Ethereum Node
Understanding the Execution and Consensus Layer split.
The Two-Client Model
Since "The Merge," Ethereum has transitioned to a modular architecture. A single monolithic application no longer runs a node. Instead, you must operate a pair of distinct software clients that communicate via a local authentication port (The Engine API).
To run a functional node, you must install and sync both:
Execution Client (EL): Handles the "user" state (balances, smart contracts, transactions).
Consensus Client (CL): Handles the "network" state (proof-of-stake, finality, the beacon chain).
1. Execution Layer Clients (EL)
Formerly "Eth1"
The Execution Client listens to the peer-to-peer network for new transactions, maintains the memory pool (mempool), and executes smart contract code in the EVM.
Client
Language
Optimization Focus
Go
Storage Efficiency. Uses a unique database structure to significantly reduce disk usage for Archive Nodes.
⚠️ Note on Client Diversity
The Ethereum Foundation strongly encourages operators to run a minority client (non-Geth). If a super-majority client (>66% share) encounters a critical bug, the chain could finalize incorrectly.
2. Consensus Layer Clients (CL)
Formerly "Eth2" / Beacon Node
The Consensus Client implements the Proof-of-Stake algorithm. It tracks the head of the chain, gossips blocks, and enables validators to attest to the state.
Client
Language
Optimization Focus
🛡️ Configuration Strategies
The modular nature of Ethereum allows operators to mix and match any Execution Client with any Consensus Client. The optimal combination depends on your specific infrastructure goals.
Strategy A: Validator Resilience
Operators running active validators often prioritize Minority Clients to mitigate "Slashing Risk."
Rationale: If a majority client contains a bug that causes it to finalize an invalid chain, validators running that client may face severe penalties.
Common Configurations: Nethermind + Lighthouse / Besu + Teku.
Strategy B: Infrastructure & RPC Stability
Operators providing public API endpoints or high-volume data access often prioritize Client Stability and JSON-RPC response times.
Rationale: Compatibility with indexers and predictable uptime are the primary metrics for RPC services.
SyncNode Insight:
While we strictly support and encourage client diversity across the network, internal benchmarks at SyncNode indicate that the Geth (EL) + Prysm (CL) combination currently offers the highest stability for high-load public RPC endpoints.
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