
  • function isBatchProven(uint256 i) → bool
• Downstream systems can enforce safety policies (e.g., “only release funds when batch i is within a proven range”).

1. Document and test “rebuild from L1” end‑to‑end

• Provide a source‑available node that reconstructs state purely from L1 blobs/commitments per L2BEAT expectations; your auditability depends on this existing and working. (l2beat.com)

Practical note on cost: verifying a Groth16 proof on L1 is roughly a few hundred thousand gas; STARK verifiers can be multiple million gas depending on scheme/parameters. Aggregation reduces on‑chain checks to one verification per aggregate, while recursion amortizes per‑batch verification off‑chain. (blog.alignedlayer.com)

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Goal 2 — Keep (or improve) “instant finality” for users

Users expect sub‑second “it’s done” UX even if cryptographic finality lands minutes later. Under continuous aggregation, you keep that with preconfirmations plus robust settlement.

Four proven patterns:

A) Preconfirmations via decentralized sequencing or BFT committees

• OP Stack + Flashbots: “Flashblocks/Rollup‑Boost” achieve ~200 ms confirmations on Base/Unichain, with verifiable ordering rules and TEE‑backed guarantees; rollout is ecosystem‑wide across the Superchain. (coindesk.com)
• BFT on L2: committee‑based consensus can give single‑slot finality on L2 while proofs/aggregates settle later (e.g., ZKsync’s ChonkyBFT design). (arxiv.org)

B) Preconfirmations authenticated by BLS and verified on‑chain efficiently

• With Pectra’s EIP‑2537 BLS12‑381 precompiles, you can cheaply verify aggregate BLS signatures for preconfirmations or DA attestations directly in Solidity—no big‑integer hacks. This is tailor‑made for “soft finality” committees. (eips.ethereum.org)

C) Robust settlement with bounded disputes

• Optimistic stacks: run permissionless fault proofs so withdrawals and L1 settlement don’t rely on a multisig. OP Mainnet shipped permissionless fault proofs in June 2024; Arbitrum shipped BoLD to permissionless validation on mainnet in Feb 2025—both materially improve state‑validation assurances under preconfirmation UX. (theblock.co)

D) Rate‑limit risk with bonds and slashing

• Back your preconfirmations with an economic bond you can slash for equivocation/reorgs. If you use a verification layer/AVS (e.g., Aligned), lean on restaked security and aggregate attestations to protect low‑latency UX. (blog.alignedlayer.com)

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A reference migration blueprint (minimal downtime, maximum clarity)

Phase 0 — Baseline and SLOs

• Define your SLOs: max proof lag, max time‑to‑prove a given L2 range, preconfirmation latency/error budget, DA posting cadence, and rollback policy.

Phase 1 — Dual‑track proving (shadow mode)

• Stand up the aggregator/recursive pipeline off‑chain. Keep posting single proofs as today, and in parallel generate rolling aggregates and publish their commitments to L1 events. Compare both continuously.

Phase 2 — Verifier contract upgrade

• Add functions:
  • proveRange(proof, publicInputs) → updates (l2Start, l2End, A_end)
  • reportBatch(bytes32 batchCommit, uint256 i) → emits per‑batch commitments (if not already emitted elsewhere)
• Bind verification to circuit version IDs; emit VersionUpgraded events.

Phase 3 — DA pipeline hardening

• Switch all batch data to blobs (EIP‑4844), set max_fee_per_blob_gas guards around Pectra’s EIP‑7691 and Fusaka BPO parameters. Monitor blob base fee and utilization; calibrate for the 6→9→15→21 cadence. Calldata fallback is now pricier post‑EIP‑7623—treat it as emergency relief only. (blog.ethereum.org)

Phase 4 — Preconfirmations rollout

• Introduce BLS‑backed preconfirmation committees and on‑chain verification using EIP‑2537 precompiles; set slashing conditions for double‑sign/ordering violations. If on OP Stack, evaluate Flashblocks/Rollup‑Boost integration to reach ~200 ms UX. (eips.ethereum.org)

Phase 5 — Cutover and deprecation

• Flip settlement to aggregated proofs on a specific L2 block boundary. Keep the single‑proof path hot as a “break glass” fallback for one challenge window. Announce the deprecation schedule publicly.

Phase 6 — Auditability drills and external validation

• Publish a reproducible “state‑from‑L1” script and run monthly public drills: given L1 slot X, reconstruct L2 state root Y and accumulator A_end. Align with L2BEAT’s Stage framework (≥7‑day challenge periods for optimistic paths; source‑available replayers). (forum.l2beat.com)

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Concrete design details that prevent audit and UX regressions

• Proof public inputs
  • start_block, end_block
  • start_accumulator, end_accumulator
  • DA epoch/slot range and KZG commitments for each batch segment
  • circuit_version_id
• Verifier contract storage
  • mapping(uint256 ⇒ bytes32) batchCommitRoot
  • struct Range { uint64 start; uint64 end; bytes32 A_end; uint32 circuitVersion; }
  • Range latest
• Events
  • event BatchCommitted(uint256 indexed i, bytes32 txRoot, bytes32 stateRoot, bytes32 accumulator)
  • event RangeProven(uint256 start, uint256 end, bytes32 A_end, uint32 version)
  • event CircuitVersionUpgraded(uint32 oldVersion, uint32 newVersion)
• Fallback semantics
  • If the aggregator stalls beyond SLA, allow a single‑batch proof to settle a small tail range to free exits, then catch up with recursion later.

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Cost, throughput, and scheduling you can actually budget

• Verification costs
  • Groth16 check: O(10^5)–O(10^6) gas magnitude for a single verifier, often ≈250k with common verifiers; STARK verifiers can be multi‑million gas. Aggregation reduces you to one on‑chain verify per range. (blog.alignedlayer.com)
• DA costs
  • With EIP‑7691 and PeerDAS live, expect structurally more blob capacity; price response is asymmetric now (~+8.2% per “full blob” block vs ~‑14.5% when empty), smoothing spikes. BPO steps to 10/15 and 14/21 increase daily capacity; plan batch sizing and posting intervals accordingly. (eip.fun)
• Proof throughput
  • Modern zkVMs expose native recursion/aggregation; SP1 Hypercube reports “<12 s for 93–99% of mainnet blocks” on commodity GPU clusters, which translates well to continuous rollup proving/aggregation SLAs. (blog.succinct.xyz)
• Off‑chain verification layers
  • If verification, not proving, is your bottleneck, outsourcing to a verification AVS can batch and attest thousands of proofs/sec, then write one aggregated result to L1—cutting queueing latency and gas. (blog.alignedlayer.com)

Rule of thumb for your 2026 budget: in steady state, blob posting and the single aggregated verifier call dominate marginal cost; execution gas of the settlement tx, not blob base fee, often dominates—until short demand spikes. Set max_fee_per_blob_gas with headroom for BPO epochs. (blog.ethereum.org)

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Sequencer and governance considerations you shouldn’t skip

• Decentralize sequencing over time; some shared‑sequencer experiments have wound down (e.g., Astria sunset in Dec 2025), while OP‑Stack+Flashbots infra is shipping at scale. Plan migrations that don’t create a single vendor chokepoint for your instant‑finality path. (unchainedcrypto.com)
• Align your challenge/exit windows with Stage criteria (≥7 days for optimistic paths), avoid relying on a Security Council for non‑emergency liveness, and document forced‑inclusion UX. These materially affect your assessed risk. (forum.l2beat.com)

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Example: converting a zkEVM rollup to continuous aggregation

• Prover side
  • Keep block‑level circuits; add a folding layer (e.g., HyperNova/IVC) that ingests block proofs and updates the accumulator.
  • Periodically SNARK‑wrap the latest IVC state into a succinct L1‑verifiable proof; schedule on a time or size threshold (e.g., every 5–10 minutes or every N blocks).
• L1 contracts
  • Add proveRange() that checks the succinct wrapper, updates the [start,end] window, and stores A_end.
  • Emit BatchCommitted for every batch regardless of settlement mode.
• Preconfirmations
  • A committee of restaked operators signs BLS preconfirmations of ordered batches; your bridge refuses L1 exits until (i) batch is DA‑available and (ii) batch index ≤ proven_end.

This preserves auditor workflows (replay from blobs, cross‑check accumulator), tightens operational costs (one verify per range), and keeps users on sub‑second UX via preconfirmations.

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Emerging best practices we recommend adopting in 2026

• Multi‑backend provers and “proof markets” to avoid single‑vendor risk; use recursion to combine outputs from heterogeneous provers in one aggregate. Track the maturing decentralized proving/verification networks and plug them into your pipeline. (blog.succinct.xyz)
• Circuit/version governance: publish circuit commits and upgrade playbooks with overlap windows and simulated “break‑glass” single‑proof fallbacks.
• Observability: expose public dashboards for “proof lag,” “unproven tail length,” blob usage, and preconfirmation rate; publish monthly reproducibility attestations.

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Checklist: ship continuous aggregation without losing trust or UX

• Events/logs bind each L2 batch to an accumulator; aggregated proofs’ public inputs cover exact ranges.
• DA uses blobs; posting cadence guarantees reconstructibility within blob retention and PeerDAS‑scaled capacity. (blog.ethereum.org)
• Verifier contract exposes proven range and circuit versions; APIs for wallets/bridges.
• Preconfirmations live (BLS aggregate signatures verified via EIP‑2537) with slashing and DA gating. (eips.ethereum.org)
• Settlement proofs are permissionlessly disputable where relevant (OP/BoLD‑like dispute windows). (theblock.co)
• Source‑available state reconstruction from L1, documented and tested. (l2beat.com)

If you follow this blueprint, continuous aggregation becomes a strict superset of your current assurances: cheaper L1 footprint, higher proving throughput, the same or better auditability, and near‑instant UX confirmations that are economically backed and cryptographically sound.

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Want help planning or implementing this migration? 7Block Labs ships rollup pipelines end‑to‑end—from contracts and DA budgeting to prover orchestration, preconfirmations, and audit tooling—using the exact primitives referenced here.