Unlock Data Observability with Astro
In our data-driven economy, ensuring data reliability and visibility is critical. Data observability gives businesses insight into the health of their data pipelines. Astronomer unifies orchestration alongside observability, enhances data quality, and makes your operations more transparent, reliable, and efficient.
Astro Observe: Now in Private Preview
Astro Observe delivers pipeline-level data observability, providing a comprehensive view of your Airflow environment; with tracking across the health and performance of data products to ensure they meet business goals. The SLA dashboard lets teams set data freshness and delivery thresholds, and provides real-time alerts when issues arise. With full lineage tracking, teams can quickly pinpoint activity and ownership across even the most complex workflows, ensuring swift remediation when needed.
What is Data Observability?
The definition of data observability is the ability to understand and monitor the health, performance, and reliability of your data pipelines. It involves tracking data lineage, detecting anomalies, monitoring data quality, and providing insights into data operations. Effective data observability ensures that your data remains accurate, timely, and accessible, supporting better decision-making and operational efficiency.
What are Data Products?
Data products are reusable assets that package together everything needed to make data consumable – whether as an internal dashboard or a customer-facing metric. Data products rely on on-time delivery of fresh data to be consumed, as they are often tied to business objectives including the use of data for decision making, as a component of a product, or for compliance purposes.
Learn more about Astronomer’s approach to data products in the blog Data Products: It’s not what you call them that matters. It’s what you do with them.
Why does Data Observability matter?
In today's data-driven world, the success of your business hinges on the reliability and transparency of your data pipelines. Data observability matters because it enables teams to proactively manage and ensure the reliability, freshness, and timely delivery of data products. Delayed or corrupted data can lead to misguided decision making, lost revenue, compliance issues and may reflect negatively on an organization's reputation.
Comprehensive Data Observability with Astro Observe
Platform-Agnostic
Astro Observe is built to sit on top of any team’s Airflow projects, regardless of if they are on Astro, OSS Airflow, Amazon Managed Workflows for Apache Airflow (MWAA), or Google Cloud Composer (GCC).
Unified Management, Observability, and Governance
Astro’s unified platform offers centralized management of all orchestration tasks, reducing complexity and streamlining operations. With features like federated observability views and integrated data lineage tracking, Astro ensures smooth data flow and interoperability across your data ecosystem.
Business-level Accountability
Assign ownership of data products to provide a clear picture of accountability and ownership.
Owners of data products can set policies around data freshness and delivery (timeliness) to better align with business outcomes, and have the necessary visibility into when there is risk so that they can take action when necessary.
Holistic View of Data Supply Chain
Astro provides detailed data lineage tracking, allowing you to trace the flow of data through your pipelines. This transparency helps identify the sources of data issues and ensures that data transformations and up-and-downstream dependencies are fully understood.
By integrating Astro with OpenLineage, metadata is collected from pipeline components such as datasets, schedulers, tasks, and source systems, with visualizations that enable you to piece together your organization’s entire data supply chain.
Real-Time Monitoring and Proactive Alerting
Astro offers real-time monitoring and alerting capabilities to track the performance of your data pipelines. This enables proactive detection and resolution of issues, ensuring that data remains accurate and available.
Astro’s proactive monitoring and alerting serve as the foundation for full-stack observability.
Granular Evaluation Criteria
Astro provides comprehensive metrics on data quality, including completeness, accuracy, consistency, and timeliness. These metrics help you maintain high standards of data quality across your organization.
Astro’s robust data quality features help maintain high standards of data integrity.
Scalable and Flexible
Astro’s scalable architecture supports the growing needs of your data operations.As deployments become more complex and activity within Airflow expands, Astro ensures that your data observability scales efficiently.
Astro’s ability to elastically scale and optimize resources and processes ensures efficient management of data operations.
Secure and Compliant
Astronomer ensures that all data workflows are secure and compliant with industry standards. Role-based access controls, encryption, and audit trails to protect your sensitive data and ensure compliance with regulatory requirements.
Let's compare. | Astronomer | Traditional Data Quality Vendors |
|---|---|---|
Custom Alerts and MonitoringConfigure and set alerts to immediately inform your team when issues occur and take action. |  | |
Metrics for Health and PerformanceComprehensive metrics on data quality including completeness, accuracy, consistency, and timeliness. | | |
Anomaly DetectionAutomatic identification of unexpected changes or patterns in your data to ensure unexpected issues are caught early. | | |
Single, Unified SolutionA view of health and the status of workflows alongside the tools necessary to manage and orchestrate pipelines. | |  |
Pipeline-level VisibilityA view of the health and status of data at every point along the supply chain; not limited to data lakes and warehouses. | | |
Automatic Bottleneck DetectionProactive detection of deviations from regular activity based upon historical context of pipeline and dependency performance. | | |
Actionable RemediationJump quickly from alerts and dependency visualizations into Airflow to resolve issues and maintain operations. | | |
Informed OptimizationsA recommendation engine built upon years of Airflow best practices and expertise, with proactive guidance to eliminate risk and unlock efficiencies. | | |
Vendor AgnosticAstro Observe is built to work across both OSS and managed Airflow; with support for Astro, MWAA, and GCC. | | |
Start Enhancing Your Data Observability with Astro Today
Astronomer is your trusted partner in optimizing data workflows and enhancing data observability. Gain complete visibility into your data pipelines, ensure high data quality, and maintain reliable data operations with Astro’s advanced capabilities. Try Astro for free and start your journey to comprehensive data observability today.
Additional Resources
Webinar Introduction to Observability for Data Pipelines 
Documentation Observability Content Hub Blog Astro Observe is Now In Public Preview Documentation Leveraging data products for health and performance benefits Documentation Implementing proactive alerting Blog What Observability Brings to Data Orchestration Explore More Use Cases
FAQs
What is data observability?
The definition of data observability is the ability to understand and monitor the health, performance, and reliability of your data pipelines. It involves tracking data lineage, detecting anomalies, monitoring data quality, and providing insights into data operations. Data teams with effective data observability practices are able to ensure that their data remains accurate, timely, and accessible, supporting better decision-making and operational efficiency.
How does data observability impact data quality?
Data observability directly impacts data quality by providing proactive insights into data freshness, delivery timelines, and potential bottlenecks, allowing teams to detect and address issues before they impact the end data product. With effective observability tools teams can ensure that that data remains reliable, accurate, and trustworthy for both internal decision-making and customer-facing applications.
How is data observability different from data monitoring?
While data monitoring allows teams to understand the status of data and workflow dependencies at any given time, the practice of data observability extends beyond a static view to provide context across the entire data supply chain; and can be applied to detect issues, understand root causes, optimize workflows, and mitigate risk. While monitoring is typically reactive, a data observability framework seeks to provide the insights that can be leveraged to detect issues or anomalies before they result in failure.
Why do organizations need data observability?
Organizations need data observability to ensure the health of their data pipelines, which are essential for the delivery of reliable data products. Observability allows teams to monitor the health of data workflows, detect issues, and ultimately reduce the risk.
How is data observability different from infrastructure and application-level observability?
Data observability focuses on gaining insights into the health and performance of data as it moves across the entire data supply chain to support business critical data products. Infrastructure and application-level observability centers around app performance, code behavior, and infrastructure health, without the specific focus on data freshness, and the timely delivery of data products that directly impact business outcomes.
How does Astronomer support data observability?
Astronomer has observability capabilities that span the Airflow managed-service, Astro, which includes alerting and a dashboard for understanding the health and status of workflows. In addition, Astro Observe, which is now in private preview provides a comprehensive view of the data supply chain by offering an SLA dashboard for tracking data freshness and delivery, predictive alerting to identify risks and optimization areas, dependency graphs that visualize up-and-downstream dependencies and bottlenecks, as well as a recommendation engine to proactively flag improvement areas and mitigate risk.
Teams that are interested in the private preview of Astro Observe can request access here.
What role does data lineage play in data observability?
Data lineage plays a crucial role in data observability by providing a complete view of upstream and downstream dependencies across data products, helping teams to quickly identify ownership, trace origin, and impact of data cross workflows, which is essential for issue remediation, compliance, and ensuring the reliability and trustworthiness of data products.
Astro Observe is built leveraging Open Lineage, which is the industry adopted standard for the collection and analysis of data lineage. Learn more about Open LIneage by visiting the official project site.
