Databricks Spark integration
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To achieve continuous Spark observability and monitoring, IBM® Databand® features seamless Databricks integration through Spark workloads.

IBM Databand provides Spark observability in the context of your broader pipelines so you can detect data incidents earlier and resolve them faster. 

Databand collects Spark-specific metadata such as job metrics as well as Spark execution logs across Python and Scala/Java Spark applications. This includes advanced tracking capabilities for Spark deployments on watsonx.data, EMR, Databricks and Dataproc.

Use cases Alert earlier

Receive real-time alerts on Spark executions and data quality incidents.

Remove surprises

See historical trends of different Spark processes to detect anomalies and incidents.

360-degree impact analysis

Use Databand’s runtime incident lineage to view how Spark executions impact downstream data.

Take the next step

Implement proactive data observability with IBM Databand today so you can know when there’s a data health issue before your users do.

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