Readme suggest

[nathanrstacey]

I went through the instructions created the dashboard. These are the changes I would make to the readme file

mil-std-1553 to Elasticsearch

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mil-std-1553 is a industrial control bus used by air and space craft.
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IRIG 106 is a comprehensive telemetry standard to ensure interoperability in aeronautical telemetry application at RCC member ranges. It defines how to store 1553 data in Chapter 10 format.
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IRIG 106 is developed and maintained by the Telemetry Group of the Range Commanders Council.
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Prerequisites

• Laptop/Server with the following
  • Docker
  • Filebeat
• Elasticsearch (can be on a remote system)
• Kibana (can be on a remote system)
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Build and run.

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1. Clone this repo.
2. Edit es_curl_setup.sh with:

• your Elasticsearch server details on both lines with a elastic URL
• add the -u parameter if a username is required
  Example of the #2 instructions:
  curl -k -XPUT "https://elastic.mydomain.com:9200/_template/1553" -u "kent" -H...
  curl -k -XPUT "https://elastic.mydomain.com:9200/_template/1553" -u "kent" -H
  ​
  ​

3. Run es_curl_setup.sh on the laptop/server
   ./es_curl_setup.sh
   Note: this .sh is setup for linux. Mac requires the top line to be removed, that line being "#!/usr/local/bin/bash"
4. Edit the filebeat.yml from this repo with your Elasticsearch server details. No need to run Filebeat yet

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5. In your newly cloned ./mil-std-1553-es, clone https://github.com/bbaggerman/irig106lib and https://github.com/bbaggerman/irig106utils. -Thank you bbaggerman!
6. Create a data_sets directory. Your directory structure should now look like the following.
Note: You might need to change the irig106utils and irig106lib foldernames to the below

./mil-std-1553-es
├── Dockerfile
├── Readme.md
├── data_sets
├── docker_build_run.sh
├── es_curl_setup.sh
├── filebeat.yml
├── irig106lib
│   ├── gcc
│   ├── msvs6
│   ├── python
│   ├── readme.txt
│   ├── src
│   ├── vs2005
│   ├── vs2008
│   ├── vs2010
│   ├── vs2012
│   ├── vs2015
│   └── vs2017
└── irig106utils
    ├── gcc
    ├── i106utils.txt
    ├── msvs6
    ├── src
    ├── vs2005
    ├── vs2008
    ├── vs2010
    ├── vs2012
    └── vs2017

7. Add your ch10 file to your ./data_sets directory. Samples can be downloaded from here.
   ​
   cp ~/TC-1553_107_132248.ch10 ./data_sets/
   ​
8. In docker_build_run.sh change the filebeat parameter to the folder locatin of your filebeat.
   Example:
   Old: ..."Ch" | filebeat -c ./filebeat.yml...
   New: ..."Ch" | filebeat-7.6.2-darwin-x86_64/filebeat -c ./filebeat.yml...
9. Load the data into Elasticsearch.
   ​
   ./docker_build_run.sh /data_sets/TTC-1553_107_132248.ch10
   Note: this .sh is setup for linux. Mac requires the top line to be removed, that line being "#!/usr/local/bin/bash"
   ​
10. Import dashboard in ./kibana/export.ndjson via Kibana's Management->Saved Objects->Import.
    ​
    Note: idmp1553 ouput does not contain Year/Month/Day. The Elasticsearch ingest pipeline sets it to Jan 1st, so set your time filter in Kibana to start at Jan 1 of this year. Hour/Day/Seconds.milliseconds are preserved.
    ​

Dashboard:

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