Ingress to Gateway API Transition: Controller-to-Endpoint Latency Bottleneck

When transitioning from Ingress to the Gateway API, controller-to-endpoint latency typically stems from the multi-layered reconciliation loop. Unlike legacy Ingress, where a single object often maps to a service, the Gateway API uses a hierarchical model (GatewayClass, Gateway, and HTTPRoute) that requires the controller to aggregate state across multiple resources before pushing updates to the data plane (e.g., Envoy xDS).

The Latency Mechanism

The reconcile_duration_seconds metric usually increases during bulk HTTPRoute updates compared to Ingress updates. In the Ingress model, the controller processes a flat list of rules. In Gateway API, the controller must:

• Watch all HTTPRoute resources associated with a specific Gateway.
• Validate cross-references to Services and ReferenceGr.
• Compute the global routing table for the entire Gateway.
• Push the updated configuration to the proxy.

If the controller implementation uses O(n²) logic for calculating the routing table based on route count, bulk updates will cause CPU spikes in the controller pod, delaying the propagation of endpoint-specific changes.

Identifying the Threshold

While there is no universal "limit" as performance varies by controller (e.g., Istio, Cilium, or Envoy-based controllers), endpoint update latency typically begins to exceed baseline when:

• Resource Density: Exceeding 500–1,000 HTTPRoutes per Gateway, depending on the complexity of the match filters and filters used.
• Update Churn: High-frequency pod scaling (autoscaling) that forces the controller to re-calculate the entire Gateway state for every single endpoint-level change.

Steps for Diagnostic Resolution

To quantify and mitigate the bottleneck, follow these steps:

1. Measure Propagation Latency: Compare the delta between api_server_update_timestamp and the time the proxy acknowledges the new configuration.
2. Profile Controller CPU: Monitor if reconcile_duration_seconds spikes during bulk updates. If it scales linearly with route count, the bottleneck is the configuration aggregation logic.
3. Shard Gateways: If latency exceeds thresholds, split high-density HTTPRoutes across multiple Gateway resources to reduce the reconciliation radius for the controller.

Note: This analysis assumes the controller is using standard HTTPRoute filters and that the data plane is an Envoy-based proxy.