@Michael Bronson Then what you could do using the config.py copy the kafka.env to the /tmp on the working cluster see below # /var/lib/ambari-server/resources/scripts/configs.py --user=admin --password=admin --port=8080 --action=get --host=localhost --cluster={your_clustername} --config-type=kafka-env --file=/tmp/kafka-env.json Sample output 2019-01-27 22:27:09,474 INFO ### Performing "get" content:
2019-01-27 22:27:09,474 INFO ### to file "/tmp/kafka.env.json"
2019-01-27 22:27:09,600 INFO ### on (Site:kafka.env, Tag:version1) Validate the contents of the .json in the "/tmp/kafka-env.json" Sample output {
"properties": {
"kafka_user_nproc_limit": "65536",
"content": "\n#!/bin/bash\n\n# Set KAFKA specific environment variables here.\n\n# The java implementation to use.\nexport JAVA_HOME={{java64_home}}\nexport PATH=$PATH:$JAVA_HOME/bin\nexport PID_DIR={{kafka_pid_dir}}\nexport LOG_DIR={{kafka_log_dir}}\n{% if kerberos_security_enabled or kafka_other_sasl_enabled %}\nexport KAFKA_KERBEROS_PARAMS=\"-Djavax.security.auth.useSubjectCredsOnly=false {{kafka_kerberos_params}}\"\n{% else %}\nexport KAFKA_KERBEROS_PARAMS={{kafka_kerberos_params}}\n{% endif %}\n# Add kafka sink to classpath and related depenencies\nif [ -e \"/usr/lib/ambari-metrics-kafka-sink/ambari-metrics-kafka-sink.jar\" ]; then\n export CLASSPATH=$CLASSPATH:/usr/lib/ambari-metrics-kafka-sink/ambari-metrics-kafka-sink.jar\n export CLASSPATH=$CLASSPATH:/usr/lib/ambari-metrics-kafka-sink/lib/*\nfi\nif [ -f /etc/kafka/conf/kafka-ranger-env.sh ]; then\n. /etc/kafka/conf/kafka-ranger-env.sh\nfi",
"kafka_log_dir": "/var/log/kafka",
"kafka_pid_dir": "/var/run/kafka",
"kafka_user_nofile_limit": "128000",
"is_supported_kafka_ranger": "true",
"kafka_user": "kafka"
} Copy the file using scp or whatever it over to your cluster and run the below command --action=set to update your problematic cluster. Before you start the kafka check the properties in the kafka.env.json to match you ie memory to match you cluster config. # /var/lib/ambari-server/resources/scripts/configs.py --user=admin --password=admin --port=8080 --action=set --host=localhost --cluster={your_clustername} --config-type=kafka-env --file=/tmp/kafka-env.json Sample output 2019-01-27 22:29:38,568 INFO ### Performing "set":
2019-01-27 22:29:38,568 INFO ### from file /tmp/kafka.env.json
2019-01-27 22:29:38,569 INFO ### PUTting file: "/tmp/kafka.env.json"
2019-01-27 22:29:38,569 INFO ### PUTting json into: doSet_version1.json
2019-01-27 22:29:38,719 INFO ### NEW Site:kafka.env, Tag:version2 Start you Kafka from Ambari this should work. Please let me know
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