Job Monitoring Best Practices

Follow these best practices to ensure the smooth functioning of your jobs.

While Visier provides extensive monitoring of its infrastructure and services, it is important for you to regularly monitor and check for errors in data extraction and processing.

Establish a workflow for monitoring and validating job statuses

Without a job monitoring process, you risk undetected errors in data extraction and processing, which can lead to inaccurate reports and decision-making. This oversight can cause operational inefficiencies and compromise data integrity. As a data administrator, it is important for you to establish a routine to regularly check and detect errors in data extraction and processing. This workflow should be built during the implementation phase and put in place before going live.

Automate job monitoring via API

While manual job monitoring via the user interface in Studio may be a good choice initially due to limited development resources, it becomes less practical as the volume of data increases. For a better long-term solution, you should automate the job monitoring process using APIs. Automation supports monitoring in both integration and production environments, leading to a more robust system. For more information, see Data and Job Handling API.

Use this example as the foundation of your job monitoring workflow

To automate this workflow:

1. Start the data load for your analytic tenants.
2. Use the jobId response from the data load to retrieve the status of the receiving job or dispatching job.
3. Use the jobId response from the data load to retrieve the status of the processing job.