Monad: 9 Concepts Explained (Builder-First)
Nine practical ideas to understand how Monad targets high throughput while staying builder-friendly—plus what to change (and not change) in your dapp.
TL;DR - Monad aims for EVM familiarity, but high-throughput environments punish shared-state hotspots. - Use WSS for real-time UX, keep RPC for reads/tx submission, and design retries to be safe. - If you run infra, snapshots + observability are the difference between “incident” and “routine”.
If you’re a builder, you don’t need a thesis to ship on Monad—you need a mental model that keeps your app stable when usage spikes.
Start here: - What is Monad (60 seconds) - Monad RPC/WSS Quickstart
1) EVM compatibility (what it means for you)
Monad aims for a “feels familiar” experience for EVM builders: similar tooling, similar JSON-RPC shape, similar transaction flow.
Builder takeaway - Your stack (wallets, ethers/viem, Foundry) should stay recognizable. - The “how to build” doesn’t change as much as the “how to scale under contention”.
2) Parallel execution (why hot spots matter more)
Parallel execution systems try to do more work concurrently when transactions don’t collide.
Builder takeaway - Your biggest enemy becomes shared state contention: one popular contract/storage slot/object that everyone hits.
Common contention patterns: - One global counter everyone increments - One shared “settlement” mapping every user touches each block - A single contract that becomes the write choke point for everything
Design rule: prefer sharded/per-user state over global shared writes.
3) Deterministic results (don’t confuse “parallel” with “random”)
Even if work happens in parallel, the chain still needs a deterministic result so everyone converges on the same state.
4) Optimistic concurrency (assume it works, handle when it doesn’t)
Under heavy contention, some transactions may fail/retry more often.
Builder takeaway - Make writes idempotent (safe to resend) - Ship retry UX with backoff + jitter - Use dedupe keys in your backend queues
5) Throughput vs latency (why pipelining matters)
Pipelining overlaps steps (gossip → ordering/consensus → execution → state writes).
Builder takeaway Ship UX states that reflect uncertainty: - “accepted by node” - “included” - “N confirmations” - “finalized” (if/when exposed)
6) Burst traffic (your app will create its own DDoS)
If your app can spike (drops, claims), assume thundering herds.
Builder takeaway Add backpressure: - server-side rate limits - per-wallet throttles - queues for expensive ops - “soft waits” in UI
7) RPC vs WSS: treat them as two separate products
You build with two pipes: - RPC (HTTPS): request/response (read state, send tx) - WSS (WebSocket): streaming (new heads, logs, real-time UX)
Public endpoints we operate: - RPC: https://monad-mainnet-rpc.natsai.xyz - WSS: wss://monad-mainnet-rpc.natsai.xyz
8) Observability (the part builders skip until it hurts)
Log these on every submit: - tx hash - wallet - chain id - RPC method + latency - full error body - correlation id across your backend
9) Snapshots (your ops cheat code)
Rolling snapshots: - https://snapshots.monad.natsai.xyz
Restore runbook: - Monad Snapshots: Fast Sync & Restore
Quickstart
A) Quick RPC sanity test
~~bash curl -s https://monad-mainnet-rpc.natsai.xyz \ -H "content-type: application/json" \ --data '{"jsonrpc":"2.0","id":1,"method":"eth_blockNumber","params":[]}' ~~
B) Quick WSS sanity test (subscribe to new heads)
~~bash websocat -t wss://monad-mainnet-rpc.natsai.xyz/ <<'EOF' {"jsonrpc":"2.0","id":1,"method":"eth_subscribe","params":["newHeads"]} EOF ~~
Common errors
- Polling constantly instead of using WSS subscriptions.
- Building one shared write path (global counters/shared objects) that becomes a hotspot.
- Retrying without backoff/jitter (you amplify congestion).
- No correlation IDs (you can’t debug incidents fast).
FAQ
Do I need to rewrite my EVM app for Monad?
Usually no. The big changes are operational: avoid hotspots, make retries safe, and use WSS properly.
What breaks first under real traffic?
Shared-state write contention. Fix that before obsessing over micro-optimizations.
How should I implement retries?
Use exponential backoff + jitter, cap attempts, and add an idempotency key so resubmits don’t duplicate side effects.
Should I poll eth_blockNumber for UI updates?
No. Use WSS subscriptions and only fall back to polling if you must.
Related Natsai
- Monad RPC/WSS Quickstart
- What is Monad (60 seconds)
- Monad Snapshots: Fast Sync & Restore
- Enterprise support & keys: /contact/
