Best Practices for Structuring RTK Query API Slices in Large Applications
When building large-scale applications, organizing RTK Query API slices properly ensures your codebase remains modular, maintainable, and easy to scale. A good structure helps with team collaboration, reusability, and performance.
1. Use a Feature-Based Approach: Group endpoints by domain or feature (e.g., usersApi, postsApi) instead of having one massive API slice.
2. Create a Shared Root API: Define a common createApi instance (with shared baseQuery, headers, and tag types) and extend it with injectEndpoints for modularity.
3. Use Consistent Tagging: Define clear tagTypes to manage cache invalidation across different slices.
4. Co-locate APIs with Features: Place API files alongside their corresponding feature components and Redux slices for better discoverability.
5. Keep API Logic Pure: Avoid adding UI or business logic inside API definitions—use onQueryStarted only for small side effects like optimistic updates.
6. Re-export Hooks: Only export the generated hooks (e.g., useGetPostsQuery) from each API slice to keep imports clean and maintain encapsulation.
7. Use TypeScript for Strong Typing: Ensure your endpoints have typed request parameters and responses for better safety and autocompletion.
This modular approach lets you split endpoints across files, improve code organization, and scale the app as it grows — while keeping all API logic under a consistent root.
- Scalability: Easily add or modify feature APIs without touching unrelated code.
- Maintainability: Clear structure improves readability and debugging.
- Modularity: Independent feature slices allow better code reuse and lazy loading.
- Team Collaboration: Different teams can safely manage different slices.
Following these practices helps large applications stay efficient, organized, and easier to maintain as the codebase evolves.
You need to set up a new Redux Toolkit store for a simple counter app. Walk me through the code you'd write to configure the store, including any default middleware.
If you forget to add the counter slice reducer when calling configureStore, what will happen when you dispatch an action?
How would you enable Redux DevTools only in a development build using configureStore?
We're adding a custom logger middleware alongside RTK's defaults. How would you modify the store configuration to include it without breaking the default behavior?
During a code review you notice the store is being created inside a component, causing multiple store instances. How would you refactor the configuration?
After upgrading to RTK 2.0, an async thunk started failing with a type error. Which part of the store setup would you inspect first and why?
Our app is split into several micro‑frontends that need to share an auth slice but have independent feature slices. How would you design the Redux Toolkit store configuration to support shared and isolated reducers while keeping middleware consistent?
We observed a performance regression after adding many reducers; the UI feels sluggish. What store configuration options or patterns could you adjust to mitigate this?
We need to lazy‑load feature reducers only when the user navigates to certain routes. Explain how you would set up the store and integrate reducer injection with configureStore.
The company is migrating a legacy Redux codebase (using createStore, combineReducers, and manual middleware) to Redux Toolkit across multiple teams. What strategy would you propose for configuring stores to minimize disruption, ensure type safety, and allow incremental migration?
Several teams want to share a global store but also maintain independent release cycles. How would you architect the store configuration, versioning, and middleware to support this long‑term, considering CI/CD and backward compatibility?