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Achieve data resilience using Amazon OpenSearch Service disaster recovery with snapshot and restore

AWS Big Data

This post focuses on introducing an active-passive approach using a snapshot and restore strategy. Snapshot and restore in OpenSearch Service The snapshot and restore strategy in OpenSearch Service involves creating point-in-time backups, known as snapshots , of your OpenSearch domain.

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Take manual snapshots and restore in a different domain spanning across various Regions and accounts in Amazon OpenSearch Service

AWS Big Data

Snapshots are crucial for data backup and disaster recovery in Amazon OpenSearch Service. These snapshots allow you to generate backups of your domain indexes and cluster state at specific moments and save them in a reliable storage location such as Amazon Simple Storage Service (Amazon S3). Snapshots are not instantaneous.

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Unleash the power of Snapshot Management to take automated snapshots using Amazon OpenSearch Service

AWS Big Data

in Amazon OpenSearch Service , we introduced Snapshot Management , which automates the process of taking snapshots of your domain. Snapshot Management helps you create point-in-time backups of your domain using OpenSearch Dashboards, including both data and configuration settings (for visualizations and dashboards).

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AWS Glue Data Catalog supports automatic optimization of Apache Iceberg tables through your Amazon VPC

AWS Big Data

The AWS Glue Data Catalog supports automatic table optimization of Apache Iceberg tables, including compaction , snapshots, and orphan data management. The data compaction optimizer constantly monitors table partitions and kicks off the compaction process when the threshold is exceeded for the number of files and file sizes.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

The AWS Glue crawler generates and updates Iceberg table metadata and stores it in AWS Glue Data Catalog for existing Iceberg tables on an S3 data lake. Snowflake integrates with AWS Glue Data Catalog to retrieve the snapshot location. Snowflake can query across Iceberg and Snowflake table formats.

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Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift

AWS Big Data

Create a role in the target account with the following permissions: { "Version":"2012-10-17", "Statement":[ { "Effect":"Allow", "Action":[ "redshift:DescribeClusters", "redshift-serverless:ListNamespaces" ], "Resource":[ "*" ] } ] } The role must have the following trust policy, which specifies the target account ID. Choose Create policy.

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Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

AWS Big Data

Create a role in the target account with the following permissions: { "Version":"2012-10-17", "Statement":[ { "Effect":"Allow", "Action":[ "redshift:DescribeClusters", "redshift-serverless:ListNamespaces" ], "Resource":[ "*" ] } ] } The role must have the following trust policy, which specifies the target account ID.