Unravel Data makes Azure Databricks perform better during and after your Azure migration and more reliably. Unravel complements the Spark web UI and automatically troubleshoots and tunes your Spark jobs. Avoid errors, slowdowns, and inefficient resource usage.
Unravel for Databricks on Microsoft Azure is complete monitoring, tuning, and optimization platform for modern data stacks running on Azure Databricks. Unravel provides granular reporting, chargeback, and cost optimization for your Azure Databricks workloads, and helps manage Azure migration from on-premises Hadoop and Spark to Azure Databricks in the cloud.
AI-powered performance management and reporting for Azure Databricks
Unravel makes it radically simple to monitor, troubleshoot, and optimize Spark performance and reliability.
Unravel’s built-in AI engine provides insights, reporting recommendations, and auto-tuning for Spark applications and pipelines in the Databricks environment. Unravel enables:
Unravel provides a unified view of Databricks with all adjacent technologies.
Unravel automatically connects your Spark jobs to the pipelines they run under. Unravel also provides a highly correlated and refined view of your Spark jobs with other services, storage, containers, and infrastructure.
Know exactly what you are using, who’s using it, and what it is costing you.
Companies choose Azure Databricks to get Spark apps into production quickly and with excellent performance. Unravel helps you achieve maximum efficiency by providing:
Maximize your Microsoft Azure HDI ROI with Unravel Data