Designing Arbitration dApps That Survive CDN and DNS Outages

On the morning a major Cloudflare outage knocked Twitter and dozens of sites offline, Priya’s cross‑border freelance marketplace hit its first serious test. Two large escrows flipped into dispute within an hour. The funds were safely locked in a Base smart contract, but her support inbox didn’t care: the dApp UI behind Cloudflare would not load, her webhook relayer in a single AWS region was timing out, and evidence uploads stalled.

Technically, nothing was wrong on‑chain. Token balances and dispute flags were exactly where they should be. Yet buyers and sellers had no way to see status or interact. The episode exposed a simple truth she had glossed over: “decentralized” describes your consensus and custody model, not your availability model. Availability is an architecture choice.

This piece looks at that choice in the concrete context of arbitration and escrow dApps, and then shows how to harden them with Verdikta‑style patterns: content‑addressed UIs via IPFS and ENS, redundant relayers and L2 nodes, and verifiable off‑chain commit–reveal attestations backed by multi‑oracle redundancy.

---

1. Cloudflare Outages Expose Centralized Choke Points

If your arbitration or escrow dApp goes dark during a CDN or DNS outage, users will not care that “the funds are still on‑chain.” From their perspective, the product is offline.

Consider a typical arbitration stack. The contracts may be impeccably designed: escrow balances held in a Base L2 contract, dispute flags stored on‑chain, arbitration outcomes emitted as events. The access path, however, is usually very Web2:

• A React or Next.js frontend built as static assets, hosted on Vercel or S3 behind Cloudflare.
• DNS at a single registrar, often fully proxied through Cloudflare.
• A single JSON‑RPC endpoint (for example, https://mainnet.base.org or one Alchemy URL) hard‑coded into the frontend.
• One webhook relayer that listens for events and calls your off‑chain arbitration logic.
• A single oracle process or Chainlink job for off‑chain decisions.
• A back‑office dashboard gated by Google Auth or Okta.

In that configuration, a Cloudflare‑scale incident behaves exactly as the Independent’s coverage described. Browsers cannot resolve or reach app.example.com, so the UI never loads. Even if a user bypasses DNS with a raw IP, TLS fails. Hosted webhook relayers and API gateways behind Cloudflare return 5xx errors; new disputes are not automatically opened, evidence uploads stall, and your support team cannot reach its dashboard because SSO is down.

From the user’s point of view, your “decentralized arbitration” product is simply offline.

What remains intact is everything the blockchain actually promised:

• The escrow contract still holds the tokens. No CDN outage can erase or move funds; contract state on Base is independent of Cloudflare’s status.
• Dispute flags, deadlines, and references to arbitration results remain in storage and in the event log. Any working RPC endpoint can return them.
• For Verdikta‑style flows, verdict events such as FulfillAIEvaluation(aggId, scores, justificationCids) are permanent history; the justification CIDs point to IPFS content that is not tied to a single web host.

A power user with a wallet and an alternate RPC URL can still call openDispute(), submitEvidence(cid), or inspect getDispute(disputeId) directly. The gap is not in consensus or custody; it is in reachability and UX. A credible availability story requires you to be able to say: the funds are safe, and there is always at least one documented path for users to see and act on that state, even if a CDN or DNS provider fails.

---

2. Mapping the Failure Surface: Centralized vs. Trustless

Availability engineering starts with a precise dependency inventory. For arbitration and escrow, it is useful to separate three layers.

First, state and execution. Smart contracts enforce objective rules: who funded which escrow, what the deadlines are, which disputes are open, and, in Verdikta’s case, which arbitration verdict scores and justification hashes have been written on‑chain. This layer is already decentralized and Byzantine fault tolerant, assuming the underlying L1 or L2 is.

Second, observation. Indexers, explorers, and UIs observe on‑chain events and present them as human‑readable timelines: “Escrow #123 created,” “Dispute opened,” “Verdict emitted with scores [85, 15] and justification CIDs QmX…,QmY….” This is where centralization usually creeps back in; a single API node or indexer becomes a hidden single point of failure.

Third, action. Users and back‑office systems send transactions to change state: opening disputes, submitting evidence CIDs, or triggering payout logic when an oracle verdict arrives. One RPC provider or one relayer process almost always mediates these actions.

With that structure in mind, you can be explicit about your failure surface:

• A CDN outage prevents frontend bundles and static assets from loading, even though the escrow contract at 0x… is live.
• DNS or registrar issues can make app.example.com unreachable or mis‑routed, regardless of on‑chain state.
• A single L2 provider outage means your hard‑coded RPC URL fails, so users cannot send dispute transactions despite other Base nodes being healthy.
• One hosted webhook relayer going down means no events are forwarded to your arbitration backend; evidence and deadlines silently drift.
• A single oracle process or Chainlink node outage stalls all off‑chain decisions.
• Third‑party auth outages lock your operators out of dashboards they might otherwise use to mitigate problems.

In contrast, the trustless core remains stable. Contracts and balances on Base are globally readable from any node. Event logs still show escrow creation, dispute opening, and Verdikta’s verdict events with justification CIDs. Users with wallets plus an alternative RPC endpoint can continue to interact, if they know how.

The technical implication is straightforward: protocol guarantees apply at the contract and event level. Every additional access path—CDN, DNS, RPC provider, relayer, oracle—is an availability risk. Good architecture minimizes the blast radius of any single failure by supplying verifiable alternatives.

---

3. Resilient UI and Node Architecture for Arbitration dApps

The contract layer is already decentralized. The question is how to make UI delivery and node access match that property as closely as is practical.

A sensible approach is to treat the user‑facing layer as three tiers: decentralized UI delivery, robust content pinning, and redundant connectivity to the L2.

On the UI side, arbitration and escrow interfaces are ideal for content‑addressed hosting. They compile to static assets: HTML, JavaScript, CSS. You can build once and deploy to IPFS:

npm run build

# Add the static build directory to IPFS
ipfs add -r build/

# Optional: publish to IPNS for a stable name
ipfs name publish <root_cid>
``

The result is a CID that globally names your UI. In parallel, you can deploy the same `build/` directory to Arweave:

```bash
arweave deploy build/ --wallet keyfile.json

To make this discoverable, bind an ENS name via its contenthash record. A minimal Ethers.js flow looks like this:

import { ethers } from "ethers";
import { namehash } from "ethers/lib/utils.js";
import ensRegistryAbi from "./EnsRegistry.json";

const provider = new ethers.JsonRpcProvider(RPC_URL);
const wallet   = new ethers.Wallet(PRIVATE_KEY, provider);
const ens      = new ethers.Contract(ENS_REGISTRY, ensRegistryAbi, wallet);

const node        = namehash("app.eth");
const contenthash = "0xe30101701220" + IPFS_CID_HEX; // IPFS codec prefix + CID bytes

await ens.setContenthash(node, contenthash);

Browsers that support ENS gateways can now resolve https://app.eth.limo or https://app.eth.link to your IPFS‑hosted UI. Even if your primary CDN is unhealthy, the ENS → IPFS path remains available. Under the hood, IPFS uses libp2p to route requests to any peer that has pinned your content.

Pinning and uptime are the next concern. IPFS CIDs do not magically persist; at least one node must pin them. In a production arbitration dApp, you should assume multiple pins:

• Two independent pinning providers for redundancy.
• A small self‑hosted IPFS cluster under your control.
• An Arweave bundle as an immutable backup of each release.

The trade‑off is a slightly more complex deployment pipeline. Each build produces a new CID, so you must update ENS contenthash or an IPNS pointer. In return, you decouple UI availability from any single CDN or object store. Cache invalidation moves from “purge Cloudflare” to “update the contenthash to point at the new CID.”

Finally, you need redundant connectivity to the L2 and indexers. Hard‑coding https://mainnet.base.org into your frontend is expedient but brittle. Instead, treat RPC endpoints as a list, and have your client libraries cycle through them:

{
  "rpcEndpoints": [
    "https://mainnet.base.org",
    "https://base.publicnode.com",
    "https://your-own-base-node.example.com"
  ]
}

If one endpoint fails health checks, your dApp selects another. The same approach applies to any custom indexer you operate for faster dispute queries: deploy a pair of indexers in different regions, backed by different Base nodes, and degrade gracefully to direct RPC reads if both are down.

Relayers should be treated similarly. Instead of routing all meta‑transactions through relay.example.com behind one CDN, define a small quorum of relayer endpoints, each behind independent infrastructure. Your client can attempt to send signed payloads to relay1 and relay2 and proceed once a configurable number of acknowledgments arrive.

None of this alters the contract layer. It simply reduces the chance that a Cloudflare‑style incident takes your availability from “high” to “zero.”

---

4. Hardening Oracles and Off‑Chain Compute with Commit–Reveal

Arbitration logic almost always involves off‑chain computation: human review, rules engines, or increasingly, AI models. If that layer is centralized or fragile, outcomes can stall even while escrow funds remain locked.

Verdikta’s protocol provides a rigorous pattern here. It uses a randomized, reputation‑weighted committee of AI arbiters, each running models off‑chain, and combines their outputs via a two‑phase commit–reveal scheme before aggregating the result on‑chain.

In the commit phase, each selected arbiter evaluates the evidence (fetched from IPFS via the user‑supplied CID) and obtains a vector of likelihood scores and a textual justification. Instead of publishing those directly, the arbiter commits to them with a compact hash:

bytes16 commitHash = bytes16(
    sha256(abi.encode(arbiterAddress, likelihoods, salt))
);

This commitHash is posted to the Verdikta aggregator contract. Only after a threshold of commits is reached does the protocol move into the reveal phase. At that point, arbiters reveal the actual scores, the justification CID, and the salt. The contract recomputes the hash and checks it against the stored commitment. As described in the whitepaper, this prevents freeloading and copying: all arbiters must decide independently before any answer is visible.

A general arbitration dApp can adopt the same structure. You define two functions in your contract, one for commitments and one for reveals, and you require both a valid hash link and a valid signature from a known oracle. A minimal sketch looks like this:

mapping(bytes32 => mapping(address => bytes16)) public commits;

function commit(bytes32 disputeId, bytes16 commitHash) external {
    require(commits[disputeId][msg.sender] == 0, "already committed");
    // check msg.sender is in the oracle set
    commits[disputeId][msg.sender] = commitHash;
}

function reveal(bytes32 disputeId, Decision calldata d, bytes calldata sig)
    external
{
    address signer = recoverSigner(d, sig);
    require(commits[disputeId][signer] != 0, "no commit");

    bytes16 h = bytes16(sha256(abi.encode(signer, d, d.salt)));
    require(h == commits[disputeId][signer], "hash mismatch");

    // record decision; when quorum reached, aggregate and apply
}

Here Decision encodes your scores, justification CID, and random salt. The contract verifies that the revealed data matches the previous commit, and that the signer is part of a configured oracle committee. Aggregation logic then computes a consensus—Verdikta, for example, finds a cluster of agreeing likelihood vectors and averages them—and applies the state transition only when a quorum of valid reveals exists.

From a cryptographic perspective there is a clear trade‑off. Per‑oracle ECDSA signatures are supported natively in the EVM via ecrecover. They are simple to audit and incur gas cost linear in the number of signers. Threshold or BLS signatures allow aggregating many oracle signatures into one, reducing on‑chain verification to a single pairing operation, but they introduce more complex primitives and a larger audit surface.

For most Base‑deployed arbitration systems, a small committee (three to seven arbiters) with ECDSA signatures and Verdikta‑style commit–reveal is a sensible default. It yields verifiable redundancy without exotic cryptography. If your committee grows large enough that signature verification dominates gas costs, revisiting BLS aggregation is reasonable, but that is a scaling decision rather than a prerequisite.

The essential property is that a decision exists only when multiple independent oracles have committed to and revealed it, and anyone can replay those checks on‑chain later. That is precisely the property Verdikta provides: a multi‑arbiter, reputation‑weighted committee using commit–reveal and an on‑chain verdict event with justification CIDs.

---

5. UX and Fallback Flows When DNS and CDNs Fail

A theoretically accessible contract is not enough. Users need clear, documented paths to complete critical actions when primary DNS or CDN paths are degraded.

For arbitration and escrow, the critical flows are straightforward:

• Viewing escrow and dispute state.
• Opening or responding to a dispute.
• Submitting evidence, typically as an IPFS CID.
• Inspecting arbitration verdicts and their justifications.

The primary flow will remain your main site—https://app.example.com—with a modern UI and wallet integration. You should, however, treat fallback paths as first‑class citizens rather than emergency hacks.

ENS plus IPFS is the obvious starting point. In your documentation and onboarding, present https://app.eth.limo (or equivalent gateway) alongside your primary domain. When you ship a new build, test both. Likewise, keep direct IPFS gateway URLs such as https://ipfs.io/ipfs/<cid> in your runbooks; they are ugly but effective when everything else fails.

Within the UI, implement a simple degraded‑mode pattern. If the app detects that its primary RPC endpoint is failing or that key APIs are unreachable, display a banner explaining the situation and linking to alternative access paths: the ENS gateway, the contract’s page on a Base explorer, and a short guide on calling functions like openDispute directly from a wallet interface.

Evidence submission deserves specific design work. Verdikta already assumes that evidence and justifications are referenced by IPFS CIDs, not stored on‑chain. In normal operation you may hide IPFS behind a convenient upload API. During an outage, that API may be down. Your fallback documentation should therefore explain how users can:

1. Upload evidence files to IPFS using a third‑party pinning service.
2. Obtain the resulting CID.
3. Submit that CID via a direct submitEvidence(disputeId, cid) transaction in their wallet.

From the contract’s perspective, nothing changes; it still stores CIDs. The only difference is whether your infrastructure or the user handles the IPFS step.

For advanced users, publishing transaction templates is useful. By “template” here I mean the ABI signature, function selector, and parameter encodings for key operations. With that information, a user who reaches a block explorer or low‑level wallet interface can construct and send the necessary transaction even without your UI.

None of these patterns are glamorous, but they directly address the failure modes exposed by events like the Cloudflare outage. They ensure that when “the dApp is down,” what is really down is a particular Web2 path, not the ability to resolve disputes.

---

6. Migration Steps, Monitoring, and Testing

Moving from a single‑CDN deployment to a resilient arbitration stack is incremental. You do not need a rewrite; you need a sequence of concrete changes and tests.

The first step is UI hardening. Integrate IPFS and, optionally, Arweave into your build pipeline. After npm run build, have CI run ipfs add -r build/, pin the resulting CID with multiple providers, and publish to Arweave. Update the ENS contenthash for your dApp name and script HTTP checks against both your primary domain and app.eth.limo.

Next, rationalize node and relayer configuration. Replace hard‑coded RPC URLs with a list, and implement simple failover logic in your client libraries. Do the same for relayers: maintain a configuration file similar to:

{
  "rpcEndpoints": [
    "https://mainnet.base.org",
    "https://base.publicnode.com"
  ],
  "relayers": [
    "https://relay1.example.com",
    "https://relay2.example.org"
  ],
  "quorum": 2
}

Ensure your backend can use either RPC endpoint, and that relayer traffic can be shifted away from a failing instance without contract changes.

Then, harden the oracle and off‑chain compute path. If you are already integrating Verdikta, much of this is in place: a randomized panel of AI arbiters, commit–reveal, aggregation, and a verdict event with justification CIDs. If you are running your own logic, introduce a minimal commit–reveal mechanism, as sketched earlier, and define a small oracle committee. Require a quorum of valid reveals before any escrow resolution occurs.

At that point, you can begin running realistic tests. In a staging environment, deliberately simulate the failures that caused Priya so much trouble:

• Block access to your primary domain or break its DNS record and verify that users can still reach the UI via ENS/IPFS.
• Kill one RPC endpoint and confirm your frontend and backend switch to the alternative.
• Shut down one relayer or oracle node and confirm that disputes still progress because quorum is preserved.

From a monitoring perspective, two metrics are particularly informative for arbitration:

• Time‑to‑finality: the elapsed time from dispute opening to on‑chain verdict event. Verdikta is designed for minutes under normal load; significant drift is an early warning.
• Oracle response variance: both latency spread across arbiters and disagreement in their scores. Increasing variance suggests infra or model problems.

Synthetic transactions are more valuable than any static dashboard. Regularly create small test escrows, open disputes, submit dummy evidence CIDs, and observe end‑to‑end behavior. That is how you verify that your availability architecture works in practice rather than only on diagrams.

A compact way to visualize the final architecture is as a textual diagram:

• User → ENS (app.eth) → IPFS or Arweave gateway, or direct CID → static UI.
• User wallet → load‑balanced Base nodes (self‑hosted + providers) → escrow and arbitration contracts.
• Oracles and relayers → commit and reveal to an aggregator → on‑chain verdict events and justification CIDs.
• Indexers and explorers → read events → back‑office dashboards.

Your testing plan should simulate failure along each arrow and confirm that alternative arrows still lead back to the same contracts and logs.

---

7. How Verdikta Fits Into This Picture

Verdikta’s design already embodies several of these resilience principles at the oracle layer. Evidence and justifications are stored as IPFS CIDs rather than raw bytes on‑chain. A randomized, reputation‑weighted committee of AI arbiters evaluates each query, each arbiter commits to its answer with a hash, then reveals scores and justification CIDs. The Verdikta aggregator contract verifies those commits, aggregates the scores to form a verdict, and emits an event carrying both the scores and the justification CIDs.

From an arbitration dApp’s perspective, that means the decision itself is not tied to any particular server or model instance. Multiple arbiters, potentially running on different cloud providers and using different AI models, must agree for a verdict to exist. The on‑chain record—the verdict scores and justification CIDs—remains accessible through any Base node, even during a Cloudflare‑style incident.

If you pair that oracle layer with the availability techniques described above—IPFS and ENS for UI delivery, redundant Base nodes and relayers, commit–reveal attestations for any additional off‑chain logic—you end up with an arbitration and escrow stack where both outcomes and access are robust. Funds remain under smart contract control, decisions are made by a decentralized AI committee with on‑chain proofs, and users have multiple documented paths to inspect and act on that state when centralized infrastructure stumbles.

The technology to do this exists today. The remaining work is architectural and operational: inventory your dependencies, remove single points of failure where they matter most, and rehearse the failure modes before they happen in production. The next Cloudflare outage will not be the last. It does not have to be the next time your “decentralized” application feels centralized to your users.