(Optional step.) 1. The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the metadata/producer/consumer requests, as well as the socket timeouts. (These are all settings creates a Kafka consumer (reader) for that partition. If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval be only one active leader connecting to the ordering service. Following configuration controls frequency of the leader heartbeat messages: peer: # Gossip related configuration gossip: election:

(Optional step.) (a) The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the meta- data/producer/consumer requests, as well as the socket timeouts. (These are all settings creates a Kafka consumer (reader) for that partition. If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval be only one active leader connecting to the ordering service. Following configuration controls frequency of the leader heartbeat messages: peer: # Gossip related configuration gossip: election: leaderAliveThreshold:

(Optional step.) (a) The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the meta- data/producer/consumer requests, as well as the socket timeouts. (These are all settings creates a Kafka consumer (reader) for that partition. If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval be only one active leader connecting to the ordering service. Following configuration controls frequency of the leader heartbeat messages: peer: # Gossip related configuration gossip: election: leaderAliveThreshold:

cluster for the corresponding channel, as well as protocol specific parameters such as heartbeat frequency, leader timeouts, and more. Recall, each channel has its own instance of a Raft protocol running timeouts. (Optional step.) The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the metadata/producer/consumer requests, as well as the socket timeouts. (These are all settings creates a Kafka consumer (reader) for that partition. If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval

cluster for the corresponding channel, as well as protocol specific parameters such as heartbeat frequency, leader timeouts, and more. Recall, each channel has its own instance of a Raft protocol running Documentation, Release master • The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the meta- data/producer/consumer requests, as well as the socket timeouts. (These are all settings a Kafka consumer (reader) for that partition. – If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval

cluster for the corresponding channel, as well as protocol specific parameters such as heartbeat frequency, leader timeouts, and more. Recall, each channel has its own instance of a Raft protocol running timeouts. (Optional step.) The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the metadata/producer/consumer requests, as well as the socket timeouts. (These are all settings creates a Kafka consumer (reader) for that partition. If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval

cluster for the corresponding channel, as well as protocol specific parameters such as heartbeat frequency, leader timeouts, and more. Recall, each channel has its own instance of a Raft protocol running (Optional step.) • The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the meta- data/producer/consumer requests, as well as the socket timeouts. (These are all settings a Kafka consumer (reader) for that partition. – If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval

cluster for the corresponding channel, as well as protocol specific parameters such as heartbeat frequency, leader timeouts, and more. Recall, each channel has its own instance of a Raft protocol running Documentation, Release master • The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the meta- data/producer/consumer requests, as well as the socket timeouts. (These are all settings a Kafka consumer (reader) for that partition. – If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval

cluster for the corresponding channel, as well as protocol specific parameters such as heartbeat frequency, leader timeouts, and more. Recall, each channel has its own instance of a Raft protocol running timeouts. (Optional step.) The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the metadata/producer/consumer requests, as well as the socket timeouts. (These are all settings creates a Kafka consumer (reader) for that partition. If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval

cluster for the corresponding channel, as well as protocol specific parameters such as heartbeat frequency, leader timeouts, and more. Recall, each channel has its own instance of a Raft protocol running timeouts. (Optional step.) The Kafka.Retry section in the orderer.yaml file allows you to adjust the frequency of the metadata/producer/consumer requests, as well as the socket timeouts. (These are all settings creates a Kafka consumer (reader) for that partition. If any of these steps fail, you can adjust the frequency with which they are repeated. Specifically they will be re-attempted every Kafka.Retry.ShortInterval