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A safe failover design starts from one distinction: a device being online does not mean your API is healthy. Android reports network transitions, the HTTP client recovers from some route failures on its own, and your app decides which endpoint to use, whether to retry, and whether a repeated request could cause harm. Each of those responsibilities belongs to a different layer, and mixing them is how a brief outage turns into a flood of duplicate requests, stalled screens, or double-applied writes.
Separate the five responsibilities
Most resilient Android clients contain five distinct mechanisms. They overlap in what they look like from the user’s side, but they answer different questions and fail in different ways.
| Layer | Question it answers | What it does not do |
|---|---|---|
| OS network transitions | Is there a usable network, and did it change? | Tell you whether a specific API origin is responding |
| HTTP client route recovery | Can this connection or address be replaced for the same request? | Switch between separately configured API base URLs |
| Application endpoint selection | Which origin should this app talk to right now? | Decide safely on its own whether a write can be replayed |
| Retry policy | Should this operation be attempted again, and how long should the app wait? | Fix an expired credential or an invalid request |
| Persistent synchronization | Can work that must not be lost wait until conditions are right? | Make an interactive call complete immediately |
The practical consequence is that each layer needs its own limits. A retry loop in application code that does not know the HTTP client already retried a connection will multiply attempts. A failover rule that switches origins on every timeout will move traffic in the middle of a write that the first origin may have already committed.
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Connectivity callbacks from ConnectivityManager tell the app that a network became available, changed capabilities, or was lost. They are signals for scheduling work and refreshing state. They are not an endpoint health check.
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Three caveats matter for design:
- Do not query network state synchronously inside a callback. The API reference warns that values read this way can be outdated or null. Use the callback’s arguments, or re-query on a background path after the callback fires.
- Do not rely on
onLosing. It is not guaranteed to fire before a sudden loss, such as a radio dropping out, so the app must already handle a request that fails with no warning. - A network that is validated can still reach a dead API. Captive portals, DNS problems, a failed backend, and a TLS misconfiguration all leave the device “online” from the OS’s perspective.
Treat a transition as a reason to reconsider pending work, not as proof that the next request will succeed.
What the HTTP client already recovers
OkHttp can select an alternate route when connection establishment fails in limited cases, most commonly when a host resolves to several addresses. The OkHttp documentation describes this as transport recovery for that connection. It does not mean OkHttp will move a request from api.example.com to api-backup.example.com. Application-level origin switching is your code’s responsibility.
Before you add retries, check which client you actually use and which version it is. Your own loop should account for what the client already does. If the client may try several addresses inside one call, an application retry that adds another full attempt can produce more load than you intended. Count total attempts across both layers and bound them together.
Android’s media documentation recommends a single network-stack instance per app when using HttpEngine, Cronet, or OkHttp. That guidance sits in the media context, and the HttpEngine recommendation is explicitly tied to API 34 or S extensions 7. It is a useful reason to share one client instance, but it is not a universal rule for every Android network workload.
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Classify every failure before you retry
Retry decisions should start from the failure class, not from the exception type alone. The Android offline-first guidance recommends classifying network errors and setting a maximum retry count. It also says not to retry unauthorized requests until proper credentials are available.
| Failure | Typical signal | Retry guidance |
|---|---|---|
| No route or DNS failure before the request is sent | Connection or resolution exception | Retry with bounded backoff; the request was not sent, so write safety is not the constraint |
| Timeout before any response | Read or connect timeout with no status | Retry only if the operation is safe to repeat (see write safety below) |
| Unauthorized | HTTP 401 | Do not retry until a credential remedy exists, such as a token refresh or a fresh sign-in |
| Invalid request | Client-error statuses such as 400 or 422 | Do not retry unchanged; fix the input or surface the error |
| Server overload or temporary unavailability | Statuses such as 429 or 503 | Often retryable; honor a Retry-After header when the API sends one. Which statuses are retryable depends on the API contract |
No universal list of retryable status codes exists for Android. Each API defines its own status semantics, so the contract is the authority. Where the contract is silent, default to not retrying a status you cannot explain.
Check operation safety before replaying a write
A timeout does not prove that the server failed to apply a request. The client may have sent a payment or a record insert, and the response was lost on the way back. Replaying that write blindly can create a duplicate.
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Bound recovery in attempts and time
Every retry loop needs two limits: a maximum attempt count and an overall time budget that fits the user-facing deadline. A screen that must respond in five seconds should not spend nine seconds on backoff.
Android’s offline-first architecture documentation describes exponential backoff this way:
“In exponential backoff, the app keeps attempting to read from the network data source with increasing time intervals until it succeeds, or other conditions dictate that it should stop.” (Android Developers, offline-first architecture documentation)
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The phrase “other conditions dictate that it should stop” is the important part. Backoff without a stop condition is just an endless loop with longer gaps. The following helper combines an attempt limit, a time budget, a failure predicate, and cancellation handling:
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import kotlinx.coroutines.CancellationException
import kotlinx.coroutines.delay
suspend fun <T> withBoundedRetry(
maxAttempts: Int = 3,
budgetMs: Long = 10_000L,
initialDelayMs: Long = 500L,
isRetryable: (Exception) -> Boolean,
block: suspend (attempt: Int) -> T
): T {
val start = System.currentTimeMillis()
var delayMs = initialDelayMs
var attempt = 1
while (true) {
try {
return block(attempt)
} catch (e: CancellationException) {
throw e
} catch (e: Exception) {
val elapsed = System.currentTimeMillis() - start
val outOfBudget = elapsed + delayMs > budgetMs
if (attempt >= maxAttempts || outOfBudget || !isRetryable(e)) throw e
delay(delayMs)
delayMs *= 2
attempt++
}
}
}Pass a predicate that returns false for non-idempotent writes unless the server supports deduplication. If many devices retry at the same moment after an outage, add random jitter to each delay so they do not return in synchronized waves. The helper above omits jitter to keep the control flow visible.
Choose the right execution lifetime
Where the work happens determines how failures can be handled.
- Interactive, latency-sensitive calls run in the foreground with a short budget. If they fail, show the failure and let the user retry. Deferring them silently changes their meaning, for example a “send” that never happens until later.
- Durable synchronization should be written to local storage first and then sent by WorkManager. Android’s architecture guidance says WorkManager suits persistent work that can wait for connectivity and retry later. Use a connected-network constraint and a backoff policy, and keep a maximum retry count so unresolved work does not retry forever.
- Cached reads can serve stale data while a refresh is attempted. This is acceptable only when the screen can show that the data may be old.
WorkManager is not a way to make an interactive request complete immediately. Its value is surviving process exit and waiting for conditions. If a user is waiting, keep the call in the foreground and fail visibly.
Application endpoint failover: when it is justified
Switching among separately configured API origins is a service design decision, and Android’s documentation does not define one. Before adding it, confirm that the alternate origin offers compatible API versions and data semantics, and that a write accepted by one origin will be visible through the other.
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A usable design needs explicit answers to these questions:
- Health criteria: what counts as unhealthy, such as consecutive timeouts, a 5xx rate over a window, or a failed TLS handshake. Thresholds are service-specific and should be measured against your own traffic.
- State consistency: whether writes on one origin replicate before the other origin is used, and how conflicts are resolved.
- Authentication and TLS: whether tokens are valid across origins, and whether certificates and pins cover every candidate host.
- DNS behavior: whether a cached resolution can keep sending traffic to a dead address after failover.
- Failback: when and how traffic returns to the primary. There is no standard interval. Choose one that avoids flapping and document it.
If the service cannot answer these questions, a cached read or an offline queue usually provides more safety than a second origin.
Observe and test the failure modes
Log enough to explain each failover decision without recording credentials or sensitive payloads. Useful fields include the selected endpoint identifier, attempt number, failure class, elapsed time, and recovery outcome. Log hostnames and error classes rather than full URLs when query parameters may contain personal data.
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- DNS failure and an address that resolves but refuses connections
- A timeout before any response arrives
- A timeout after the server has applied a write
- An expired token that returns 401, confirming there is no retry storm
- Server overload returning 429 or 503 with and without
Retry-After - A Wi-Fi-to-cellular transition during an in-flight request and during a queued sync
These are recommended test scenarios. They describe what to verify in your own app, not measured outcomes from any particular implementation.
Quick Recap
Practical checklist
- Name the failover mechanism you actually need: route recovery, origin switching, cache, queue, or deferred work.
- Confirm which recovery steps the HTTP client already performs, and count attempts across layers.
- Classify each failure before deciding whether to retry.
- Confirm idempotency or deduplication before replaying any write.
- Set an attempt limit and a time budget that fit the user’s deadline.
- Move durable work to WorkManager with connectivity constraints and a retry cap.
- Add origin switching only with defined health, consistency, and failback rules.
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