Transform custom Docker logs into fluentd into elastic search

Question

I will publish some Docker containers incorporating a common logging framework (written in golang). The logging format is a JSON format.

There is distinct data in this custom json logging format that I would like to be index/searchable from with Kibana. My understanding is that I need to transform/filter this data, but I'm struggling to understand how this is done even after RTFM. I have to extract JSON from JSON?

Some example output from minimal sample application as seen in Docker logs:

{"app_name":"SampleApp","app_port":6666,"app_version":"0.0.2","file":"/build/examples/sample/app/runmain/main.go:131","func":"example.com/code/microservices/examples/sample/app/runmain.mainErr.func1","fw_version":"v0.0.1","level":"info","msg":"listening","time":"2024-01-18T20:31:39.163970213+07:00"}

The data makes its way into fluentd and is logged as:

2024-01-18 20:31:39.000000000 +0000 f905b090d278: {"container_id":"f905b090d278ec2cc2f1f912acdbf8787a0a1c91d8ab7b00ad84e9da20c8c147","container_name":"/fervent_jemison","source":"stdout","log":"{\"app_name\":\"SampleApp\",\"app_port\":6666,\"app_version\":\"0.0.2\",\"file\":\"/build/examples/sample/app/runmain/main.go:131\",\"func\":\"example.com/code/microservices/examples/sample/app/runmain.mainErr.func1\",\"fw_version\":\"v0.0.1\",\"level\":\"info\",\"msg\":\"listening\",\"time\":\"2024-01-18T20:31:39.163970213+07:00\"}\r"}

<source>
  @type forward
  port 24224
  bind 0.0.0.0
</source>

<filter docker.**>
  @type parser
  key_name log
  reserve_data true
  <parse>
    @type json
  </parse>
</filter>

<match *.**>
  @type copy

  <store>
    @type elasticsearch
    host es
    port 9200
    user elastic
    password elastic
    logstash_format true
    logstash_prefix fluentd
    logstash_dateformat %Y%m%d
    include_tag_key true
    type_name access_log
    tag_key @log_name
    <buffer> 
      flush_interval 1s
    </buffer>
  </store>

  <store>
    @type stdout
  </store>
</match>

Initially, I'll deploy this all locally on a single host.

Any tips or further direction would be greatly appreciated. This is a new world to me.