1. Concurrency & Throughput

The problem: You want high throughput, but your design forces sequential access (everything in one shared object).

Why it happens: Sui parallelizes transactions that touch disjoint objects. A single “global counter” or monolithic registry becomes a bottleneck.

Step-by-step solution:

Prefer owned objects for per-user state. Each user’s actions then parallelize naturally.

Sharding pattern for shared state:

Create multiple shared “buckets” (e.g., 256 shards by hash of a key).

Route writes to the appropriate shard so contention remains low.

Use dynamic fields on parent objects to create scalable per-key storage without ballooning a single central structure.

Emit events for discovery; avoid centralized indexes inside a single shared object.

Quick check: If your hottest function always touches the same object, refactor to spread the load.

2. Gas Strategy & User Experience

The problem: Users hit “insufficient gas,” abandoned flows, or churn because they don’t understand coin objects.

Step-by-step solution:

Proactively merge dust:

Offer a one-click “Consolidate SUI” in your UI (call merge-coin under the hood).

Set predictable gas budgets:

Benchmark your calls on testnet; choose a budget that covers p95 costs with headroom.

Sponsored transactions (pattern):

For onboarding or promos, sponsor gas server-side so users can try the app without pre-funding.

Implement rate limits and abuse checks.

Batch where possible:

If users perform repeated micro-updates, consider a single “commit” call that processes many changes inside the Move entry function.

Common gotcha: A wallet may pick a tiny coin as gas, causing failure. Let users select the gas coin or auto-choose the largest one.

3. Storage Costs, Rebates, and Object Lifecycle

The problem: Storage bloat increases costs; you’re not reclaiming value from deleted data.

Sui concept: When you store data on-chain, you pay; when you delete it, Sui’s economics can return a storage rebate.

Step-by-step solution:

Design with deletion in mind:

Provide admin/user functions to reclaim obsolete objects (receipts, expired orders, draft states).

Use compact data formats:

Favor IDs and indices over large blobs inside objects; store bigger assets off-chain + on-chain references/hashes.

Batch cleanup:

Periodically run maintenance transactions that delete or compress inactive data and claim rebates.

Track storage over time:

Monitor object counts and average sizes; set alerts when growth deviates from plan.

4. Safe Access Control with Capabilities

The problem: “Who is allowed to call this mutation?” Without strict access control, your app can be griefed.

Step-by-step solution:

Mint a capability object at initialization (e.g., AdminCap).

Require &AdminCap (or ownership of it) in entry points that change critical state (fees, parameters, emergency pause).

For per-user rights, encode capabilities tied to the user’s address or object so they can’t be misused by others.

Avoid reliance on msg.sender-style checks: Move’s type system and capabilities are safer and more explicit.

Bonus: Log every privileged change with events for transparency.

5. Data Modeling with Dynamic Fields

The problem: You need a map (key → value) attached to some parent (like a marketplace, inventory, or profile) that can grow without locking a giant object.

Step-by-step solution:

Create a parent object (owned or shared) that will hold your dynamic fields.

Use dynamic fields to store key-value pairs under that parent.

Access by key in your entry functions; emit events so your indexer/front end can find additions/updates quickly.

Garbage-collect old entries to control storage.

Result: Massive scalability without contention on a single oversized object.

6. Shared Objects Without the Pain

The problem: You must coordinate global state (auctions, order books, on-chain games) but shared objects introduce contention and complexity.

Step-by-step solution:

Minimize shared state: Keep only what truly needs to be global (e.g., root registry, epoch parameters).

Layer your design:

Global shared registry → points to many child owned objects or sharded shared objects.

Make writes small:

Avoid heavy computation or large writes on shared objects; push per-user data to owned objects.

Use events as append-only logs for activity feeds instead of mutating large arrays on a shared object.

7. Testing, Fuzzing, and Failure Paths

The problem: Code works in happy-path tests but fails in production edge cases.

Step-by-step solution:

Unit tests with sui move test:

Cover not only success but expected failures (bad caller, missing capability, zero amounts, overflow).

Property testing/fuzzing (where available):

Assert invariants: balances never go negative, counts don’t overflow, capabilities aren’t leaked.

Simulate high contention:

Run parallel calls against your shared objects to observe conflicts and tune the design.

Production tip: Add telemetry to record failed error codes and parameters. That’s your roadmap to hardening.

8. Upgrades, Versioning, and Migrations

The problem: You need to upgrade logic without breaking data.

Step-by-step solution:

Keep the upgrade capability safe after your first publish.

Design for migration:

Versioned structs (e.g., V1, V2) and explicit migration functions.

Emit an event when migration completes.

Dry-run on testnet/devnet:

Publish the upgrade, run migrations on sample data, measure gas/time.

Announce a maintenance window (even though chain is live) so users expect temporary quirks.

Common pitfall: Changing a struct layout without providing a way to transform old objects. Always ship migration entry points with the upgrade.

9. Indexing for Real-World Frontends

The problem: Your UI needs fast queries (“show my positions”, “my NFTs”, “order history”) but raw node APIs can be slow/awkward for complex filters.

Step-by-step solution:

Design event schemas first (think: what will the UI need to filter by?).

Run or use an indexer to ingest events and object changes into a queryable store (SQL/GraphQL).

Keep deterministic IDs and include them in events so frontends can deep-link into any object.

Backfill and reorg handling:

Make your indexer idempotent; store last processed checkpoint; be able to rebuild from genesis if needed.

10. NFT & Game Patterns (high-churn objects)

The problem: Many mint/burn/transfer operations lead to fragmentation and gas surprises.

Step-by-step solution:

Lazy metadata: Keep heavy assets off-chain with content hashes on-chain.

Batch minting: Group operations under a single entry call when possible.

Ownership first: Favor owned NFTs; only share when game rules need global coordination.

Inventory using dynamic fields: Parent “Account” object → entries for each NFT/item for scalable lookups.

11. Incident Response & Kill Switches

The problem: A bug or exploit requires immediate action.

Step-by-step solution:

Admin capability must allow:

Pausing sensitive entry points,

Freezing minting or withdrawals,

Rotating authorities.

Emergency playbook:

Prewrite a runbook (who does what, where the keys are, how to communicate).

Post-mortem discipline:

Publish timelines, fixes, and compensations if applicable.

Add tests preventing the same class of bug.

12. Developer Quality of Life

The problem: Friction slows teams.

Step-by-step solution:

Makefiles or npm scripts to wrap common CLI actions (build, test, publish, call).

Templates for new modules and events so patterns stay consistent.

Pre-commit hooks to format Move code, lint, and run unit tests.

Environments as code:

Store RPCs, package IDs, and object IDs per-env in a small config file the app can read.

13. Launch Checklist (copy/paste)

All critical functions require the correct capability.

Shared objects are minimal; hot paths avoid contention.

Gas budgets tested at p95/p99; UX merges dust automatically.

Events cover every important state transition.

Indexer tested from clean slate and resilient to retries.

Upgrade capability secured; migration plan rehearsed.

Storage cleanup tools exist; rebates recoverable.

Runbooks for incidents and communications prepared.