About EIP-7892

Blob Parameter Only (BPO) Hardforks are specialized protocol upgrades that modify blob-related parameters through simple configuration changes—no client code modifications required. Unlike traditional hard forks that bundle multiple protocol changes and require extensive coordination, BPO forks focus exclusively on three critical blob parameters:

• Blob Target: The expected number of blobs per block under normal conditions
• Blob Limit (Max): The maximum number of blobs allowed in a single block
• Blob Base Fee Update Fraction: Controls how aggressively blob pricing adjusts based on demand

Why BPO forks matter

Traditional hard forks require thousands of lines of boilerplate code, extensive testing cycles, and coordinated deployment across all client implementations. BPO forks eliminate this overhead by treating blob parameters as configuration data rather than hardcoded values.

Key advantages:

• Configuration-based activation: Parameters are specified in node configuration files with predetermined activation timestamps
• Automatic parameter switching: Nodes automatically adopt new blob parameters at the specified block height
• Streamlined coordination: No code changes required across client implementations
• Rapid deployment: Weeks instead of months for parameter adjustments

Think of BPO forks as a "cheat sheet" for blob scaling—they provide a predetermined roadmap for capacity increases that can be executed quickly when network conditions demand it.

How BPO hardforks work in practice

To understand BPO forks in practice, consider how Ethereum might scale blob capacity over the next two years as L2 adoption accelerates.

Current situation (without BPO forks)

Ethereum currently supports 3 target blobs and 6 maximum blobs per block. When L2 demand consistently fills all 6 blob slots, creating expensive congestion, the only solution is a full hard fork that might take 6-12 months to coordinate, test, and deploy.

With BPO forks

Network operators can pre-plan a series of graduated capacity increases:

1. BPO Fork 1 (3 months later): Increases target to 6 blobs, maximum to 9 blobs
2. BPO Fork 2 (6 months later): Increases target to 12 blobs, maximum to 16 blobs
3. BPO Fork 3 (9 months later): Increases target to 16 blobs, maximum to 24 blobs

Each fork activates automatically at its predetermined timestamp. When network monitoring shows that blob utilization consistently exceeds 80% for several weeks, the next BPO fork provides immediate relief without requiring emergency coordination.

Step-by-step BPO fork process

1. Configuration update: Node operators update their configuration files with new blob parameters and activation timestamp
2. Automatic activation: At the specified timestamp, all nodes simultaneously adopt the new parameters
3. Immediate effect: Block builders can now include more blobs, reducing congestion and fees
4. Network verification: The P2P network automatically updates its fork digest to reflect the new parameters

This process transforms blob scaling from a major coordination challenge into a predictable, automated response to network demand.

Benefits of BPO hardforks

Rapid scaling response

Traditional hard forks require extensive coordination between core developers, client teams, node operators, and the broader ecosystem. This process typically takes 6-12 months from proposal to activation. BPO forks reduce this timeline to weeks, enabling Ethereum to respond quickly to L2 growth.

Example: If Arbitrum, Optimism, and Polygon zkEVM simultaneously launch major consumer applications that double blob demand overnight, a BPO fork could provide relief within 2-3 weeks rather than waiting months for the next planned hard fork.

Reduced operational overhead

According to the EIP authors, implementing a typical hard fork in Lighthouse requires "thousands of lines of boilerplate" before any protocol changes occur. BPO forks eliminate this overhead entirely by treating blob parameters as configuration data.

This means client development teams can focus on building new features rather than managing repetitive hard fork infrastructure. The result is faster innovation cycles and more predictable development timelines.

Enhanced stability with new technologies

Major scaling upgrades like EIP-7594 (Peer Data Availability Sampling) introduce uncertainty about optimal blob limits. Rather than forcing developers to guess the right parameters before deployment, BPO forks allow for conservative initial limits followed by rapid increases based on observed performance.

This approach reduces the risk of destabilizing the network while maximizing capacity utilization. For instance, when EIP-7594 launches, developers might initially set conservative blob limits, then use BPO forks to gradually increase capacity as the network demonstrates stability.

Predictable upgrades for builders

L2 solutions require confidence that Ethereum will scale to meet their data availability needs. BPO forks provide this predictability by establishing a clear roadmap for capacity increases.

According to the EIP motivation, this predictability allows "rollups to commit to Ethereum over alternative DA solutions." Instead of hedging their bets with multiple DA providers, L2 teams can confidently build on Ethereum knowing that capacity will scale with demand.

Technical implementation

The BPO fork mechanism operates through coordinated configuration changes across Ethereum's execution and consensus layers, with specific data structures designed to handle the transition seamlessly.

Execution layer configuration

The execution layer uses an extended version of the blobSchedule object from EIP-7840, linking each fork to an activation timestamp. BPO forks follow the naming convention bpo<index> where index starts at 1:

"blobSchedule": {
  "prague": {
    "target": 6,
    "max": 9,
    "baseFeeUpdateFraction": 5007716
  },
  "bpo1": {
    "target": 12,
    "max": 16,
    "baseFeeUpdateFraction": 5007716
  }
},
"pragueTime": 1747387400,
"bpo1Time": 1757387400

Consensus layer configuration

The consensus layer introduces a BLOB_SCHEDULE field containing entries for each fork that modifies blob parameters. This schedule specifies the epoch number and new MAX_BLOBS_PER_BLOCK value for each transition.

Network coordination

BPO forks require modifications to Ethereum's peer-to-peer networking to ensure nodes can properly coordinate during transitions. The compute_fork_digest function is updated to incorporate blob parameters into the network's fork identification, ensuring that nodes with different blob configurations can't accidentally connect.

Additionally, consensus layer nodes include a new nfd (next fork digest) field in their Ethereum Node Records (ENRs), allowing peers to communicate their upcoming fork transitions during network discovery.

Implementation considerations

Network impact and block size

Including blob scheduling information increases block size, but analysis shows this impact is manageable. The additional configuration data adds approximately 100-200 bytes per block, negligible compared to the 1-2 MB size of blocks containing maximum blobs.

The real consideration is ensuring that increased blob capacity doesn't overwhelm network bandwidth. BPO forks enable gradual capacity increases that can be monitored and adjusted based on network performance, rather than large jumps that might cause congestion.

Validation requirements

For BPO forks to maintain network security, all nodes must transition simultaneously at the specified timestamp. This requires:

• Synchronized clocks: All nodes must agree on the activation timestamp
• Configuration consistency: Execution and consensus layers must specify identical parameters
• Backward compatibility: Older nodes must be able to validate blocks up to the fork transition

Testing and deployment

While BPO forks eliminate most implementation complexity, they still require testing to ensure parameter changes don't create unexpected behavior. The EIP specifies that testing teams can "investigate different parameters with minimal involvement from client implementers," streamlining the validation process.

Future implications

Enabling higher throughput

The efficiency gains from responsive blob scaling could enable Ethereum to support significantly higher L2 throughput. As blob capacity increases predictably, L2 solutions can commit to serving more users without worrying about DA cost spikes.

For example, if current blob capacity supports 100,000 L2 transactions per second across all rollups, a series of BPO forks could potentially scale this to 500,000+ transactions per second over 12-18 months.

Foundation for on-chain governance

While BPO forks initially rely on off-chain coordination, they establish the technical foundation for future on-chain blob parameter governance. Once blob capacity stabilizes and the community gains experience with parameter adjustments, this mechanism could evolve into a more decentralized governance system.

Integration with future scaling solutions

BPO forks complement other scaling initiatives like stateless clients and verkle trees. By ensuring that blob capacity can scale rapidly, BPO forks remove a potential bottleneck that might otherwise limit the effectiveness of these future improvements.

The EIP authors note that BPO forks "provide a simpler, more predictable approach while leaving room for future on-chain voting mechanisms when blob capacity stabilizes." This suggests that BPO forks are designed as a transitional solution during Ethereum's high-growth phase.

Conclusion

EIP-7892 represents a significant advancement in Ethereum's ability to scale responsively to L2 demand. By introducing Blob Parameter Only Hardforks, Ethereum gains the ability to adjust blob capacity in weeks rather than months, ensuring that data availability never becomes a bottleneck for L2 growth.

The technical implementation is elegant in its simplicity—treating blob parameters as configuration data rather than hardcoded values eliminates the complexity of traditional hard forks while maintaining network security and decentralization. With BPO forks, Ethereum transforms from a system that scales in large, infrequent jumps to one that can adapt continuously to market demand.

This innovation ensures that Ethereum can confidently support the next generation of L2 applications, from consumer-facing social networks to enterprise-scale financial systems. As the ecosystem continues to grow, BPO forks provide the scaling agility that will keep Ethereum competitive with alternative data availability solutions.

As Ethereum approaches its next major upgrade phase, EIP-7892 demonstrates that significant protocol improvements don't always require complex implementations. Sometimes the most powerful innovations come from reimagining how we approach familiar problems—in this case, turning the challenge of blob scaling into a predictable, automated response to network growth.

Frequently asked questions

What is EIP in Ethereum? EIP stands for Ethereum Improvement Proposal. EIPs are standards that describe potential new features or processes for Ethereum. They contain technical specifications for proposed changes and serve as the primary mechanism for proposing new features, collecting community input on issues, and documenting design decisions that have gone into Ethereum. EIP-7892 introduces Blob Parameter Only Hardforks to enable rapid scaling of blob capacity through lightweight, focused hard forks.

How do BPO forks differ from regular hard forks? BPO forks modify only blob-related parameters through configuration changes, without requiring any client-side code modifications. Regular hard forks typically bundle multiple protocol changes and require extensive coordination, testing, and implementation changes across all client software. BPO forks can be deployed in weeks rather than months and eliminate the thousands of lines of boilerplate code typically required for hard fork implementation.

What are blobs and why do they matter for scaling? Blobs are large data packets introduced in Ethereum's Dencun upgrade that provide cheap data availability for Layer 2 solutions. L2 rollups use blobs to store compressed transaction data, enabling them to offer much lower fees than mainnet Ethereum. As L2 adoption grows, blob demand increases, making it critical for Ethereum to scale blob capacity to prevent congestion and high fees.

Who controls when BPO forks activate? BPO forks activate automatically at predetermined timestamps specified in node configuration files. The timing and parameters are coordinated by Ethereum's core development community through the same process used for regular hard forks, but without requiring code changes across client implementations. This allows for much faster deployment while maintaining the same security and decentralization guarantees.

Will BPO forks replace regular hard forks? No, BPO forks are designed specifically for blob parameter adjustments. Regular hard forks will still be necessary for broader protocol upgrades, new features, and other improvements. BPO forks complement regular hard forks by providing a streamlined mechanism for one specific but critical type of network upgrade, allowing regular hard forks to focus on more substantial protocol changes.

What is the purpose of EIP-7892 in relation to Ethereum's blob capacity? EIP-7892 introduces Blob Parameter Only Hardforks to enable rapid scaling of Ethereum's blob capacity in response to Layer 2 demand. The proposal allows Ethereum to adjust blob capacity in weeks rather than months, ensuring that data availability never becomes a bottleneck for L2 growth. This transforms Ethereum from a system that scales in large, infrequent jumps to one that can adapt continuously to market demand.

How does EIP-7892 enable scaling of Ethereum's blob capacity? EIP-7892 enables scaling through configuration-based parameter changes that activate automatically at predetermined timestamps. Instead of requiring extensive code changes across all client implementations, nodes simply update their configuration files with new blob parameters and activation times. This eliminates the thousands of lines of boilerplate code typically required for hard forks and allows for rapid deployment when network conditions demand increased capacity.

What are blob-related parameters that can be modified through EIP-7892? EIP-7892 allows modification of three critical blob parameters: the blob target (expected number of blobs per block under normal conditions), the blob limit or maximum (maximum number of blobs allowed in a single block), and the blob base fee update fraction (controls how aggressively blob pricing adjusts based on demand).

What are Blob Parameter Only (BPO) hardforks? BPO hardforks are specialized protocol upgrades that modify only blob-related parameters through configuration changes, without requiring any client-side code modifications. Unlike traditional hard forks that bundle multiple protocol changes, BPO forks focus exclusively on blob parameters and can be deployed through automatic parameter switching at specified block heights, enabling streamlined coordination and rapid deployment.

How do BPO forks differ from traditional hard forks? BPO forks treat blob parameters as configuration data rather than hardcoded values, eliminating the need for extensive code changes, testing cycles, and coordinated deployment across all client implementations. Traditional hard forks typically require 6-12 months from proposal to activation and thousands of lines of boilerplate code, while BPO forks can be deployed in weeks and require only configuration file updates.

What are the target and limit parameters mentioned in EIP-7892? The target parameter represents the expected number of blobs per block under normal conditions, while the limit (or maximum) parameter sets the absolute maximum number of blobs allowed in a single block. These parameters work together to manage blob capacity and pricing - the target establishes baseline expectations while the limit provides headroom for periods of high demand.

Why might lightweight hard forks for blob parameters be beneficial for Ethereum? Lightweight hard forks for blob parameters provide rapid scaling response to L2 growth, reduced operational overhead for client development teams, enhanced stability when deploying new technologies, and predictable upgrades that give L2 solutions confidence in Ethereum's scaling roadmap. This approach allows Ethereum to respond quickly to demand spikes and maintain competitiveness with alternative data availability solutions while reducing the complexity burden of frequent major protocol upgrades.