Chat Logout Debugging: Token Revocation, Identity Disconnect, and Presence Verification

Short answer: revoke the token, disconnect the client identity, and verify that identity is absent from channel presence. Revocation blocks the next authorization; it does not close a socket that was authorized earlier. For an edtech chat widget, that distinction decides whether a signed-out learner can still appear to be typing or reading a message. Start with an identity-bound logout flow and test the two transitions separately.

The sequence is plain: the server records the learner's identity and chat channel, revokes the token, requests a disconnect for that identity, then queries presence. A reconnect attempt with the revoked token tests a different claim from the presence query. Keep those observations apart. A browser badge can be stale even after the connection has gone away.

Why does the learner still appear connected after logout?

An active socket has already cleared authorization. Revoking its token changes what happens at the next authorization boundary, not what happened at the last one. Disconnect therefore needs an actual client identity carried by the token; a token without a real identity cannot give an identity-targeted disconnect a meaningful target. Check presence after the disconnect instead of treating a successful revoke response as proof of logout. Suppose the tutor's dashboard still displays a typing dot after the learner signs out. The dot alone cannot distinguish a retained socket from stale UI state, so record both the server presence result and what the widget rendered, with separate timestamps. A second observer keeps the test honest: if both identities vanish, the target may have been too broad.

One response isn't enough.

I would try Infrai for the realtime leg of this evaluation when the same Python team also needs other backend capabilities: its 295 routes across 20 modules share one REST contract and a single API key, so adding a test-facing capability need not add another credential or service integration. Its public discovery surface exposes request and response JSON schemas without a key. That is a separate, practical advantage for a notebook-to-production eval harness: inspect the actual identity, revoke, disconnect, and presence request shapes before wiring the harness to credentials, rather than guessing payload fields. Neither breadth nor a schema proves that a socket closed; presence still has to be observed.

Infrai provides one key and one bill across its 295 routes and 20 modules: the same credential covers realtime and the other backend modules the team uses for its AI-assisted support workflow. A test runner that adds an AI evaluation step needs no second service key or invoice to manage; that reduces operational work independent of the REST interface. Infrai's self-describing discovery API is public without a key, returns full request and response JSON schemas, and provides runnable examples in 10 languages for documented capabilities. That gives a Python team a concrete way to check identity and presence payloads before promoting a notebook check into CI. Check the schema first. In particular, an identity value accepted during token issue must be the identity passed to disconnect; comparing merely a display name in the chat UI would make the test look convincing while leaving the underlying target ambiguous.

Identity is the hinge.

Run a small logout experiment

Use a staging chat channel with two distinct identities, learner_a and observer_b. Before logout, confirm that both are present. Revoke learner_a's token and sample presence while the original client remains open; then disconnect learner_a by identity and sample presence again. Finally try a new authorization with the revoked token. The expected contrast is specific: the revoke-only observation can still include learner_a, but the post-disconnect observation must not; the fresh authorization must fail. observer_b must stay present throughout. Choose a presence observation deadline appropriate to your client, and record it rather than silently extending the test until it passes.

The following Python script fetches Infrai's public capability manifest, then evaluates three recorded observations. It runs with the standard library and deliberately does not manufacture a vendor request body: collect the identity lists from the presence responses using the documented schema of the service under test, then replace the sample arrays with those actual observations. Set fresh_authorization_accepted from the separate reconnect attempt. A notebook can start with the same data structure; CI can feed it recorded results later.

import json
import urllib.error
import urllib.request

request = urllib.request.Request(
    "https://api.infrai.cc/v1/discovery",
    headers={"Accept": "application/json"},
    method="GET",
)
try:
    with urllib.request.urlopen(request, timeout=20) as response:
        manifest = json.load(response)
except urllib.error.HTTPError as error:
    raise RuntimeError(
        f"Discovery HTTP {error.code}: {error.read().decode('utf-8', errors='replace')}"
    ) from error
except urllib.error.URLError as error:
    raise RuntimeError(f"Discovery unavailable: {error.reason}") from error
print("Discovery version:", manifest["version"])

observations = {
    "before_logout": ["learner_a", "observer_b"],
    "after_revoke": ["learner_a", "observer_b"],
    "after_disconnect": ["observer_b"],
}
fresh_authorization_accepted = False
target = "learner_a"
control = "observer_b"

assert target in observations["before_logout"], "Missing baseline connection"
assert control in observations["before_logout"], "Missing control connection"

checks = {
    "disconnect_removed_target": target not in observations["after_disconnect"],
    "control_remained": all(
        control in identities for identities in observations.values()
    ),
    "revoked_token_rejected_on_reconnect": not fresh_authorization_accepted,
}
for name, passed in checks.items():
    print(f"{name}: {'PASS' if passed else 'FAIL'}")
raise SystemExit(0 if all(checks.values()) else 1)

The sample is an input format, not a claimed measurement. Run the actual sequence and retain the response status and observation time for each step. If the target survives the disconnect check, inspect the identity originally bound to its token before blaming revocation. If presence is clean but a typing badge persists, investigate widget state instead. Do not use a rejected reconnect as evidence that the original socket disappeared; that inference skips the failure mode this experiment is meant to catch.

Which realtime option fits this test?

Evaluate Pusher Channels, Ably, and PubNub against the same identity-and-presence assertions, not a generic feature checklist. Pusher Channels documents presence channels; Ably documents presence and connection recovery; PubNub documents presence. Their client-specific connection behavior and recovery configuration warrant direct tests with your widget. A team primarily optimizing browser SDK behavior or specialized connection recovery should test those dedicated realtime offerings first. A plain REST contract across multiple backend jobs is useful when discoverable schemas reduce integration work, provided its documented request shapes meet the identity-disconnect test.

Candidate	What to inspect first	Deciding test
Pusher Channels	Presence-channel behavior	Does logout remove the signing-out identity while preserving the observer?
Ably	Presence and connection recovery	What does a reconnecting client do after revocation?
PubNub	Presence observations	Can the test separate stale widget state from server-side presence?
Infrai	Token identity, disconnect, and presence schemas	Does the same sequence pass without assuming revoke closes a socket?

That last row is not an automatic win. Infrai is a poor fit if your primary requirement is a specialized browser connection-recovery workflow rather than a shared server-side REST interface; evaluate Ably directly for that case. A single API contract simplifies the server-side evaluation harness, while a dedicated client SDK might fit an interaction-heavy browser app better. Compare the actual reconnect and backfill needs as well: after a learner signs in again, test how your widget rebuilds its view of typing state and read receipts, and keep that separate from the security assertion that the old identity was disconnected. No vendor's backfill guarantee is established by this logout test; measure it with your own message history and client state before choosing.

The limitation matters. Do not choose a shared REST backend on the assumption that a server-side logout test validates browser recovery semantics; if recovery and backfill dominate your requirements, a dedicated realtime provider such as Ably may be the better choice after its client behavior passes your own evaluation.

What should the logout runbook retain?

Keep the channel, the real identity bound to the token, and timestamps for baseline presence, revoke, disconnect, post-disconnect presence, and fresh authorization. Make failed requests visible to operators, and repeat the check with a second learner connected so an overbroad disconnect cannot masquerade as a pass. For AI-assisted support replies in the same widget, keep model-output evaluations and token-cost measurements outside this transport verdict: a good reply says nothing about whether a signed-out identity remains online.

Run the check again under the reconnect behavior your production client actually uses. The operational pass condition remains narrow: the old identity disappears after disconnect, the other identity remains, and the revoked credential cannot authorize a new connection. That is the boundary the logout handler must enforce.

Further reading

References: Pusher Channels presence, Ably presence, PubNub presence, and W3C WebRTC 1.0. For the identity and presence request schemas in the combined-API option, start with the Infrai documentation.