API7 Gateway 3.10.8: Make Rate Limits Explain Their Decisions

Key Takeaways

API7 Gateway 3.10.8, released on October 9, 2026, makes rate-limit evidence more explicit across distributed API and AI traffic.
AI Rate Limiting cost_expr can address nested numeric usage fields such as input_tokens_details__cached_tokens; these joined names require a 3.10.8 Data Plane, while older instances evaluate them as 0.
For Limit Count, Limit Count Advanced, GraphQL Limit Count, and AI Rate Limiting, $rate_limiting_info now reports window, counter, increment, decision, sliding-window, and delayed-synchronization context as JSON. A counter update failure is recorded as decision: error, not disguised as a rejection.
A 3.10.8 fix for Limit Count, Limit Count Advanced, and GraphQL Limit Count prevents an instance serving only rejected requests from continuing to reject against stale cached quota when sync_interval is enabled.
Redis TLS connections now send a server name through redis_server_name or a hostname-valued redis_host, helping plugins connect to managed Redis endpoints that route TLS by name.
Delayed synchronization is still approximate across workers and gateway nodes, and response-derived AI usage is still committed after delivery for later decisions. The release improves correctness and evidence without removing those boundaries.

A rate limit is easy to describe as a number: 1,000 requests per minute, 100 concurrent connections, or 500 model tokens per subscription. Production behavior is harder. The decision may depend on a local snapshot, a Redis-backed counter, a sliding-window estimate, or usage that becomes known only after an LLM finishes responding.

When operators see HTTP 429, they need more than the status code. Which window was used? Did the request add one unit or 200 tokens? Was it rejected by policy, or did the counter backend fail? If one gateway instance only sees rejected traffic, is it refreshing the shared state or extending an old decision?

API7 Gateway 3.10.8 addresses that operational gap. It improves nested AI usage accounting, expands decision telemetry, fixes stale-state behavior under delayed synchronization in Limit Count, Limit Count Advanced, and GraphQL Limit Count, and sends the TLS server name required by many managed Redis services. The result is not mathematically exact limiting in every mode. It is a clearer contract between configuration, runtime decisions, and the evidence teams use to verify them.

flowchart LR
    request[Current Request] --> decision[Pre-response Quota Decision]
    decision -->|Allowed| upstream[Upstream or Model]
    decision -->|Rejected| reject[Policy Response]
    decision --> evidence[JSON Decision Evidence]
    upstream --> response[Response Delivered]
    response -. Usage committed in log phase .-> counter[Updated Counter]
    counter --> later[Later Request]

The dotted path is important: response-derived AI usage updates a counter after the current response. It can affect a later request, but it does not retroactively block the response that produced the usage.

A 429 Is an Outcome, Not an Explanation

Distributed rate limiting separates several questions that dashboards often collapse into one chart:

What is the key? A consumer, subscription, route, client address, or another configured value may own the quota.
What is the cost? A request may count as one unit, a calculated GraphQL cost, or usage reported by an AI provider.
Where is the state? The counter may be local or shared through Redis, Redis Cluster, or Redis Sentinel.
When is state synchronized? Direct synchronization reads and updates shared state per request; delayed synchronization temporarily accumulates local increments.
What actually happened? The policy may allow or reject a request, while the counter update itself may succeed or fail.

The last distinction matters during an incident. A rejection is a policy decision based on available state. A counter update error means the gateway could not complete part of the accounting path. Those conditions should not be logged as though they were the same event, and neither label alone describes every caller-facing consequence of a particular plugin configuration.

API7 Gateway 3.10.8 gives operators enough structured context to keep these questions separate.

Account for Nested AI Usage Without Pretending to Know the Future

AI providers increasingly return usage as a nested object. For example, the OpenAI Responses API reports cached input tokens as cached_tokens inside input_tokens_details. In 3.10.8, AI Rate Limiting can expose that numeric value to cost_expr as:

input_tokens_details__cached_tokens

Top-level usage fields keep their existing names, so current expressions do not need to change. The joined name is a Data Plane capability, however. A Data Plane earlier than 3.10.8 evaluates it as 0, which can make a mixed-version gateway group charge less than the expression intends.

Do not add a nested field to production policy immediately after upgrading only the Control Plane. Wait until every Data Plane that can serve the route runs 3.10.8, then send provider responses that contain the field and verify the committed cost. Also confirm the provider's semantics before combining fields: a nested cached-token value may be a subset of a top-level total rather than an additional amount.

The timing boundary remains unchanged. Current AI Rate Limiting documentation states that response usage is committed in the log phase because it is not available when the request is admitted. The first successful response can therefore show the quota before its own usage is charged, and a later request sees the updated counter.

This is after-delivery accounting, not pre-request prediction. Use it to govern cumulative consumption over time, and keep separate request-size, concurrency, or upstream controls for risks that must be bounded before a model response completes.

Make Decision Evidence Machine-Readable

In Limit Count, Limit Count Advanced, GraphQL Limit Count, and AI Rate Limiting, the $rate_limiting_info variable now describes the window in which a request was counted. Depending on the configured algorithm and synchronization mode, its JSON can include:

window type and size;
whether the request was allowed or rejected;
the increment added to the counter;
current-window start, end, and count;
the weighted previous window used by a sliding window; and
the snapshot used by a delayed-synchronization decision.

When the counter cannot be updated—for example, when Redis is unreachable—the variable records decision as error instead of making the event look like a policy rejection. A key containing a quote or backslash is now escaped as valid JSON as well.

These improvements require a log-pipeline change. The field order is no longer fixed, and future versions may add more fields. Parse the value as JSON and select keys by name. A positional parser that expects the old serialization can silently attach the wrong meaning to a new field even though the JSON itself is valid.

Treat decision: error as an investigation signal, not a complete statement about the client response. Correlate it with the plugin, policy, gateway log, Redis health, and caller-visible status. The variable reports rate-limit state; it does not replace end-to-end request telemetry.

Delayed Synchronization Still Trades Exactness for Fewer Redis Round Trips

By default, Redis-backed limit-count policies synchronize on every request. Operators can set sync_interval to accumulate increments locally and send them to Redis on an interval. The current documentation requires at least 0.1 seconds and a value smaller than a numeric time_window; -1, the default, keeps direct synchronization.

The trade-off is deliberate. Before local increments synchronize, workers or gateway nodes can hold different views of the shared counter. Concurrent requests can exceed the configured count during that interval. Use direct synchronization when exact shared enforcement matters more than reducing Redis traffic.

For Limit Count, Limit Count Advanced, and GraphQL Limit Count, API7 Gateway 3.10.8 fixes a separate correctness problem inside that approximate mode. With sync_interval configured, an instance serving only rejected requests could stop refreshing its cached quota after its local count expired. It continued rejecting against stale state until the cached quota expired. With a sliding window, it could also keep applying the previous window's weight for the rest of the window and allow far fewer requests than configured. When Redis was unreachable, the same path could charge the local fallback counter during each synchronization even though the instance had admitted no request.

The fix removes those stale-rejection and fallback-counter effects. It does not make delayed synchronization exact, merge all in-flight local increments instantly, or remove the need to test failure behavior for the selected Redis policy.

Send Managed Redis the TLS Name It Expects

Redis-backed limiting is only useful when every gateway instance can reach the same intended backend. In 3.10.8, TLS connections used by Limit Count, Limit Count Advanced, GraphQL Limit Count, Limit Conn, Limit Req, AI Rate Limiting, and AI Cache send a server name through SNI.

The selection rule is explicit:

if redis_server_name is set, the gateway sends that value;
otherwise, a hostname-valued redis_host is sent; and
if redis_host is an IP address and no explicit name is set, no server name is sent.

Earlier releases sent no server name. Managed Redis services that choose a TLS endpoint or certificate by hostname could therefore be unreachable even when redis_ssl was enabled.

SNI communicates the intended server name during the TLS handshake; it is not, by itself, proof of certificate verification or authorization. Test the complete Redis TLS configuration used by the plugin, including name resolution, trust material, credentials, and the behavior when the endpoint is unavailable.

What Changes in the Failure Path

The most useful way to validate a limiter is to test more than the happy path. API7 Gateway 3.10.8 changes several failure observations without turning them into one universal behavior:

Counter update failure in Limit Count, Limit Count Advanced, GraphQL Limit Count, and AI Rate Limiting: $rate_limiting_info uses decision: error, separating backend/accounting failure from a policy rejection.
Rejected-only traffic with delayed sync in Limit Count, Limit Count Advanced, and GraphQL Limit Count: the instance refreshes the relevant shared state instead of extending stale rejection behavior.
Sliding windows in those three plugins: stale previous-window weighting no longer persists for the rest of the window on the affected path.
Redis unreachable during delayed sync in those three plugins: an instance that admitted nothing no longer repeatedly charges the local fallback counter during synchronization.
Nested AI usage on an old Data Plane: the joined field still evaluates to 0; mixed versions remain an under-accounting risk until the rollout is complete.

None of these statements means every Redis outage must fail open or fail closed. That outcome depends on the plugin and configuration path in use. Test the exact deployed policy and record both the client response and the structured decision evidence.

What to Validate Before Upgrading to 3.10.8

Use the API7 Gateway upgrade guide and rolling-upgrade procedure: first deploy one target Data Plane as a canary outside the production load balancer, validate it, and then begin the production rollout.

Inventory configurations by change: Redis SNI covers Limit Count, Limit Count Advanced, GraphQL Limit Count, Limit Conn, Limit Req, AI Rate Limiting, and AI Cache; $rate_limiting_info covers Limit Count, Limit Count Advanced, GraphQL Limit Count, and AI Rate Limiting; and the delayed-synchronization fix covers Limit Count, Limit Count Advanced, and GraphQL Limit Count. Record the applicable policy, window type, sync_interval, Redis endpoint, TLS options, and log consumers.
For the four $rate_limiting_info plugins, update log pipelines to parse JSON by field name before the Data Plane rollout. Preserve unknown fields rather than rejecting the record.
For those four plugins, capture allowed, rejected, and Redis-unreachable cases under the applicable direct and delayed synchronization modes. Compare client status, gateway log, decision, increment, window boundaries, and counter values.
Using Limit Count, Limit Count Advanced, or GraphQL Limit Count, send traffic so one instance predominantly receives rejected requests. Verify that cached quota refreshes and, for sliding windows, that previous-window weighting changes as the window advances.
If Redis TLS uses a managed hostname, test the explicit redis_server_name and the hostname fallback separately. Do not assume an IP address supplies SNI.
Keep nested AI cost_expr fields out of shared configuration until every relevant Data Plane runs 3.10.8. Then verify provider payload shape and the cost committed after the response.
Compare the first successful AI response with the next request so the team understands the log-phase accounting delay and does not read current-response headers as final usage.
Define alerts for decision: error separately from policy rejections, and attach Redis health and gateway error logs to the same investigation view.

Do not modify gateway configuration during the upgrade window. Back up the database and declarative configuration, validate the path in pre-production, upgrade the Control Plane first, and roll Data Plane nodes according to the documented procedure.

Make Every Limit Auditable

API7 Gateway 3.10.8 does not eliminate the trade-offs behind distributed rate limiting. Delayed synchronization still exchanges some short-term exactness for fewer Redis round trips. AI usage that appears in a response still arrives too late to govern that same response before delivery. SNI tells Redis which server name the client intends, but it does not describe the entire TLS trust decision.

What the release changes is the quality of the accounting contract. Nested usage can be named accurately. For Limit Count, Limit Count Advanced, GraphQL Limit Count, and AI Rate Limiting, $rate_limiting_info carries the window and counter context operators need and records counter-update failures as decision: error. For Limit Count, Limit Count Advanced, and GraphQL Limit Count, a rejected-only instance no longer extends stale state in the affected delayed-sync path.

Read the complete API7 Gateway 3.10.8 release notes, then validate each limiter as a sequence of inputs, state transitions, decisions, and evidence. A limit is production-ready only when the team can explain not just that it fired, but why.