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• base_socket_url

  • Description: The URL used by the Secure Agent to establish a connection with the EazyDi platform.

  • Purpose: This is a crucial setting that should not be altered. It specifies the endpoint for all communication between the agent and the cloud service.

• username

  • Description: The username associated with your EazyDi account.

  • Purpose: This parameter is used for authenticating the Agent with the EazyDi platform. It ensures that the agent operates under the correct user context.

  • Example: username=myusername@eazydi.com

• token

  • Description: The authentication token provided by EazyDi.

  • Purpose: This token is used in conjunction with the username to authenticate the Secure Agent. It is essential for secure and authorized access to the platform.

  • Example: token=320af1e1-5786-4779-bf20-1ecadb92c900

• spark_memory

  • Description: The amount of memory allocated to Apache Spark.

  • Purpose: This setting determines how much memory is available for Spark jobs executed by the Agent. Adequate memory allocation is crucial for performance, especially when handling large datasets.

  • Example: spark_memory=6g

• spark_master

  • Description: The Spark master URL.

  • Purpose: This specifies the master node for the Spark cluster. In a standalone or local mode, it indicates that Spark jobs should run on the local machine.

  • Example: spark_master=local

• spark_cores

  • Description: The number of CPU cores allocated to Spark.

  • Purpose: This parameter sets the number of CPU cores available for Spark processing tasks. More cores can improve performance by allowing more parallel processing.

  • Example: spark_cores=2

For Windows

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• Unzip the downloaded file and open app.ini

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• Once Job is complete it will reflect in Eazydi’s Monitor → Archived Listings

For Linux

• Run the command to extract tar.gz file

mkdir linux_eazydi_agent
tar -xzvf eazydi-agent-linux-v0.1.tar.gz -C linux_eazydi_agent
cd linux_eazydi_agent
chmod +x eazydi_agent

• Update the app.ini using your preferred Linux editor

[app]
base_socket_url=<the url for the connection of the agent to eazydi,do not change>
username=myusername@eazydi.com
token=320af1e1-5786-4779-bf20-1ecadb92c900
spark_memory=6g
spark_master=local
spark_cores=2

• Fill up username and token

• Run

./eazydi_agent

• Notice in Environments Tab your machine will be registered and shows status as up

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• Notice the agent receiving a message after registering the machine

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Using the Eazydi Agent

• Create Connections which support the Eazydi Agent and assign the environment to your Agent

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• In Creating Pipelines using the Eazydi Agent, the Source and Target connections should be the same environment

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• Running Jobs make sure that the Agent is up and running. Notice the agent will receive requests for jobs in the logs

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• Once Job is complete it will reflect in Eazydi’s Monitor → Archived Listings

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