Unravel Data Introduces AI-powered Data Operations Solution to Monitor, Troubleshoot and Optimize Apache Spark Applications Using Microsoft Azure Databricks

Unravel Data, the only data operations platform providing full-stack visibility and AI-powered recommendations to drive more reliable performance in modern data applications, today announced Unravel for Azure Databricks, a solution to deliver comprehensive monitoring, troubleshooting, and application performance management for Azure Databricks environments. The new offering leverages AI to enable Azure Databricks customers to significantly improve performance of Spark jobs while providing unprecedented visibility into runtime behavior, resource usage, and cloud costs.

“Spark, Azure, and Azure Databricks have become foundational technologies in the big data landscape, with more and more Fortune 1000 organizations using them to build their modern data pipelines,” said Kunal Agarwal, CEO, Unravel Data. “Unravel is uniquely positioned to empower Azure Databricks customers to maximize the performance, reliability and return on investment of their Spark workloads.”

Unravel for Azure Databricks helps operationalize Spark apps on the platform: Azure Databricks customers will shorten the cycle of getting Spark applications into production by relying on the visibility, operational intelligence, and data driven insights and recommendations that only Unravel can provide. Users will enjoy greater productivity by eliminating the time spent on tedious, low value tasks such as log data collection, root cause analysis and application tuning.

“Unravel’s full-stack DataOps platform has already helped Azure customers get the most out of their cloud-based big data deployments. We’re excited to extend that relationship to Azure Databricks,” said Yatharth Gupta, principal group manager, Azure Data at Microsoft. “Unravel adds tremendous value by delivering an AI-powered solution for Azure Databricks customers that are looking to troubleshoot challenging operational issues and optimize cost and performance of their Azure Databricks workloads.”

Key features of Unravel for Azure Databricks include:

1. Application Performance Management for Azure Databricks – Unravel delivers visibility and understanding of Spark applications, clusters, workflows, and the underlying software stack
2. Automated root cause analysis of Spark apps – Unravel can automatically identify, diagnose, and remediate Spark jobs and the full Spark stack, achieving simpler and faster resolution of issues for Spark applications on Azure Databricks clusters
3. Comprehensive reporting, alerting, and dashboards – Azure Databricks users can now enjoy detailed insights, plain-language recommendations, and a host of new dashboards, alerts, and reporting on chargeback accounting, cluster resource usage, Spark runtime behavior and much more

Azure Databricks is a Spark-based analytics platform optimized for Microsoft Azure. Azure Databricks provides one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts.

An early access release of Unravel for Azure Databricks available now.