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A cellular handoff can interrupt a socket, but it cannot guarantee that a realtime score stream will resume without loss. Correct retention comes from the application contract: every score update needs a stable identity and ordered position, the client must persist the last position it has safely applied, and the server must define how far back it can replay. If that position is older than retained history, the API must return a complete authoritative snapshot and a new position from which incremental updates can continue.
This design separates radio behavior from data recovery. A phone may move between cells, switch access technologies, lose service in an elevator, or suspend the process in the background. In each case, the client should move through explicit reconnecting, stale, and resynchronizing states rather than assuming that a connected socket means the displayed score is current.
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A handoff only describes a change in network attachment or path; it does not promise that an application transport remains continuous or that missed messages will be replayed. RFC 3753, the IETF’s Mobility Related Terminology document from June 2004, distinguishes who initiates a handover and whether it is planned or unplanned. Those categories are useful vocabulary, not a guarantee about interruption duration, packet delivery, or application recovery.
During a planned transition, the operating system or modem may move traffic from one cell or access technology to another. During an unplanned event, coverage can disappear abruptly. Either case can produce a broken TCP connection, a stalled WebSocket, reordered packets, or a process that is suspended before it receives the final messages. The score API must therefore treat transport continuity and state continuity as separate concerns.
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- Transport question: can the client open or maintain a connection?
- Recovery question: which score state did the client apply, and what updates are missing?
- Freshness question: even if connected again, is the displayed state recent enough for the product’s promise?
A reconnect that merely creates a new socket answers only the first question. The other two require positions, retention rules, snapshots, and explicit status signals.
What should a score event and cursor contain?
Give each event a stable identity and a monotonic position within its score stream. The position can be a sequence number, revision, timetoken, or another resumable cursor; the exact representation is API-specific. Telegram’s official update documentation illustrates the pattern with sequence and state counters used alongside locally stored state to apply updates precisely and detect missed or duplicate updates.
Use a stream-scoped position
A position must be unambiguous for the stream the client is following. A simple event envelope can include:
{
"event_id": "match-4821:period-2:revision-193",
"stream": "match-4821",
"position": 193,
"occurred_at": "2026-10-26T19:42:11Z",
"kind": "score_update",
"payload": { "home": 2, "away": 1 }
}The syntax above is illustrative rather than a required wire format. What matters is that an event can be recognized after a retry, compared with the last applied position, and associated with one logical score stream. If a provider uses multiple counters, document which counter orders score changes and which counters cover other update classes.
Separate event identity from ordering
An event identifier answers “have I seen this exact update?” A monotonic position answers “where does it belong in the stream?” Keeping both lets a client handle a retried event whose position is already committed, and lets operators diagnose a missing range such as positions 194 through 197. Do not infer ordering from arrival time, device time, or the order in which callbacks fire.
Include a snapshot position
Every authoritative snapshot used for recovery should carry the position at which it was generated, or a cursor explicitly associated with that snapshot. Without that association, the client cannot know where to start incremental replay and may apply updates twice or miss updates between the snapshot and the next subscription.
How should the client commit score updates?
Persist the cursor only after the corresponding update has been applied safely to local state. This ordering is a design recommendation derived from cursor-based replay and duplicate handling: if a process records a position first and crashes before applying the event, a later reconnect can skip data that never reached the displayed state.
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- Read the incoming event. Validate that it belongs to the expected stream and that its identity and position are present.
- Compare its position with local state. An older or equal position may be a duplicate; a position greater than the next expected value indicates a gap.
- Apply idempotently. Update the score model in a way that can be repeated without creating an extra point, card, substitution, or other side effect.
- Durably save state and position together. Use one transaction where the platform permits it, or a journal that can be replayed after a crash.
- Acknowledge or advance the subscription. Only advertise the new position after the local commit succeeds.
The exact storage mechanism depends on the client platform. The invariant is more important than the database choice: a stored cursor must never claim progress that the application has not safely incorporated.
Why idempotency matters
Delivery outcome can be uncertain when a process stops between applying an event and sending an acknowledgement. A server may replay the event, or a client may receive it again after reconnecting. Handlers should therefore use event IDs, sequence checks, or a deterministic state transition so that the same event cannot produce a second external side effect.
For example, setting a score to “home 2, away 1” is naturally idempotent when tied to a revision. Incrementing the home score by one is not safe by itself; it needs a unique event ID or a previously recorded revision to prevent double counting.
How do reconnect and replay work after a handoff?
On reconnect, request updates after the last committed cursor, not merely updates that arrived after the socket was reopened. The following procedure handles both an ordinary short interruption and a longer outage.
- Mark the stream reconnecting. Stop presenting the connection as proof of freshness, and retain the last committed position locally.
- Open a new authenticated connection. The new connection is a transport event; it does not reset application state.
- Send the stream identifier and committed cursor. Ask for events strictly after that position, using the provider’s documented resume field.
- Process the replay through the same idempotent handler. Do not use a special, less-tested code path for replay.
- Check continuity. Verify that the first returned position is the expected successor, or that the API explicitly reports a complete replay.
- Return to live mode only after catching up. A socket can be open while the client is still processing a backlog.
- Persist each successful advance. Keep the cursor and score model consistent across crashes during replay.
PubNub’s architecture documentation describes a related approach: resume from the last received timetoken, use short-gap buffering, and use persisted history for longer gaps within its retention limits. Those are product-specific mechanisms; the general lesson is to make the resume position and the boundary of available history explicit.
What is the difference between cursor lifetime and event-retention lifetime?
A cursor can remain syntactically valid after the events it points to have disappeared. Cursor lifetime and event-retention lifetime are separate controls, so an API must document both. A client may possess a perfectly formatted position that the server can no longer use to reconstruct the missing interval.
| Concept | What it means | Failure the client must handle |
|---|---|---|
| Cursor validity | The server still recognizes the position format, stream, tenant, or subscription context. | The cursor may be accepted but cannot necessarily produce every intervening event. |
| Replay retention | How long the server keeps events in a replay buffer or persistence store. | A request before the retained boundary cannot return the complete event sequence. |
| Snapshot availability | Whether a complete current-state representation can be generated for the stream. | Without a snapshot, the client has no safe way to repair a gap after history expires. |
| Freshness window | How recent data must be before the product labels it current. | A connected client may still need a stale warning while data is old. |
Do not promise a universal number of minutes or hours. Retention should be sized from the maximum offline interval the product intends to recover, event volume per stream, expected bursts, and the operational cost of replay storage. State the guaranteed replay window in the API contract and state exactly what happens after it expires.
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How do you calculate a practical retention budget?
Start with a recovery objective, then model storage rather than choosing a round number. Let W be the guaranteed offline interval, R the average events per stream per unit of time, B a burst allowance, and S the encoded size of an event including indexes and operational overhead. A first-order capacity estimate is:
storage per stream ≈ (R × W + B) × S
This is a planning model, not a published benchmark. Measure event rates separately for quiet periods, active play, overtime, corrections, and provider-generated status messages. If a stream can fan out to many consumers, multiply by the number of retained streams and account for replication, indexing, and snapshots.
Write the guarantee in user terms
“The API supports resume” is incomplete. A useful contract says, for example, that a client can request events after a committed position while that position remains inside the documented replay window; after the window, the server returns a resynchronization outcome and a complete current snapshot. The contract should identify whether the window is configurable, whether it is measured from event time or ingestion time, and whether burst traffic can shorten practical recovery.
Budget for bursts and suspension
Cellular handoffs are not the only outage. Mobile operating systems can suspend a process for an unpredictable interval, and a user may reopen the application hours later. Include the longest interval the product actually promises to recover, not only the median handoff interruption. If the promise is deliberately narrower, expose that limitation in the client experience instead of silently showing an old score.
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What should happen when replay history has expired?
Return a clear resynchronization result rather than an empty success response. Data for Tennis’s live WebSocket documentation uses a RESYNC_REQUIRED outcome when the requested replay is no longer retained. Its documented recovery flow replaces local state with a current snapshot and then resumes incremental updates from the snapshot-associated cursor.
- Detect the expired position. The server should identify that the requested cursor predates retained history, not pretend that zero events means no changes occurred.
- Mark the client resynchronizing. The UI should distinguish this state from ordinary reconnecting and should avoid claiming that the score is current.
- Fetch or receive a complete snapshot. The snapshot must contain every field required to render a valid current score, not just the field that most recently changed.
- Atomically replace local state. Do not merge a partial snapshot with unknown intermediate history.
- Store the snapshot’s associated cursor. This is the new replay starting point.
- Resume updates after that cursor. Apply subsequent events with the normal idempotent and continuity checks.
A snapshot restores current state; it does not recreate omitted historical events. If the product needs a timeline, audit trail, or betting-grade record of every transition, that history requires a separately retained store and cannot be reconstructed from a current-score snapshot.
How can the API show whether a displayed score is fresh?
Expose freshness as an application state, not as a side effect of socket readiness. The live-score documentation cited above describes heartbeat and freshness fields and cautions that connection readiness does not prove prediction or score freshness. Use explicit timestamps, sequence positions, or provider freshness indicators so the client can make a visible decision.
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| Client state | Meaning | Recommended behavior |
|---|---|---|
| Connected and current | Transport is active and the client is receiving positions within the freshness policy. | Show the score normally and display the last-update time if useful. |
| Reconnecting | The transport is being reopened; no continuity claim has been made. | Keep the last value with a reconnecting indicator. |
| Stale | No update or heartbeat has arrived within the product’s freshness threshold. | Label the value as delayed or stale; avoid implying live accuracy. |
| Resynchronizing | A gap or expired cursor requires a snapshot replacement. | Prevent actions that depend on authoritative current state until recovery completes. |
| Current after snapshot | The snapshot was accepted and incremental updates have resumed from its cursor. | Clear the resync warning and continue normal processing. |
Keep the thresholds configurable per product requirement. A scoreboard may tolerate a visible delay; an automated action may require a stricter freshness policy. The API should supply the facts, while the client decides how to present them.
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Make these outcomes explicit in the contract and telemetry. A duplicate is an event whose identity or position is already committed; it can be acknowledged without changing state. A gap is a position beyond the next expected value, and it requires replay, buffering under a documented limit, or resynchronization.
- Duplicate: record the event as already applied and do not repeat side effects.
- Expected successor: apply it, persist the resulting state and cursor, then continue.
- Future position: stop normal application, request the missing range, and preserve the later event only if the API defines safe buffering.
- Older position with a different payload: treat it as a data-integrity error and escalate; never overwrite newer state silently.
- Malformed or wrong-stream event: reject it and emit an observable protocol error.
Do not hide gaps by sorting events according to device timestamps. Clock skew and corrections can make timestamps unsuitable for causal ordering. The stream position supplied by the authority should control ordering.
What changes when the app is suspended or restarted?
Process suspension turns a short network interruption into an unknown offline interval. Persist the last committed cursor and the minimum score state needed to render a defensible value before suspension. On restart, load that state, mark it stale until a successful replay or snapshot, and then follow the same reconnect algorithm used after a handoff.
Do not delete the cursor merely because the previous socket closed. Deleting it forces an unnecessary full resynchronization and can conceal whether history was actually available. Conversely, do not retain it indefinitely without recording the stream identity, authentication context, and the time it was last committed; a cursor from another match or an obsolete subscription must not be applied to a new stream.
Which API designs are easiest to operate?
There is no vendor-neutral ranking in the cited material, but the following comparison highlights the decisions an engineering team should make before implementation.
| Design choice | Strength | Risk or question to resolve |
|---|---|---|
| Monotonic sequence per score stream | Simple gap detection and deterministic ordering. | Define behavior when events are corrected or streams are partitioned. |
| Opaque resumable cursor | Lets the provider change storage and encoding without exposing internals. | Document expiry, scope, and whether it survives client restart. |
| Event replay plus authoritative snapshot | Covers both short gaps and outages beyond retention. | Ensure the snapshot is complete and carries its starting cursor. |
| Short-gap buffer only | Low storage and fast recovery for brief interruptions. | Longer outages need a documented full resync path. |
| Heartbeat and freshness metadata | Separates a live socket from a current score. | Define thresholds and what each heartbeat actually proves. |
| Exactly-once external effects | Can simplify downstream accounting when genuinely supported. | Do not assume it; the Data for Tennis documentation, for example, limits exactly-once guarantees for external side effects. |
Evaluate each provider or internal service against seven questions: Is the replay window documented and configurable? Does the cursor survive a client restart? Are event identity and ordering guaranteed? How are duplicates and gaps signaled? Is the snapshot complete and tied to a cursor? What freshness or heartbeat fields exist? What exact response is returned after replay expires?
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How do you test retention across real handoffs?
Test the application boundary independently from radio performance. A lab handoff that keeps the socket alive does not prove that recovery works, and a forced socket close does not prove that the modem caused it. Exercise the following cases with recorded event sequences and assertions on final state.
- Close the connection between two consecutive events and verify that replay returns the missing event exactly once.
- Deliver the same event twice and confirm that the score and every external side effect remain unchanged.
- Deliver a future position first and verify that the client detects a gap instead of applying it out of order.
- Stop the process after applying an event but before cursor persistence, then restart and confirm safe replay.
- Stop the process after cursor persistence but before state application in a fault-injection test; the implementation should prevent this ordering or recover from its journal.
- Use a cursor older than the configured replay window and verify a clear resynchronization response plus a complete snapshot.
- Reconnect successfully but suppress updates and heartbeats; confirm that the UI becomes stale even though the socket reports connected.
- Replace a snapshot while a correction event is in flight and verify that the associated cursor prevents omission or double application.
Record the stream ID, last committed position, requested cursor, server response, snapshot position, and final position for every test. These fields make production incidents diagnosable without guessing whether the failure was cellular, transport, storage, or contract-related.
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What should be monitored in production?
Monitor the boundaries that determine correctness, not only connection counts. Useful measures include reconnect attempts, time spent reconnecting, replay distance, expired-cursor responses, snapshot frequency, duplicate rate, detected gaps, stale duration, and the age of the oldest displayed data. Break them down by device platform, access technology, application version, and stream type so a modem issue is not confused with a retention-policy issue.
Alert on a rising expired-cursor rate, because it means the guaranteed replay window is shorter than the outage pattern or that clients are failing to commit progress. Alert separately on snapshot failures and on freshness violations after a socket is connected. A healthy connection metric alongside stale scores is a contract or processing failure, not a successful recovery.
What is the concise design rule?
Budget retention around the outage you promise to recover, then make the boundary observable. Commit ordered, idempotently applied events; resume from the last committed cursor; detect gaps and duplicates; and return a complete snapshot with a new cursor when history has expired. Treat handoff, connection, replay, and freshness as four different states in both the API and the user interface.
Frequently Asked Questions
Can a WebSocket keep a score accurate during a cell-to-cell handoff?
It may remain open, but socket continuity alone does not prove that every event arrived or that the score is fresh. Accuracy still requires an ordered cursor, duplicate-safe processing, and a replay or snapshot path after any detected interruption.
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Should a mobile client store the last received event or the last applied event?
Store the last event position that has been applied and durably committed with the corresponding state. Recording arrival before application can cause a crash to skip an update on the next reconnect.
What if a provider returns an empty replay response?
An empty response is safe only when the provider explicitly guarantees that the requested cursor is current and retained history has no events after it. Otherwise, require a documented status that distinguishes “no new events” from “cursor expired” or “resynchronization required.”
Do snapshots preserve the complete scoring history?
Usually they restore the authoritative state at one position, not every historical transition that led to it. Keep a separate event or audit store if users or downstream systems need the omitted timeline.
How should a UI label a score after the app was backgrounded?
Load the cached value but mark it stale until replay or snapshot recovery completes and freshness criteria are met. A successful network connection should clear the warning only after the application has caught up to an authoritative position.
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