Unravel Data is the DataOps observability platform for the modern data stack. Unravel provides AI-powered recommendations for performance, cost governance, and quality so data teams spend less time firefighting and more time innovating.
Let’s see how it works
Unravel auto-discovers and contextualizes metadata.
Unravel automatically and continuously discovers everything you have running. Unravel’s lightweight agentless design uses native APIs and non-intrusive custom micro-sensors to automatically gather metadata from every platform, system, and application across your data stack. Unravel captures deep details for jobs, pipelines, clusters, data, infrastructure, and users that web app observability and point tools do not. For example, Unravel automatically helps you capture details about your cluster types, table and partition access metrics, source code, and dependencies for each stage of your data pipelines.
Unravel provides a single pane of glass for single source of truth.
Unravel correlates these granular details to build a dynamic data model that connects the dots to provide a holistic view of how everything works together.
This view helps your team visualize and understand all of the interrelationships within your data stack, such as degree of parallelism, resource contention, dependencies, and data lineage. Unravel provides one-click drill-downs into configurations, code, containers, resource usage, costs, data tables, and data quality checks.
For example, Unravel automatically helps you visualize your data pipeline using a Dag graph. View the status of your jobs on a Gantt chart, color-coded along a timescale.
Unravel provides actionable intelligence through automated analysis and prescriptive AI recommendations.
Unravel’s AI-powered recommendations don’t just show you what’s going on, but why and exactly how to fix things. You can detect anomalous behavior in real time, pinpoint root causes in milliseconds, and automatically provide prescriptive recommendations on where and how to change configurations, containers, code, resource allocation, and more.
What makes Unravel unique are the AI-powered optimization recommendations that provide continuous analysis of your jobs, pipelines, clusters, infrastructure, datasets, and more.
Unravel enables automated governance through proactive guardrails to enable self-service.
Unravel helps you go from reactive to proactive. Unravel empowers you to preemptively snuff out problems, keep things on track, make iterative improvements, and accelerate at scale. Automated guardrails and governance rules trigger alerts when violated—you can even have Unravel take autonomous corrective actions on your behalf. AI recommendations empower junior engineers and non-experts to make expert-level optimizations confidently on their own.
Unravel enables automated guardrails for a wide variety of parameters such as size, job length, and cost. You can enable proactive smart alerts via Jira, Slack, and PagerDuty for missed SLAs, usage policy violations, and impact on downstream dependencies. All jobs with AI optimization recommendations are indexed in one place for everyone to easily see.
The Unravel platform harnesses full-stack visibility, contextual awareness, AI-powered intelligence, and automation to go “beyond observability”—to not only show you what’s going on, but why and how to make things better and then keep them that way proactively. Unravel is designed for every member of your data team.