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.

Organizations using Unravel’s Databricks data optimization platform typically see significant cost reductions. Our customers report cutting wasted cloud data costs by up to 70% within six months while maintaining or optimizing Databricks performance. The FinOps Agent can automatically find Databricks cost optimization opportunities, implement governance policies, and provide detailed chargeback and showback tracking to keep costs under control. These results show why investing in the right Databricks agents delivers measurable ROI.

At the FinOps Crawl phase, the data will be less granular. You may start at the cloud provider and service level. In the Walk phase, you’ll want additional granularity to go into the application level. If FinOps data is only available at the cluster or infrastructure level, you may face challenges with allocation. In the Run phase, you may need to get to the user, project, and job level.

Real-time monitoring and alerting with Databricks Overwatch requires a time-series database. Databricks refreshes your billable usage data about every 24 hours and AWS Cost and Usage Reports are updated once a day in comma-separated value (CSV) format. Since Cost Explorer includes usage and costs of other services, you should tag your Databricks resources and you may consider creating custom tags to get granular reporting on your Databricks cluster resource usage. Unravel simplifies this process with Cost 360 for Databricks to provide full cost observability, budgeting, forecasting, and optimization in near real time. Cost 360 includes granular details about the user, team, data workload, usage type, data job, data application, compute, and resources consumed to execute each data application. In addition, Cost 360 provides insights and recommendations to optimize clusters and jobs as well as estimated cost improvements to prioritize workload optimization.

Many enterprises are facing this exact situation, experiencing performance and cost issues migrating on-premises workloads to Databricks. On-prem workloads are naturally limited in terms of cost due to the physical constraints of their data center, but costs can suddenly grow on the cloud. Enterprises that have successfully migrated to Databricks start by optimizing jobs before moving them to the cloud to ensure they can predict the spend and performance.

Databricks offers general tips and settings for certain scenarios, for example, auto optimize to compact small files. Unravel provides recommendations, efficiency insights, and tuning suggestions. With a single Unravel instance, you can monitor all your clusters, across all instances, and workspaces in Databricks to ​​speed up your applications, improve your resource utilization, and identify and resolve application problems.

Learn more about our AI for Data Observability. 

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?

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