Ethereum Fusaka Upgrade: PeerDAS Impact Explained

The Ethereum Fusaka upgrade introduces PeerDAS, a way for validators to check that rollup data is available by sampling pieces of it rather than downloading every blob in full. That can support greater blob capacity and improve Layer 2 data throughput, but it does not guarantee cheaper fees or a fixed increase in transactions per second.

That distinction matters in September 2026: more capacity is useful only if rollups use it, users benefit from lower costs, and Ethereum’s data-availability assumptions remain sound. Here is what Fusaka changes, how to evaluate its real-world impact, and what investors should monitor before treating throughput as an ETH price catalyst.

Ethereum Fusaka upgrade and PeerDAS: what changed

Fusaka’s central data-availability change is PeerDAS, short for Peer Data Availability Sampling. Ethereum uses blobs to carry data that rollups can use without publishing all of that data as ordinary execution-layer calldata. PeerDAS changes how consensus-layer participants check that blob data is available to the network.

Before sampling, validators generally needed to receive the relevant blob data to verify availability. With PeerDAS, data is erasure-coded and distributed in pieces, allowing a validator to sample parts of the data. If enough pieces are accessible under the protocol’s sampling rules, the network can gain confidence that the full data can be reconstructed when required.

This is a change in how Ethereum handles data availability, not a shortcut around the need for data. PeerDAS does not make rollup data optional, nor does it automatically make transactions execute faster on Ethereum’s base layer. Its purpose is to help Ethereum support more rollup data without requiring every validator to download every byte of every blob.

Fusaka is also associated with a more flexible path for adjusting blob parameters through Blob Parameter-Only (BPO) forks. That matters because Ethereum can tune blob targets and limits in stages rather than tying every capacity adjustment to a large, all-purpose upgrade. For exact parameters active on a particular date, check current Ethereum client and network documentation; targets and maxima can change as the roadmap progresses.

For context, Pectra raised the pre-Fusaka blob target to six blobs per block, with a maximum of nine. Those figures describe that earlier configuration, not necessarily the live September 2026 setting. The key takeaway is that PeerDAS is designed to make higher data capacity more practical; it should not be confused with a single permanent throughput number.

PeerDAS Layer 2 data throughput: how the mechanism works

A rollup batches transactions, processes them outside Ethereum’s execution layer, and posts data or commitments back to Ethereum. That lets users share the cost of settlement across many transactions, but the rollup still needs a reliable way to make transaction data available so independent parties can verify its state and, where applicable, challenge incorrect results.

A blob is a fixed-size data object of 128 KiB. Instead of asking every validator to handle all blob data in the same way, PeerDAS uses sampling across data columns and erasure coding. The network’s design aims to make it possible to reconstruct the original data from enough of the distributed pieces while allowing individual validators to check a sample.

In practical terms, PeerDAS can support increased blob capacity while limiting the amount of data each participant must download. More room for rollup data can ease competition for blob space. If demand is high relative to capacity, that could reduce pressure on blob fees; if demand remains low, the upgrade may have little immediate effect on users’ costs.

It is important to separate four measures that are often collapsed into the word “throughput”:

• Blob capacity: how much rollup data Ethereum can include and make available over time.
• Rollup throughput: how many transactions a particular Layer 2 can process, influenced by its software, sequencer, and transaction mix.
• User fees: what users pay, which may include rollup fees, data costs, execution costs, and other charges.
• Finality and security: how quickly transactions reach the relevant confirmation threshold and what assumptions protect the rollup.

So PeerDAS does not promise a universal TPS multiplier. A simple transfer might use less data than a complex contract interaction, while compression techniques can let a rollup represent many actions compactly. The same blob capacity can therefore translate into different transaction counts across networks and over time.

The economics are also more nuanced than “more blobs equals free transactions.” Rollups may price in sequencer operations, proof generation, L1 settlement, and their own margins. For a closer look at these components, see ValorisVisio’s Layer 2 fee economics and L2 finality economics.

Fusaka Layer 2 throughput: what users and rollups may notice

The most direct benefit for Layer 2 users is potential relief when demand for Ethereum blob space is high. If a rollup’s data costs fall, its operators may have more room to lower fees, offer promotions, or handle additional activity. But passing savings through to users is a business and competition decision, not an automatic protocol rule.

Rollup operators may also find it easier to plan capacity when the network can accommodate more data. That can support higher activity during busy periods, but each Layer 2 still has its own bottlenecks: sequencer limits, prover performance, block production, withdrawal design, and the cost of keeping its system secure. PeerDAS addresses an important L1 data-availability constraint; it does not remove every scaling constraint.

The relationship between L1 blob fees and the fee a user sees can be indirect. A rollup may batch data, spread costs across a large number of transactions, or adjust its pricing at a different pace from the underlying market. For that reason, compare costs on individual networks rather than assuming that an Ethereum-wide capacity increase produces identical savings everywhere.

A practical comparison should include at least these indicators:

| Indicator | What it tells you | What it does not prove | |---|---|---| | Blob demand and blob fees | Whether rollups are competing for data space | That users receive all cost savings | | Rollup transaction counts | Whether a network is seeing more activity | That activity is organic or profitable | | Median user fee | The cost for a defined transaction type | The cost of every transaction or network | | L1 data cost per batch | A rollup’s settlement-data expense | Its full operating cost or security quality | | Confirmation and withdrawal times | Part of the user experience and trust model | That a rollup has no other security assumptions |

Use consistent periods and transaction types when comparing networks. For instance, compare ordinary token transfers with ordinary token transfers, and note whether a fee estimate includes only the sequencer charge or also the cost of L1 data and settlement.

Ethereum’s Layer 2 ecosystem is diverse, so aggregate charts can conceal differences between networks. The Growthepie L2 ecosystem resource is relevant when comparing activity across the ecosystem, while Ethereum L2 security economics helps put throughput claims alongside trust and settlement design.

Ethereum Fusaka upgrade in September 2026: metrics to track

The useful September 2026 question is not simply whether Fusaka increased theoretical capacity. It is whether the change is being used, whether costs respond, and whether the full system continues to meet its reliability and security goals. Check live network dashboards and protocol configuration rather than relying on old launch-era targets or a headline TPS claim.

Start with blob utilization and fees. Rising use alongside persistently high fees may indicate that demand is absorbing added capacity. Low fees and low utilization may mean there is room to grow, but they do not prove that new capacity caused adoption or that demand will persist.

Next, check rollup-level activity and fees. Look at transactions, active users where the methodology is clear, failed transactions, and comparable user costs. Keep in mind that activity metrics can be affected by incentive programs, automated transactions, and changes in how providers count users.

Finally, track network health and data availability. Sampling introduces operational requirements for clients and depends on the protocol’s data distribution and reconstruction assumptions. A capacity increase is only valuable if clients can keep up, data remains available, and the network continues to operate reliably.

Ethereum monitoring can help separate protocol performance from marketing claims. ValorisVisio’s guides to Ethereum network baselines and Ethereum data collection are useful context for assessing what metrics mean and how they are gathered.

When evaluating a throughput claim, ask the source for the measurement window, the Layer 2 included, and whether it reports theoretical capacity or observed usage. Also ask what transaction types were counted and whether the figure depends on assumptions about compression or future parameter increases.

Comparisons with other data-availability approaches need the same care. For example, Celestia’s block-capacity plans provide a useful scaling comparison, but raw capacity figures across different architectures are not directly interchangeable. Their security models, node requirements, and settlement arrangements differ.

Ethereum Fusaka upgrade risks, scenarios, and FAQs

For ETH users and investors, Fusaka is best understood as infrastructure that can influence adoption and costs, not as a direct tokenomics change or guaranteed price catalyst. More usable rollup capacity may help the Ethereum ecosystem compete for applications and users, but ETH’s market price also responds to broader liquidity, risk appetite, regulation, supply dynamics, and competing networks.

There are several risks to keep in view. Greater data capacity can increase demands on clients and network operators, while implementation bugs or operational issues could undermine expected reliability. Rollup fees may not fall in proportion to L1 data costs, and activity can migrate between networks without producing a corresponding increase in ETH demand.

A balanced scenario analysis should test at least three cases:

• Conservative: blob demand stays modest, user fees change little, and rollup activity grows slowly.
• Base case: rollups use more capacity over time, with selective fee relief and gradual ecosystem expansion.
• Upside: sustained demand, efficient rollup designs, and competitive user pricing reinforce one another.

These are scenarios, not predictions. Avoid building a valuation around a single throughput estimate; vary adoption, fee capture, and market conditions independently. Investors should also distinguish protocol success from token performance: a technically successful upgrade does not guarantee that ETH will outperform other assets.

What is Ethereum PeerDAS, and why does Fusaka include it?

PeerDAS is Ethereum’s Peer Data Availability Sampling approach. It lets validators sample distributed pieces of blob data rather than requiring each one to download every blob in full. Fusaka uses this design to help Ethereum support more rollup data while retaining a mechanism for checking data availability.

Will the Ethereum Fusaka upgrade make Layer 2 fees cheaper?

It may help reduce pressure on data fees when blob space is scarce, but lower user fees are not guaranteed. Rollup costs also depend on demand, batching, sequencer pricing, proof systems, and each network’s fee policy. Check actual, comparable transaction fees on the specific Layer 2 you use.

Does PeerDAS increase Ethereum transactions per second?

Not by itself in a fixed, universal way. PeerDAS can support additional rollup data capacity, which may allow Layer 2 networks to process more transactions. The result depends on transaction size, compression, rollup implementation, demand, and other network bottlenecks, so TPS claims need clear methodology.

What should I monitor after Fusaka in September 2026?

Track live blob targets and limits, blob utilization, blob fees, rollup-level activity, and comparable user costs. Also review client and network health, data-availability performance, and rollup security assumptions. Use current dashboards and configuration records because parameters and activity can change after an upgrade.

Conclusion: Fusaka and PeerDAS improve Ethereum’s ability to support rollup data, but the real test is whether increased capacity translates into reliable networks, sustained usage, and meaningful user value. Model conservative, base, and upside outcomes with the free ValorisVisio calculator rather than treating throughput as a guaranteed price signal.