How to Plan Stateless Client Support

Stateless clients are a paradigm shift for blockchain node architecture. Unlike full nodes that store the entire state (account balances, contract storage), a stateless client only holds the block headers and requests specific state data, or witnesses, on-demand to validate new blocks. The core goal is to drastically reduce hardware requirements, enabling lightweight clients to participate in consensus without trusting third parties. This is achieved through cryptographic commitments like Merkle Patricia Tries (MPT) in Ethereum, where a single root hash in the block header commits to the entire world state.

Planning support begins with selecting a state commitment scheme. Ethereum's current MPT is being upgraded to a Verkle Tree for more efficient proofs. Alternative Layer 1s and Layer 2s use different structures: StarkNet employs a binary Merkle tree for its Cairo-AVM state, while zkSync Era uses a Sparse Merkle Tree. Your choice dictates proof size and verification cost. You must also decide on the data availability source for witnesses: will your client fetch them from a peer-to-peer network, a dedicated gateway like the Portal Network, or a trusted RPC provider? Each has trade-offs in decentralization, latency, and reliability.

The implementation involves two main components: the verification logic and the data layer. The verification logic must validate that the provided witness corresponds to the state root in the block header and that the transactions in the block execute correctly against this witness. For Ethereum, this means implementing EIP-6800 for Verkle proof verification. The data layer manages the fetching, caching, and potentially gossiping of witnesses. A robust plan includes a fallback mechanism, such as a weak subjectivity checkpoint sync, in case the witness network is unavailable, ensuring the client can always bootstrap securely.

Stateless clients are a paradigm shift in blockchain node design, where nodes validate blocks without storing the entire world state. Instead, they rely on cryptographic proofs—primarily Merkle proofs or Verkle proofs—provided with each block to verify state transitions. Planning for this architecture requires a clear understanding of your chain's current state model, consensus mechanism, and the trade-offs between on-chain proof size and off-chain data availability. The core goal is to drastically reduce hardware requirements, enabling lightweight nodes to participate in consensus with the same security guarantees as full nodes.

Begin by auditing your existing state management. For Ethereum Virtual Machine (EVM) chains, this involves analyzing the Merkle Patricia Trie structure, state growth rate, and access patterns. For non-EVM chains like Cosmos SDK-based appchains or Solana, you must map the native state commitment scheme. Key metrics to gather include: average state size per block, state witness size (the proof data needed for validation), and the performance impact of proof generation and verification in your current client implementation (e.g., Geth, Erigon, Besu).

The choice of cryptographic accumulator is critical. The Ethereum community is transitioning from Merkle-Patricia to Verkle trees (using polynomial commitments) to reduce proof sizes from ~1 MB to ~150 KB. Your planning must decide between adopting an existing standard (like the upcoming Ethereum Verkle spec) or designing a custom scheme. This decision impacts every layer: the consensus protocol must agree on proof validity, the execution client must generate proofs, and the network layer must efficiently transmit them. Consider using libraries like ipa_multipoint for Verkle proof verification.

Define the operational scope for your initial rollout. Will you support full stateless validation from genesis, or a weak subjectivity sync from a recent checkpoint? A hybrid "stateless block verification" mode, where blocks are validated statelessly but a small state cache is maintained for execution, can be a pragmatic intermediate step. Plan your network protocol upgrades: the P2P layer needs new message types (e.g., GetProofsV2) and services for distributing state witnesses, potentially leveraging decentralized storage networks or dedicated blob sidecars.

Finally, establish a testing and rollout strategy. Create a dedicated testnet that mirrors mainnet state size. Use tools like turbo-geth's stateless prototype or the Ethereum Stateless Ethereum Testnets to benchmark performance. Key performance indicators (KPIs) should include block import time with proofs, CPU/memory usage of the proof verifier, and network bandwidth consumption. A phased rollout, starting with a subset of validator nodes, allows for real-world data collection and risk mitigation before enforcing the new validation rules network-wide.

Stateless clients represent a paradigm shift in blockchain node architecture. Unlike a full node that stores the entire state (account balances, contract code, storage), a stateless client validates blocks using only a block header and a cryptographic proof, known as a witness. This witness contains the minimal subset of state data needed to execute the block's transactions. The primary goal is to drastically reduce hardware requirements, enabling validation on resource-constrained devices and improving network decentralization. Ethereum's roadmap, via The Verge, is explicitly targeting this architecture to solve state growth.

Planning for stateless support begins with a technical assessment of your client's role. You must decide if you are building a block producer (e.g., a validator) or a block verifier (e.g., a light client). Block producers need efficient ways to construct and attach witnesses, while verifiers need robust logic to validate them. The core dependency is the adoption of a Verkle tree state structure, which replaces the current Merkle Patricia Trie. Verkle trees enable much smaller witnesses (on the order of kilobytes instead of megabytes) through the use of vector commitments, making stateless validation practically feasible.

The implementation involves several key components. First, integrate a Verkle tree library, such as the one developed by the Ethereum Foundation. Your client must be able to generate witnesses for transactions it creates and verify witnesses for blocks it receives. This requires new JSON-RPC endpoints (e.g., eth_getProof for Verkle trees) and updates to the block synchronization protocol. You'll also need a strategy for accessing witness data, which may involve a peer-to-peer network or a service like a portal network. Testing against existing testnets, like a Verkle-powered devnet, is crucial for validation.

Consider the transition period, as networks will support both stateful and stateless clients simultaneously. Your client should implement fallback mechanisms to operate in a stateful mode if a witness is unavailable or invalid. Furthermore, analyze the impact on APIs and downstream services. Applications that rely on state queries may need to adjust, as the client may no longer locally host the full state. Planning should include benchmarks for witness size, verification speed, and bandwidth usage to ensure the client meets performance targets in a stateless environment.

Stateless clients verify blockchain state without storing it locally by relying on witnesses—compact cryptographic proofs that a piece of data is part of the current state. Planning support for this architecture requires designing efficient witness formats and the network protocols to request and deliver them. The core challenge is minimizing witness size while maintaining verifiability, as large witnesses increase bandwidth and latency, negating the benefits of statelessness. Formats like Merkle proofs, Verkle proofs, and binary Merkle Patricia Trie (MPT) proofs each offer different trade-offs between proof size and computational overhead.

The first step is selecting a state commitment scheme. Ethereum's current hexary MPT produces large witnesses (often several kilobytes), motivating a shift to Verkle trees for sub-linear proof sizes. A witness format must serialize the proof data—such as tree nodes, sibling hashes, and optional value data—into a deterministic byte array. This involves defining a serialization schema (e.g., using SSZ, RLP, or a custom binary format) and specifying inclusion rules for what data is mandatory versus optional. For example, a block witness for execution might include the account and storage proofs needed to validate all transactions in that block.

Network protocol design dictates how clients request and receive witnesses. This typically involves a new P2P protocol message (e.g., GetWitnesses/Witnesses in Ethereum's devp2p) where a request contains identifiers like block hash and a list of account addresses, and the response delivers the corresponding proofs. Protocols must handle partial witnesses (for specific accounts) and full block witnesses, and may require witness caching strategies by full nodes. Bandwidth efficiency can be improved with compression techniques and by differentiating between hot data (frequently accessed state) and cold data proofs.

Implementation requires integrating witness verification into the client's state transition logic. After receiving a block and its witness, the client must recompute the state root using the provided proofs and verify it matches the block header. This involves writing verification functions for your chosen proof type. For a Merkle proof, this means hashing sibling nodes up the tree. For a Verkle proof, it requires polynomial commitment checks. Libraries like nim-verkle or go-verkle provide primitives for this. The client's execution engine must be modified to request missing state data via the witness protocol instead of a local database.

Finally, planning must address transitional states and forward compatibility. During a network upgrade to a new witness format (like Ethereum's transition to Verkle trees), clients may need to support both old and new formats simultaneously via versioned protocols. Furthermore, designs should allow for witness aggregation (combining multiple proofs) and future proof upgrades to even more efficient proving systems. Thorough testing with existing blockchain data is crucial to benchmark witness sizes and validation performance under real-world conditions before deploying to a testnet.

The primary challenge in planning stateless client support is managing the witness data required to validate blocks without storing the full state. A witness is a cryptographic proof, typically a Merkle proof, that a specific piece of state data (like an account balance) is part of the current state root. Clients must decide on a witness format—such as binary Merkle proofs or Verkle proofs—which directly impacts proof size and verification speed. For Ethereum, the shift to Verkle trees aims to reduce witness sizes from ~1 KB to ~150 bytes, a critical optimization for bandwidth-constrained environments.

A major trade-off involves the source of witness data. Clients can fetch witnesses from a peer-to-peer network, a dedicated witness provider service, or generate them locally if they maintain a partial state. Relying on the P2P layer adds latency and requires a robust gossip protocol for witness distribution. Using a centralized provider introduces a trust assumption and a potential single point of failure. The Ethereum roadmap addresses this with proposals like The Portal Network, a decentralized network for serving light client data including witnesses.

Developers must also plan for state growth and access patterns. Stateless validation is most efficient for transactions that touch a small, predictable set of accounts. Applications with highly random state access can generate large, inefficient witnesses. To mitigate this, smart contract developers should design for locality of reference, grouping frequently accessed data within the same storage subtree. Protocols may also implement witness compression techniques or bundle transactions with shared witnesses to amortize overhead.

Another critical consideration is client synchronization and bootstrapping. A new stateless client needs an initial, trusted block header and the corresponding state root. From there, it can validate incoming blocks with witnesses. However, if the client goes offline, it may need to fetch historical witnesses to verify the chain since its last update. Planning for this catch-up mechanism is essential, potentially involving checkpoints or incremental witness accumulation from archive nodes.

Finally, the transition path for existing stateful clients must be planned. A hybrid approach, where clients run in a semi-stateless mode, is often a practical first step. In this mode, clients maintain a small, recent state cache (e.g., the last 128 blocks) to validate most transactions without witnesses, only fetching proofs for cache misses. This reduces immediate bandwidth demands while allowing the network and tooling to mature toward full statelessness, as envisioned in Ethereum's Verge upgrade.

Successfully planning for stateless client support requires a phased approach. Begin with a proof-of-concept using a testnet or a local development chain. Focus on integrating a state commitment scheme like Verkle Tries or Binary Merkle Patricia Tries. Use a library like go-verkle or polynomial-commitments to handle the cryptographic proofs. The initial goal is to validate a single block with a stateless execution engine, verifying that you can correctly process transactions using only a block header and a witness.

The next phase involves optimizing witness handling. This is the most critical engineering challenge. You'll need to design an efficient network protocol for witness distribution, potentially using a dedicated P2P subprotocol or a service like a portal network. Implement caching strategies for frequently accessed state elements to reduce bandwidth. Benchmark your client's performance against key metrics: witness size per block, time to fetch and verify a witness, and sync time from genesis.

Finally, prepare for mainnet readiness. This involves extensive testing, security audits, and community coordination. Run long-term sync tests to ensure robustness. Engage with other client teams and research groups through the Ethereum Statelessness R&D Discord or the Ethereum Magicians forum. The transition to statelessness is a network-wide upgrade; your implementation must be interoperable with others. Review the latest EIPs, such as those detailing Verkle tree transition mechanics, to ensure compliance.

For ongoing learning, follow the work of core research teams. The Ethereum Foundation's Stateless Ethereum portal provides updates. Study the specifications for EIP-6800 (Verkle Trees) and the accompanying execution and consensus client changes. Experiment with existing implementations in the ethereum/go-ethereum (Geth) or nethermindeth/nethermind codebases, which have active statelessness branches. Contributing to these codebases or their test suites is a valuable way to deepen your expertise.

The path to stateless clients is complex but essential for Ethereum's long-term scalability. By methodically building expertise in state commitments, proof systems, and peer-to-peer data retrieval, you can contribute to a more decentralized and efficient blockchain future. Start small, iterate based on data, and collaborate with the broader ecosystem to turn this research into production-ready software.