MONITORING AND ALERTING PLATFORM FOR EXTRACT, TRANSFORM, AND LOAD JOBS
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United States of America
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Issued Date -
Dec 26, 2024
app pub date -
Sep 10, 2024
filing date -
Sep 10, 2024
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Abstract
In some implementations, a system may monitor extract, transform, and load (ETL) jobs by generating metrics, including status, timing, and data volume information for constituent tasks of ETL jobs. The system may identify anomalies based on deviations from historical trends in the metrics and may invoke a messaging service to generate notifications related to the anomalies via a workspace accessible to client devices. The system may also automatically remediate anomalies by requeuing, canceling, or dividing ETL jobs or constituent tasks, ensuring efficient ETL job processing and management by handling data volume, execution time, and task statuses dynamically. These capabilities enhance the reliability, performance, and scalability of ETL operations, providing a robust framework for managing large volumes of data and mitigating potential failures in the data processing pipeline.
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