L1 Era: Why Real-World Applications Are Moving Beyond Shared Blockspace
- Kamil Jakub Natil
- Dec 30, 2025
- 6 min read
Shared blockspace solved the last scaling crisis. It will not solve the next one.
For years, scaling in Web3 followed a clear trajectory. As demand increased, execution moved up the stack. Rollups absorbed congestion, reduced fees, and restored usability at a critical moment for Ethereum and the broader ecosystem.Â
Shared execution environments made it possible to scale while preserving strong security guarantees and reducing liquidity fragmentation, and for a long time, that trade-off worked. But as applications mature and new sectors enter the space, the limits of shared blockspace are becoming harder to ignore.
Fee markets remain volatile when multiple applications compete for the same shared execution environment. Execution environments are tightly coupled to upstream decisions, limiting how much teams can customize runtime logic, fee mechanisms, or upgrade schedules. Sequencers, which are responsible for ordering and batching transactions in many rollup architectures, introduce operational and governance risks because they often begin as centralized services and create single points of failure. Outages and downtime at the sequencer level can halt progress across an entire network. At the same time, centralized control over transaction ordering raises additional trust assumptions. At the same time, data availability and settlement layers ultimately bound throughput and scalability, since rollups must post transaction data and proofs back to an underlying layer, creating performance ceilings outside an application’s direct control.
These constraints are no longer theoretical for performance-sensitive applications. They are increasingly visible in production systems, particularly for teams building payments, trading engines, RWAs, gaming platforms, and other user-facing products where predictable execution and reliability are essential.
Modular infrastructure addresses these challenges by rethinking how blockchain systems are assembled. By separating core functions and making them composable, modular infrastructure makes sovereign L1s viable again, without reintroducing the operational complexity that once made them impractical.
What is Modular Infrastructure?
Modular infrastructure is fundamentally about separating concerns.
Instead of a single chain handling execution, consensus, data availability, and settlement at once, modular architectures split these responsibilities into independent layers. Each layer is optimized for a specific role and can evolve without forcing changes across the entire stack.
Execution environments can be tailored to application-specific workloads. Data availability layers can focus purely on throughput and cost. Consensus and security can be shared across multiple systems without locking them into a single execution model, an approach explored in practice through designs such as Tanssi’s modular consensus architecture (see Decoding Tanssi II).
This shift enables choice. Teams can decide how much control they want over execution, how they source security, and how they design upgrades and governance. Modularity is an architectural foundation for specialization.
Shared Blockspace Became a Limiting Factor
Shared blockspace simplifies early growth, but it imposes trade-offs that become harder to ignore at scale.
When applications share the same execution environment, they also share the same fee market. Spikes in upstream activity directly affect costs and latency, even when an application itself is not responsible for congestion. Performance becomes unpredictable by design. Layer-2 networks can still experience variable fee dynamics as demand shifts, with higher priority fees and data posting costs adding unpredictability during high-volume periods, even when average fees remain low under normal conditions.
Intense DEX usage drives more competition in slot bidding, pushing tip fees upward during peak hours. - Swaps with urgency (arbitrage, front-running) disproportionately increase gas costs. Historically, DEX swap priority fees made up 50%–70% of daily Base sequencer fees; - DEX-driven gas spikes are more volatile than simple transfer activity. During high-volume times, priority fees can dominate.
Control is also limited. Applications cannot fully customize runtime logic, fee mechanisms, or upgrade schedules. Governance decisions made at the base layer propagate outward, affecting all dependent systems.
Operational risk compounds the problem. Many rollup designs rely on centralized or semi-centralized sequencers. While this improves performance in the short term, it introduces single points of failure. Sequencers are responsible for ordering and batching transactions in many rollups, and their centralization creates operational and governance risk.
High-profile outages have demonstrated how dependent these systems remain on a narrow operational surface.
Sovereignty Without the Old Trade-Offs
Sovereign L1s are sometimes framed as a return to early blockchain models. In practice, what is emerging now is structurally different.
Modern sovereignty is not about isolation. It is about control over execution, economics, and governance when shared environments are no longer sufficient. Teams want predictable blockspace, application-specific logic, and upgrade paths aligned with their product roadmap rather than global consensus processes.
Historically, this level of control came at a high cost. Launching an L1 required bootstrapping validators, designing sequencers, setting up RPCs and explorers, managing indexing and monitoring, handling cross-chain messaging, and maintaining upgrades. Sovereignty was attractive in theory but prohibitive in practice.
Modular infrastructure changes this balance.
How Modularity Lowers the Barrier to Launching L1s
By decoupling execution from the rest of the stack, modular infrastructure allows teams to focus on what differentiates their application rather than on rebuilding infrastructure.
Security and consensus can be sourced from shared systems. Data availability can be provided by layers optimized for scale. Tooling for networking, monitoring, and upgrades can be standardized rather than rebuilt for every chain.
This reduces the cost of launching an L1 from a multi-month engineering effort to an infrastructure configuration problem. Sovereignty becomes an option earlier in a project’s lifecycle, rather than a distant ambition.
The missing piece is orchestration. Orchestration layers manage sequencing, validation, networking, and lifecycle operations across multiple chains in a unified way. This is what turns modular architecture into something deployable in production, not just theoretically scalable.
Security Without Compromise
Security has always been the most challenging part of launching a new chain.
Bootstrapping economic security from scratch is slow and risky. Low-security networks are vulnerable precisely when trust and reliability matter most. This challenge historically forced teams to choose between sovereignty and credible security.
Shared security models change that trade-off. Universal Staking by Symbiotic or Restaking by EigenLayer frameworks enable new L1s to align with Ethereum’s security assumptions while maintaining independent execution environments.
ETH-backed security allows application-specific L1s to inherit strong economic guarantees from day one. Teams can design sovereign execution layers without sacrificing security or relying on fragile validator sets.
For applications handling real value, whether financial assets, RWAs, or high-volume transaction flows, this alignment is critical.
From Architecture to Production
Modular infrastructure matters only if it translates into production systems.
Launching an L1 today no longer requires assembling every component manually. Builders can rely on orchestrated infrastructure, shared security, and standardized tooling to deploy chains that are robust from the start.
Tanssi exists to make this transition practical.
By orchestrating execution environments and integrating with Ethereum-aligned security models, Tanssi allows teams to launch dedicated L1s without building and operating the underlying infrastructure themselves.
For teams ready to experiment directly, launching an L1 becomes an accessible step rather than a long-term infrastructure commitment.
https://apps.tanssi.network
For builders who want to understand how modular components come together in practice, Tanssi’s documentation outlines the complete deployment model, from execution to operator management and upgrades.
https://docs.tanssi.network/builders/build/
What It Enables
For builders, modular infrastructure enables a different approach to scale.
Instead of optimizing around shared constraints, applications can define their own execution environments and evolve independently. Performance becomes predictable. Upgrades become intentional. Governance aligns with product needs.
For users, the benefits are concrete. Dedicated execution environments reduce congestion-related failures. Applications become more reliable, more responsive, and easier to trust over time.
As Web3 moves from experimentation to sustained usage, these properties matter more than raw throughput metrics.
Modular Infrastructure as the New Default
The move toward modular infrastructure is not a rejection of rollups or shared blockspace. These models solved real problems and will continue to play an important role.
What is changing is the default assumption. As applications become more demanding, shared execution environments are no longer the obvious choice. Modular infrastructure provides a path to sovereignty without sacrificing security or operational simplicity.
The next generation of L1s will be:
Application-specific,
Security-aligned,
and operationally streamlined.
Modular infrastructure is what makes that possible. This is now the default assumption for serious teams. For teams building long-lived systems.
About Tanssi
Tanssi delivers decentralized infrastructure as a service, empowering RWA and fintech clients to launch sovereign appchains effortlessly, without managing infrastructure complexity.