Handle failure in case the Kafka Broker is down

I have a Kafka broker running where messages are consumed successfully but I want to handle the case where Kafka Broker is down on the Kafka Consumer end.

I have read this thread but came to know that the logs are shown at DEBUG level. I was wondering if I can handle this manually on an event trigger may be because I want to handle the failure of Kafka broker myself. Does Spring Kafka provide something to handle this situation?

Please tell me if any more details are needed. I would highly appreciate any suggestions on this that would point me in the right direction. Thanks

EDIT 1:

As answered by @Artem, I've tried this in my KafkaConsumer

@EventListener
public void handleEvent(NonResponsiveConsumerEvent event) {
    LOGGER.info("*****************************************");
    LOGGER.info("Hello NonResponsiveConsumer {}", event);
    LOGGER.info("*****************************************");     
}

This event is triggered ONCE even when Kafka server is running (when I start the application first time). Please see the below logs:

....
....
2017-12-04 13:08:02,177 INFO o.s.c.s.DefaultLifecycleProcessor - Starting beans in phase 0
2017-12-04 13:08:02,218 INFO o.a.k.c.c.ConsumerConfig - ConsumerConfig values: 
    auto.commit.interval.ms = 5000
    auto.offset.reset = latest
    bootstrap.servers = [52.214.67.60:9091]
    check.crcs = true
    client.id = 
    connections.max.idle.ms = 540000
    enable.auto.commit = false
    exclude.internal.topics = true
    fetch.max.bytes = 52428800
    fetch.max.wait.ms = 500
    fetch.min.bytes = 1
    group.id = workerListener
    heartbeat.interval.ms = 3000
    interceptor.classes = null
    internal.leave.group.on.close = true
    isolation.level = read_uncommitted
    key.deserializer = class org.apache.kafka.common.serialization.StringDeserializer
    max.partition.fetch.bytes = 1048576
    max.poll.interval.ms = 300000
    max.poll.records = 500
    metadata.max.age.ms = 300000
    metric.reporters = []
    metrics.num.samples = 2
    metrics.recording.level = INFO
    metrics.sample.window.ms = 30000
    partition.assignment.strategy = [class org.apache.kafka.clients.consumer.RangeAssignor]
    receive.buffer.bytes = 65536
    reconnect.backoff.max.ms = 1000
    reconnect.backoff.ms = 50
    request.timeout.ms = 305000
    retry.backoff.ms = 100
    sasl.jaas.config = null
    sasl.kerberos.kinit.cmd = /usr/bin/kinit
    sasl.kerberos.min.time.before.relogin = 60000
    sasl.kerberos.service.name = null
    sasl.kerberos.ticket.renew.jitter = 0.05
    sasl.kerberos.ticket.renew.window.factor = 0.8
    sasl.mechanism = GSSAPI
    security.protocol = PLAINTEXT
    send.buffer.bytes = 131072
    session.timeout.ms = 10000
    ssl.cipher.suites = null
    ssl.enabled.protocols = [TLSv1.2, TLSv1.1, TLSv1]
    ssl.endpoint.identification.algorithm = null
    ssl.key.password = null
    ssl.keymanager.algorithm = SunX509
    ssl.keystore.location = null
    ssl.keystore.password = null
    ssl.keystore.type = JKS
    ssl.protocol = TLS
    ssl.provider = null
    ssl.secure.random.implementation = null
    ssl.trustmanager.algorithm = PKIX
    ssl.truststore.location = null
    ssl.truststore.password = null
    ssl.truststore.type = JKS
    value.deserializer = class org.springframework.kafka.support.serializer.JsonDeserializer

2017-12-04 13:08:02,346 INFO o.a.k.c.u.AppInfoParser - Kafka version : 0.11.0.0
2017-12-04 13:08:02,346 INFO o.a.k.c.u.AppInfoParser - Kafka commitId : cb8625948210849f
2017-12-04 13:08:02,350 INFO o.s.s.c.ThreadPoolTaskScheduler - Initializing ExecutorService 
2017-12-04 13:08:02,363 INFO o.s.b.a.e.j.EndpointMBeanExporter - Located managed bean 'auditEventsEndpoint': registering with JMX server as MBean [org.springframework.boot:type=Endpoint,name=auditEventsEndpoint]
2017-12-04 13:08:02,397 INFO c.t.m.w.c.k.c.KafkaConsumer - *****************************************
2017-12-04 13:08:02,397 INFO c.t.m.w.c.k.c.KafkaConsumer - Hello NonResponsiveConsumer ListenerContainerIdleEvent [timeSinceLastPoll=1.51237491E9s, listenerId=workerListener-0, container=KafkaMessageListenerContainer [id=workerListener-0, clientIndex=-0, topicPartitions=null], topicPartitions=null]
2017-12-04 13:08:02,403 INFO c.t.m.w.c.k.c.KafkaConsumer - *****************************************
....
....

EDIT 2:

Issue resolved by upgrading spring-kafka to 1.3.2