Data Pipeline Design Considerations

So I have a confluent kafka with multiple topics per network divided as follows

NET1: Data

NET1-SYSLG

NET1-WIN

======
NET2 : Data

NET2-SYSLG

NET2-WIN

I have 2 logstash servers reading from those topics on Kafka

1 reading the topics from NET1 going to Elastic
the second is reading only the topic data from NET2 also going to the same Elastic
If i have created 2 spaces to isolate the data once I called it NET1 and the second one is NET2

NET1:SYSLG, WIN ---> Logstash 1 -------------------- NET1 SPACE
KFK- -------------------------------- ------- | --------> ELASTIC |
NET2: SYSLG, WIN --- > Logstash2 --------------------- NET2 SPACE

what is best approach or procedures to write data for logstash 1 to SPACE 1 index called net1-syslog
How do I go about configuring that on Elasticsearch to map those incoming events from each logstash to their corresponding space and indices ? Any insight or help would be appreciated

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