Camunda AI Decision Gateway Discovery Dashboard

This application connects to a Camunda ElasticSearch (ES) cluster and converts usertask completion data into a machine learnable format

Note

Please note that this project is a prototype and not an officially maintained Camunda product.

Configuring the Elasticsearch Connection

• Make a copy of the .env file and name it .env.local
• Ensure that the ES_ENDPOINT points to your ES cluster
• Uncomment the lines that make sense for your environment to configure the connection and authentication:
• For TLS configuration via CA_CERT and CA Fingerprint, see https://www.elastic.co/guide/en/elasticsearch/client/javascript-api/current/client-connecting.html#connect-self-managed-new
• The ES_CA_CERT_PATH is relative to the root directory (so if the cert file is in the same directory as the .env.local file, it should be ./http_ca.crt)
• For the Authentication strategies, see https://www.elastic.co/guide/en/elasticsearch/client/javascript-api/current/client-connecting.html#auth-strategies

If you have trouble connecting to Elasticsearch, check out src/app/utils.js. This is where the ES connection is configured. Feel free to make adjustments and send a Pull Request if you encounter any issues with a specific setup.

Getting Started

1. Install Dependencies npm i
2. Run Server: npm run dev
3. Open http://localhost:3000 with your browser

License

Apache License, Version 2.0