Packet loss can spike past 10% on satellite links, so resilient APIs must survive retries, reordering, and offline writes without data drift. Read now.
Why satellite links break ordinary API assumptions
Most APIs are designed for low-latency, mostly reliable paths: a request either succeeds quickly or fails cleanly. Satellite links break that model. Latency is high, loss can spike past 10%, and packets may arrive out of order or after the client has already retried. A naive retry loop can create duplicate writes, partial updates, and clients that believe they are in sync when the server has a different truth.
Resilient satellite APIs treat every call as potentially delayed, duplicated, or observed offline. The goal is not perfect connectivity; it is correctness when connectivity is intermittent and expensive.
Design for retries, reordering, and idempotency
Assume every mutating request may be sent more than once. Give each write a client-generated idempotency key so the server can apply the effect once and return the same result on replay. Prefer operations that commute or that can be merged with clear precedence rules instead of blind last-write-wins when concurrent offline edits are possible.
Reordering is common when multiple in-flight requests complete at different times. Do not rely on arrival order to reconstruct intent. Version each resource, include expected versions or etags on updates, and reject or queue conflicting changes instead of silently overwriting. Read-after-write on a high-latency link is unreliable; design reads to return explicit resource versions so clients can detect drift.
Offline writes without data drift
Satellite apps often need to queue work while disconnected, then flush when the link returns. Persist a local write log with stable operation IDs, timestamps of client intent, and dependency order where one write relies on another. On reconnect, replay in dependency order, not wall-clock order of when the radio came back up.
Server-side, accept offline batches as first-class input: validate each operation, apply idempotently, and return a per-operation outcome so the client can drop only what succeeded and keep what failed for repair. Never treat a successful HTTP status on a batch as success for every item inside it. Partial apply is normal; drift appears when clients clear the whole queue after a single ambiguous response.
- Use idempotency keys on every mutation, including those flushed from offline queues.
- Carry resource versions on reads and writes so conflict detection does not depend on arrival order.
- Return granular results for batch and replay APIs so partial success is explicit.
- Keep a durable client write log until the server acknowledges each operation by ID.
Practical API surface and operational habits
Keep payloads compact and prefer fewer round trips: composite reads, conditional updates, and server-side merge helpers reduce chatter on a lossy link. Timeouts should reflect satellite latency budgets; aggressive client timeouts that retry early amplify load and reordering. Prefer long-lived sessions or resumable streams only when mid-stream recovery is well defined; otherwise stick to short, restartable request/response units with clear checkpoints.
Instrument for duplication and conflict rates, not only latency. When retries and offline flushes are first-class paths, the important signals are how often the same key is replayed, how often version checks fail, and how long operations sit unacknowledged. Resilient satellite APIs earn trust by making retries, reordering, and offline writes safe by construction so data does not drift under packet loss.