Introduction
Mobile users frequently lose connectivity—in elevators, on public transport, or in areas with unreliable coverage. An application that requires a network connection for every interaction can feel fragile even when its backend is healthy.
Offline-first design lets the application read or update local data and synchronize changes when connectivity returns. The hard part is deciding how to resolve conflicts and communicate synchronization status.
1. Choose a local source of truth
A local database can support cached reads and queued changes. Depending on the application, options include SQLite-based solutions, Isar, or other maintained storage libraries compatible with your requirements.
A repository can provide one interface to the UI while coordinating local and remote sources:
abstract class TaskRepository {
Future<List<Task>> getTasks();
Future<void> saveTask(Task task);
}The interface hides the storage strategy from widgets. The implementation can read local data immediately and synchronize with a remote API separately.
2. Track pending changes
When a user edits a task offline, save the change locally and mark it as pending synchronization.
A local record may include fields such as:
- A stable identifier
- The current data
- A modification timestamp
- A synchronization status
- A server version or revision, if supported
Do not rely solely on a timestamp to resolve every conflict. Device clocks can be inaccurate, and timestamps may not express which changes are semantically correct.
3. Design synchronization as a process
A basic synchronization cycle might:
- Find locally pending changes.
- Send them to the server.
- Process the server’s response.
- Mark successfully synchronized records.
- Fetch remote changes.
- Update local storage.
Handle partial failure explicitly. If the third operation fails, the application should not silently mark all pending records as synchronized.
Use stable operation identifiers and idempotent server endpoints where possible, so retrying after a timeout does not create duplicate records.
4. Define conflict resolution
Suppose a task is edited on two devices before either device synchronizes. The application needs a defined rule.
Possible approaches include:
- Last-write-wins for low-risk data
- Server-side version checks
- Field-level merging
- A conflict screen where the user chooses
- Domain-specific resolution rules
The right policy depends on the data. Overwriting a simple display preference is different from overwriting a shared financial or medical record.
5. Make synchronization visible
Users should understand whether their changes are saved locally, synchronized, or waiting because of an error.
A small status indicator can distinguish “Saved on this device,” “Syncing,” and “Could not sync.” Provide a retry path without forcing users to re-enter their work.
Avoid repeatedly prompting users about transient connectivity changes when the application can recover automatically.
6. Test interruptions and duplicate delivery
Test going offline during an edit, closing the application before synchronization, retrying a request after a timeout, and changing the same record on two devices.
These cases reveal the difference between a demo that works on a stable connection and an offline-first system that can be trusted.
Conclusion
Offline-first applications need durable local storage, explicit synchronization states, safe retries, and a conflict policy. Start with the user experience you need to support, then design the data model and synchronization process around those requirements.
