Databricks observability gives you complete visibility into how your data pipelines and systems are performing across your entire data stack. Modern Databricks data teams need data observability tools because optimizing data reliability, pipeline performance, and spending manually is nearly impossible with today’s complex, distributed environments. A solid Databricks data observability platform helps teams catch problems before they hurt business operations, optimize how resources get used, and make sure reliable data reaches decision-makers when they need it.

Unravel’s data observability platform works perfectly for data-driven enterprises looking to optimize data performance, speed up data-driven insights, and optimize cloud spending. Our data observability software is built for organizations that depend on analytics from complex data pipelines handling massive amounts of data across modern, intricate data stacks. What separates us from other Databricks data observability companies is our AI-native approach that goes beyond monitoring to provide actionable automation and optimization.

Azure Databricks offers optimization suggestions and troubleshooting tips for certain scenarios, for example, auto optimization to compact small files. Unravel provides recommendations, efficiency insights, and tuning suggestions on the Applications page and the Jobs tab. With a single Unravel instance, you can monitor all your clusters, across all instances, and workspaces in Azure Databricks to ​​speed up your applications, improve your resource utilization, and identify and resolve application problems.

Databricks collects monitoring and operational data in the form of logs, metrics, and events for your Databricks job flows. Databricks metrics can be used to detect basic conditions such as idle clusters and nodes or clusters that run out of storage. Troubleshooting slow clusters and failed jobs involves a number of steps such as gathering data and digging into log files. Data application performance tuning, root cause analysis, usage forecasting, and data quality checks require additional tools and data sources. Unravel accelerates the troubleshooting process by creating a data model using metadata from your applications, clusters, resources, users, and configuration settings, then applying predictive analytics and machine learning to provide recommendations and automatically tune your Databricks clusters.

Unravel doesn’t orchestrate Databricks Workflows but uses AI to improve Databricks performance, productivity and cost efficiency of your Databricks jobs. Unravel’s AI Agents for Databricks provide insights and recommendations for optimizing Databricks jobs. Simply ask questions in plain language to identify areas for improvement and potential cost savings. You can ask specific questions about the insights, recommendations, or performance metrics of your Databricks jobs that run on job compute clusters.

Unravel’s Databricks optimization platform gets rid of the manual work that slows down data teams. Our data observability software automates Databricks performance optimization, handles routine debugging tasks, and provides intelligent code reviews. This means data engineers spend less time on repetitive troubleshooting and more time building valuable data products. Teams report dramatically reduced time spent firefighting issues and faster resolution of data pipeline problems, showing how effective data observability tools can transform team efficiency. 

Yes. Unravel’s CI/CD integration for Databricks is language-agnostic. It seamlessly integrates with popular programming languages such as SQL, Python, Scala, and Java.

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Yes. Unravel’s CI/CD integration for Databricks supports both Azure DevOps and GitHub. You have the flexibility to choose the platform that best suits your team’s needs.

Learn more about Unravel’s CI/CD Integration for Databricks.

Yes. With Unravel’s CI/CD integration for Databricks, you gain access to comprehensive metrics and AI-powered insights about your pipelines’ performance. You can identify and quickly resolve bottlenecks, improve resource efficiency, optimize code, and make data-driven decisions.

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Yes. Unravel allows you to tailor the PR review process according to your specific requirements. You can define custom rules, set thresholds for performance metrics, and establish guidelines to ensure code quality.

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Yes. Unravel’s CI/CD integration for Databricks seamlessly integrates with popular automated testing frameworks. You can incorporate unit tests, integration tests, and regression tests into your pipeline to ensure the reliability of your code.

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Unravel’s FinOps Agent automatically optimizes Databricks costs through intelligent cluster rightsizing, idle resource detection, code optimization and workload optimization. Rather than just identifying cost issues, Unravel implements fixes automatically based on your governance preferences. You control the automation level, from manual approval to full automation for proven optimizations. Customers typically see 25-35% sustained cost improvements while maintaining performance, with granular cost visibility and budget tracking built natively on Databricks System Tables.

Learn more about Unravel for Databricks Cost Optimization.

Unravel Databricks Agents are AI-powered components that extend traditional Databricks data observability tools by taking automated actions for your team. The FinOps Agent handles Databricks cost optimization and governance within the data observability platform, delivering up to 50% more workloads for the same budget. The DataOps Agent cuts firefighting time by 99% through automated troubleshooting built into our Databricks data observability software. The Data Engineering Agent automates Databricks performance optimization, code reviews, and debugging, making our data observability platform a real AI teammate for your data engineering teams. 

Learn more about our Agents for Databricks Observability.

Unravel’s AI-enabled Databricks data observability platform offers hundreds of powerful capabilities that help data teams troubleshoot issues, optimize performance, migrate workloads, and control costs. Our Databricks optimization tools provide comprehensive monitoring, automated root cause analysis, intelligent cost optimization, and proactive issue prevention. Ready to see what our Databricks optimization solutions can do?

Here’s how you can get started:

• Get a Free Databricks Health Check Report
• Explore our Self-Guided Interactive Tours
• Book a Personalized 30-Minute Live Demo