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Yu-Ting Su on Muck Rack

Yu-Ting Su

As seen in: Amazon Web Services, MDPI, Nutrition & Metabolism, BioRxiv, Cell Press, Dove Medical Press, Lexology, Chemistry World, Aging, Law.Asia
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Articles

Detect and resolve HBase inconsistencies faster with AI on Amazon EMR

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By Yu-Ting Su, Remediation Guidelines
| Amazon Web Services
AWS Big Data Blog HBase operations teams spend hours manually correlating logs, metadata, and consistency reports to identify root causes. Traditional approaches require deep expertise and extensive investigation across scattered data sources, directly impacting MTTR and operational efficiency. As HBase deployments scale and expertise becomes increasingly scarce, organizations face mounting pressure to maintain service reliability while managing growing operational complexity.
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Optimize HBase reads with bucket caching on Amazon EMR

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By Yu-Ting Su, Anirudh Chawla, readRequest Count
| Amazon Web Services
Apache HBase is a database system for big data applications that efficiently manages billions of rows and millions of columns. Its distributed, column-oriented structure handles both structured and unstructured data while addressing speed, flexibility, and scalability challenges. Amazon EMR HBase on Amazon S3 extends these features by storing data directly in Amazon S3, enabling data persistence and cross-zone access while supporting compute-based cluster sizing and read-only replicas.
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Enhance Amazon EMR observability with automated incident mitigation using Amazon Bedrock and Amazon Managed Grafana | Amazon Web Services

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By Yu-Ting Su
| Amazon Web Services
Maintaining high availability and quick incident response for Amazon EMR clusters is important in data analytics environments. In this post, we show you how to build an automated observability system that combines Amazon Managed Grafana with Amazon Bedrock to detect and remediate EMR cluster issues.
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