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Next Generation of Hadoop
Security, Governance and Operations

nube Libro blanco: Mejor seguridad y gobernanza de los datos con Apache Hadoop

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Integración de Apache Atlas y Apache Ranger para capacitar las políticas de seguridad basadas en la clasificación

As organizations pursue Hadoop initiatives to capture new opportunities for data-driven insights, data governance and data security requirements can pose a key challenge. Hortonworks created an Apache Hadoop Data Governance Initiative to address the need for open source governance solution to manage data classification, data lineage, security and data lifecycle management.


La gestión eficaz de los datos y el control no pueden ser pasivos o forenses. El control de acceso centralizado impulsado por la clasificación de datos consistente es la base para la seguridad dinámica y es un requisito básico para Open Enterprise Hadoop. Para lograr este objetivo, Hortonwroks está anunciando la liberación de nuevas funciones de vista previa pública con Apache Atlas y Apache Ranger, reuniendo la clasificación de datos con aplicación de la política de seguridad.


Apache Atlas, created as part of the Hadoop data governance initiative, empowers organizations to apply consistent data classification across the data ecosystem. Apache Ranger provides centralized security administration for Hadoop. By integrating Atlas with Ranger, Hortonworks empowers enterprises to institute dynamic access policies at run time that proactively prevents violations from occurring.


The Atlas/ Ranger integration represents a paradigm shift for big data governance and data security in Apache Hadoop. By integrating Atlas with Ranger enterprises can now implement dynamic classification-based security policies, in addition to role-based security. Ranger’s centralized platform empowers data administrators to define security policy based on Atlas metadata tags or attributes and apply this policy in real-time to the entire hierarchy of data assets including databases, tables and columns.


Hortonworks empowers data managers to ensure the transparency, reproducibility, auditability and consistency of the Data Lake and the assets it contains. Apache Atlas now provides the ability to visualize cross-component lineage, delivering a complete view of data movement across a number of analytic engines such as Apache Storm, Kafka, Falcon and Hive. Hadoop operations, stewards, operations, and compliance personnel now have the ability to visualize a data set’s lineage and then drill down into operational, security and provenance-related details. As this tracking is done at the platform level, any application that uses multiple engines will be natively tracked. This allows for extended visibility beyond a single application view.