With its on-demand, auto-scaling compute, Amazon EMR enables a multitude of big data use cases from batch processing to data science modeling, resulting in immense cost savings and increased performance.
But data platform teams are still stuck at the last mile of data delivery - trying to open up access to data whilst remaining compliant with emerging data privacy legislation such as GDPR and CCPA.
IAM roles were never designed to provide fine-grained access to data, and quickly become painful to work with, ultimately resulting in the platform team becoming a bottleneck for analytics.
In this webinar, we'll discuss:
- The IAM challenge on Amazon EMR
- Why open-source governance solutions such as Apache Ranger do not scale
- How to enforce fine-grained access policies using Okera while running Apache Spark and Presto on EMR.
- Real-life use case examples of how F500 organizations are scaling enforcement for different EMR use cases.
Download it now for an in-depth demo of Okera’s dynamic enforcement of fine-grained access control that scales transparently, removing the need to manage IAM roles on each cluster.
