assertEquals("Event should be available.", EVENT, handler.context.getEvent());
    assertEquals("Subscriber should be available.", subscriber, handler.context.getSubscriber());
    assertEquals(
        "Method should be available.",
        subscriber.getClass().getMethod("throwExceptionOn", String.class),
        handler.context.getSubscriberMethod());
  }

    assertEquals("Event should be available.", EVENT, handler.context.getEvent());
    assertEquals("Subscriber should be available.", subscriber, handler.context.getSubscriber());
    assertEquals(
        "Method should be available.",
        subscriber.getClass().getMethod("throwExceptionOn", String.class),
        handler.context.getSubscriberMethod());
  }

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		return s.iptablesConfigurator.CreateInpodRules(&HostProbeSNATIP)
	}); err != nil {
		log.Errorf("failed to update POD inpod: %s/%s %v", pod.Namespace, pod.Name, err)
		return err
	}

	log.Debug("notifying subscribed node proxies")
	if err := s.sendPodToZtunnelAndWaitForAck(ctx, pod, openNetns); err != nil {
		// we must return PartialAdd error here. the pod was injected with iptables rules,

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At a high level, each client job will find the correct generator for the request, generate the required configuration, and send it.

#### Optimizations

A naive implementation would simply regenerate all resources, of all subscribed types, for each client, on any configuration change. However, this scales poorly. As a result, we have many levels of optimizations to avoid doing this work.