An offline-first access controller should make credential decisions from authenticated policy stored locally and operate its relay without waiting for a cloud response. The difficult part is not simply caching permissions: it is defining which cached permissions remain valid during an outage, how a controller safely adopts updates after reconnection, and how synchronization avoids delaying live door decisions.
What does offline-first mean for a door controller?
It means the controller can evaluate an available credential against locally available authorization data and command the local relay even when its connection to a central service is unavailable. Cloud services can distribute policy and receive audit events, but neither should sit in the critical path between a credential presentation and the relay command.
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“Offline support” can describe several different arrangements, with different limits. A reader may cache credentials it has encountered; a controller may retain its last received configuration; or a credential may carry information used by an offline verification path. These are not interchangeable. In every case, an isolated device can only authorize from information it already has.
What do documented offline designs actually provide?
The following are product or project descriptions, not an independent performance comparison. The vendors’ materials do not establish a common definition of offline operation or a cross-platform latency guarantee.
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| Example | Where authorization data resides | Documented offline and recovery behavior |
|---|---|---|
| Kisi reader-cache path | Reader cache populated from recent credential use | Kisi says the cache can support outages for up to 36 hours and hold up to 1,000 access rights and 250 groups in less than 0.2 MB. Its feature description says changed credentials synchronize within minutes, while its API-to-reader-cache synchronization is once daily, at midnight. These are product-specific statements; the separate synchronization descriptions mean an engineer should verify when a particular change will be available on a particular offline path. (Kisi documentation; year not stated.) |
| Verkada controller | Controller’s last received configuration, with events stored locally | Verkada says a controller runs the last configuration it received and stores events for later upload. Its example says a badge added in the cloud while the controller is offline will not work at the door until the controller reconnects and receives the update; the example describes that update arriving within seconds, not a guaranteed convergence time. (Verkada, “Offline Operation”; year not stated.) |
| OpenLatch project | Cryptographically signed allow-list cached in ESP32 local flash | The project describes local access decisions and periodic synchronization of the allow-list from its backend. It illustrates signed local policy; it is not an independent benchmark or a commercial-platform service commitment. (OpenLatch project documentation; year not stated.) |
| Axis multi-controller configuration | Configuration distributed across controllers | Axis documents cases where configuration changes depend on a connected majority, with an offline controller receiving updates after reconnecting. It also describes regular synchronization of device events and schedules. (Axis documentation; year not stated.) |
These examples show why cache location, refresh behavior, local connectivity, and multi-controller consistency need to be evaluated separately. Kisi also documents reader-to-controller communication over UDP port 62435 and says local connectivity is needed for offline support; a local cache alone does not guarantee that the reader and controller can communicate during a network fault.
How should local policy and cache invalidation work?
Store a complete, authenticated policy version
Prefer a complete policy snapshot with an explicit version over a series of partially applied changes. Authenticate and validate a new snapshot before activating it, then switch to it atomically so a failed or interrupted transfer cannot leave a mixture of old and new permissions. OpenLatch’s signed allow-list is a documented example of signed local policy; versioning and atomic activation are architectural recommendations, not claims about that project or the commercial systems above.
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Make the stale-policy rule explicit
Record the active policy version and the time of its last successful update. Define what the controller does as that snapshot ages: for example, whether ordinary credentials continue to work, whether certain doors or higher-risk credentials require a fresher check, and what operators see when a device is beyond its allowed staleness window. These are decisions for the system’s threat model and operating requirements, not a universal setting.
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Define how new credentials become usable offline
Do not assume that a credential added centrally is immediately present in every cache. A recent-use cache, a full controller snapshot, and an offline credential-carried path may have different enrollment and refresh requirements. Confirm how the initial offline data set is populated, which changes trigger refresh, and what must happen before a user’s first offline presentation. Kisi’s documented recent-use cache and daily API synchronization illustrate why the population and update path matter as much as cache capacity.
How can relay latency stay predictable?
Keep the real-time decision path short and local: receive the reader’s credential result, perform the required local authorization and schedule checks, then issue the relay command. Do not make a cloud round trip a prerequisite for routine authorization. The cited documentation demonstrates offline operation, but does not establish a universal relay-latency figure or prove that a particular process, thread, or controller architecture will meet a target.
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- Give credential decisions priority over event upload, policy downloads, and other background work.
- Prevent synchronization from holding locks or exhausting CPU, memory, storage bandwidth, or connection capacity needed by the decision path.
- Bound the work required to evaluate a credential; avoid doing unbounded queue processing before issuing a relay command.
- Measure the physical result, not just a software or network response: time from credential presentation to the electrical relay transition.
The source scenario describes embedded Linux controllers, biometric terminals, encrypted RFID readers, OSDP v2.2 over RS-485, and a sub-200 ms response objective. Those are the scenario author’s assumptions and target, not verified characteristics of a deployed system or a published benchmark. Test the assembled reader, controller, wiring, and relay to determine whether it meets the actual requirement.
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What should happen when connectivity returns?
- Re-establish and authenticate the connection. Treat connectivity as restored only after the controller can communicate with the intended configuration service, not merely after a link light or network interface returns.
- Fetch and validate the newest complete policy. Verify authenticity and integrity before applying it. Reject malformed, incomplete, or older state according to the system’s version rules.
- Activate policy consistently. Apply the validated state atomically, then report the active version and synchronization status so operators can distinguish “connected” from “current.”
- Resume event upload without blocking access. Upload buffered events with stable sequence identifiers, tolerate duplicate or out-of-order delivery, and make retry handling idempotent. Reconciliation and event replay behavior must be designed and validated for the selected platform; the cited sources do not specify one universal protocol.
- Throttle background recovery work. Limit replay and synchronization resource use so current credential decisions keep priority while the backlog drains.
Reconcile policy before declaring the controller current. A reconnect does not itself prove that a revocation, new credential, or schedule update has been applied.
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How should the event backlog be bounded?
Persist events locally with sequence identifiers and monitor both queue depth and storage consumption. Set an explicit retention and overflow policy: the system must define whether it stops accepting new event records, overwrites old records, or raises an operational alarm when storage is exhausted. The appropriate behavior depends on audit and safety requirements; the available product descriptions do not establish a universal buffer size or replay rate.
Test event recovery while live credentials are being presented. A controller that eventually uploads every event is not sufficient if replay saturates storage or delays relay decisions during the process.
What should an offline-access validation plan cover?
Measure end-to-end from credential presentation to relay transition, and record authorization outcome, active policy version, connectivity state, and event-queue depth alongside each result. Test at least these conditions:
- Normal operation and WAN loss, including a prolonged partition.
- Credentials and schedules changed centrally while the controller is isolated, followed by reconnection.
- Event queue near its configured capacity, with replay and live access happening at the same time.
- Peak expected credential throughput and controller reboot or power recovery.
- Reader-to-controller communication failure separately from loss of the controller’s WAN connection.
- Multiple controllers when configuration propagation or a connected-majority rule is relevant.
Use the results to verify both the response-time requirement and the intended stale-policy rule. A timing result from a cloud request, a lab component, or an unloaded controller is not a measurement of the door’s physical response under degraded operating conditions.
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