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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities. These metrics help agents improve their call handle time and also reallocate agents across organizations to handle pending calls in the queue.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

This data is sent to Apache Kafka, which is hosted on Amazon Managed Streaming for Apache Kafka (Amazon MSK). Expiring old snapshots – This operation provides a way to remove outdated snapshots and their associated data files, enabling Orca to maintain low storage costs.

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Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Redshift provisioned clusters also support query monitoring rules to define metrics-based performance boundaries for workload management queues and the action that should be taken when a query goes beyond those boundaries. A predicate consists of a metric, a comparison condition (=, ), and a value.

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Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

Although this post uses an Aurora PostgreSQL database hosted on AWS as the data source, the solution can be extended to ingest data from any of the AWS DMS supported databases hosted on your data centers. Monitoring – EMR Serverless sends metrics to Amazon CloudWatch at the application and job level every 1 minute.