As Ethereum’s Fusaka upgrade progresses, client teams are increasingly turning to shadow forks of the mainnet to conduct performance benchmarking. This shift reflects growing concerns about the limitations of testnets and the urgent need for high fidelity validation of protocol changes such as EIP-7907.
During ACDT-41, developers shared benchmarking results that used a shadow fork of Ethereum mainnet to test execution times on large contracts under the proposed changes of EIP-7907. This approach offered real world data profiles, especially with large databases, which traditional devnets and test fixtures often fail to replicate.
Why It Matters
Unlike testnets, shadow forks replicate Ethereum’s live chain with identical state, allowing developers to observe performance patterns, I/O pressure, caching behavior, and contract execution at full scale.
This has proven especially valuable for analyzing code size indexing, gas limit pressure, and execution latency across clients like Geth, Besu, Nethermind, and Erigon. The Ethereum protocol is evolving rapidly with data intensive upgrades like blobs and larger smart contracts.
Testnets often fall short of capturing real mainnet complexity. Shadow forks enable protocol teams to:
- Test client specific optimization strategies
- Benchmark gas usage in realistic block conditions
- Avoid misleading performance boosts from artificial environments
The consensus from ACDT-41 is clear that shadow fork testing is essential. It helps refine benchmarks, guide EIP specification clarity, and determine readiness for rollout to Devnet 3 and eventually mainnet.
A Brief History of Shadow Forks
Shadow forks have been a critical part of Ethereum’s development process since 2022. They first rose to prominence during Merge testing, offering a safe space to test client compatibility, consensus logic, and execution coordination without disrupting the mainnet.
In 2025, shadow forks once again played a pivotal role, stepping in to support the Holesky testnet during periods of instability and finality issues. Their ability to mirror Ethereum’s live state while remaining isolated makes them uniquely suited for detecting sync failures, bottlenecks, and edge case bugs that no testnet could reliably surface.
Their usage has only grown over time, evolving from niche experiments to a core component of Ethereum’s test infrastructure.
Conclusion
Shadow forks allow realistic benchmarking that testnets cannot provide. They have uncovered issues in gossip propagation, client compatibility, and execution performance under real world load.
Any client or spec update that skips this phase risks overlooking issues that only real state replication can expose. The path to Devnet 3 and eventual mainnet stability will rely more than ever on the continuous use of shadow forks.
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