Blockchain Basics Module

Scaling & Layer 2

How blockchains increase throughput without breaking base-layer guarantees

Core path (recommended): Why scaling exists → Trilemma → L1 vs L2 map → Rollups & proofs → Data availability → Blockspace budgeting

~60–90 minutes • Beginner → early intermediate

This is the required path to complete the module. All other articles are optional.

Start core path

What this module covers

Scaling is a system constraint, not just “more optimization”. Blockspace is scarce because decentralization and safety impose limits.

This module connects earlier modules into one causal picture: congestion → fees, execution costs → calldata/logs, and finality → settlement assumptions.

Hard stop: before protocol-specific L2s, app-level optimization, and advanced cryptography.

Time

60–90 min (recommended path)

Level

Beginner → early intermediate

Prereqs

Fees & Incentives + Consensus & Finality + Execution (helpful, not required)

This module is for

  • Anyone who wants a system-level understanding of L2 without protocol specifics
  • Developers making deployment decisions across L1/L2
  • Users trying to understand settlement, data availability, and UX trade-offs

This module is not

  • Protocol-specific L2s and chain-by-chain details
  • App-level optimization playbooks
  • Advanced cryptography deep dives

Stage 0

Orientation: Why Scaling Exists

Why can’t blockchains just “process more transactions”?

Treat scaling as a system constraint, not an optimization deficit.

Core

Beginner → Intermediate • 6-9 min • Concept

What Is Blockchain Scalability? (Sharding, Rollups, L2)

The scalability constraint (fees, throughput, latency) and why it frames all scaling approaches.

CORE • Step 1/6 • Coming soon

Why Block Space Is Scarce

Why blocks have limited capacity and why demand makes it expensive.

Supporting (intuition)

Optional intuition and mental models.

Coming soon

Latency vs Throughput Intuition

Why networking delays and capacity constraints don’t scale linearly.

Coming soon

Why “Bigger Blocks” Is Not a Free Win

How bigger blocks pressure propagation, storage, and node requirements.

Reference (how to observe the system)

Optional verification via explorers, clients, wallets, and documentation.

Coming soon

Throughput Comparisons (Conceptual, Non-Protocol)

A conceptual way to compare throughput claims without chain specifics.

You can move on when:

  • You can explain why block capacity is limited in decentralized systems.
  • You can connect scarcity to congestion and fees.
  • You can explain why “just make blocks bigger” isn’t free.

Stage 1

The Scalability Trade-off

What breaks when we try to scale?

Lock in the tension between throughput, decentralization, and security.

Core

CORE • Step 2/6 • Coming soon

The Scalability Trilemma

Why improving one dimension usually weakens another.

Supporting (intuition)

Optional intuition and mental models.

Coming soon

Why Decentralization Is a Constraint, Not a Preference

Why real decentralization imposes limits on throughput and hardware.

Reference (how to observe the system)

Optional verification via explorers, clients, wallets, and documentation.

Coming soon

Historical Scaling Debates (Conceptual)

A conceptual view of recurring scaling arguments without protocol specifics.

You can move on when:

  • You can explain the trilemma as a trade-off, not a slogan.
  • You can explain why decentralization is a constraint, not a preference.
  • You can connect scaling choices to node requirements.

Stage 2

Layer 1 vs Layer 2

What does it mean to move work “off-chain”?

Treat Layer 2 as an architectural technique, not “a separate blockchain”.

Core

CORE • Step 3/6 • Intermediate • 6-8 min • Concept

Layer 1 vs Layer 2

How base layers and execution layers differ and cooperate.

Supporting (intuition)

Optional intuition and mental models.

Coming soon

Bridges and Settlement Assumptions

High-level trust and settlement assumptions (no mechanics).

Reference (how to observe the system)

Optional verification via explorers, clients, wallets, and documentation.

Coming soon

Where Users Interact With L1 vs L2

A conceptual view of user touchpoints across layers.

You can move on when:

  • You can define L1 vs L2 roles (execution, settlement, data).
  • You can explain the main scaling approach categories (sharding, rollups, L2).
  • You can articulate bridge/settlement assumptions at a high level.

Stage 3

Rollups & Proofs

How can off-chain execution still inherit L1 security?

Treat rollups as execution off-chain with verification/settlement on-chain.

Core

CORE • Step 4/6 • Coming soon

Optimistic vs ZK Rollups

Two approaches to proving correctness.

Coming soon

Fraud Proofs and Validity Proofs

Challenges vs cryptographic proofs (conceptual).

Supporting (intuition)

Optional intuition and mental models.

Coming soon

Why Proof Systems Affect Latency and UX

Why challenge windows and proof generation affect user experience.

Reference (how to observe the system)

Optional verification via explorers, clients, wallets, and documentation.

Coming soon

Rollup Settlement Flows (Conceptual)

A conceptual flow of how rollups settle to L1.

You can move on when:

  • You can explain optimistic vs ZK at a high level.
  • You can explain fraud proofs vs validity proofs conceptually.
  • You can connect proof choices to latency/UX trade-offs.

Stage 4

Data Availability & Sharding

Why is publishing data as important as executing correctly?

Understand security depends on data availability, not just proofs.

Core

CORE • Step 5/6 • Coming soon

Data Availability Explained

Why users must be able to reconstruct state.

Coming soon

Sharding Basics

How increasing data bandwidth improves throughput.

Supporting (intuition)

Optional intuition and mental models.

Coming soon

DA Layers and Sampling Intuition

Why availability can be verified probabilistically (high-level).

Reference (how to observe the system)

Optional verification via explorers, clients, wallets, and documentation.

Coming soon

What Happens When Data Is Withheld (Conceptual)

Conceptual consequences of withheld data for users and safety.

You can move on when:

  • You can explain what data availability means.
  • You can explain why withheld data breaks user security.
  • You can explain how sharding increases data bandwidth.

Stage 5

Blockspace as a Budget

How do teams make practical scaling decisions?

Connect scaling architecture to cost, UX, and operational constraints.

Core

CORE • Step 6/6 • Coming soon

Blockspace as a Budget

Throughput, cost, and UX as trade-offs.

Coming soon

When to Deploy on L1 vs L2

A decision framework for architecture choices.

Supporting (intuition)

Optional intuition and mental models.

Coming soon

The Hidden Costs: Data, Indexing, and Infra

Operational and data costs beyond L1 execution.

Reference (how to observe the system)

Optional verification via explorers, clients, wallets, and documentation.

Coming soon

Typical Deployment Trade-offs (Conceptual)

A conceptual list of trade-offs teams compare.

You can move on when:

  • You can explain blockspace as a budget constraint.
  • You can describe a framework for L1 vs L2 deployment decisions.
  • You can name hidden infra/indexing costs.

Stage 6

Boundaries & Domain Closure

What scaling solves — and what it does not?

Close the domain without leaking into protocol-specific L2s or advanced crypto.

You now have the complete causal loop: shared state → scarcity → fees/incentives → ordering/MEV → execution costs → settlement/finality → scaling trade-offs.

Hard stop (covered later)

  • Protocol-specific L2s and chain-specific details
  • App-level optimization playbooks
  • Advanced cryptography deep dives

Leads naturally to

  • Advanced L2 architectures
  • Protocol design & economics
  • Application-specific scaling

Supporting (intuition)

Optional intuition and mental models.

Intermediate • 6–8 min • Bridge

Fees and Fee Markets Under Congestion

Congestion drives fee dynamics and changes UX.

Intermediate • 6–8 min • Bridge

Execution and Calldata / Logs Costs

Execution and data costs shape batching and rollup economics.

Intermediate • 6–8 min • Bridge

Consensus Finality and Settlement

Settlement depends on finality guarantees and canonical history.

Completion checklist

If you can answer these, you’ve closed Blockchain Basics.

  1. Why is scaling a system constraint in decentralized networks?
  2. What does the scalability trilemma mean in practice?
  3. What does it mean to move work off-chain (L2), and what stays on L1?
  4. How do rollups aim to inherit L1 security via verification/settlement?
  5. Why does data availability matter as much as correctness?
  6. How do teams treat blockspace as a budget for cost/UX/ops trade-offs?

FAQ

Related system guides

How rollups anchor to the base layerComing soon

A system view of how L2 state relies on L1 settlement.

Data availability and security assumptionsComing soon

How security depends on what data is available to users.

Key concepts

Open glossary

RollupComing soon
Layer 2Coming soon
SettlementComing soon

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