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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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Evaluating sample Amazon Redshift data sharing architecture using Redshift Test Drive and advanced SQL analysis

AWS Big Data

Redshift Test Drive is a tool hosted on the GitHub repository that let customers evaluate which data warehouse configurations options are best suited for their workload. Generating and accessing Test Drive metrics The results of Amazon Redshift Test Drive can be accessed using an external schema for analysis of a replay.

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Apache HBase online migration to Amazon EMR

AWS Big Data

And during HBase migration, you can export the snapshot files to S3 and use them for recovery. Additionally, we deep dive into some key challenges faced during migrations, such as: Using HBase snapshots to implement initial migration and HBase replication for real-time data migration.

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In-place version upgrades for applications on Amazon Managed Service for Apache Flink now supported

AWS Big Data

Refer to Upgrading Applications and Flink Versions for more information about how to avoid any unexpected inconsistencies. The next recommended step is to test your application locally with the newly upgraded Apache Flink runtime. If you’re using Gradle, refer to How to use Gradle to configure your project.

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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

It also applies general software engineering principles like integrating with git repositories, setting up DRYer code, adding functional test cases, and including external libraries. For more information, refer SQL models. Snapshots – These implements type-2 slowly changing dimensions (SCDs) over mutable source tables.

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Find the best Amazon Redshift configuration for your workload using Redshift Test Drive

AWS Big Data

In this post, we answer that question by using Redshift Test Drive , an open-source tool that lets you evaluate which different data warehouse configurations options are best suited for your workload. Redshift Test Drive uses this process of workload replication for two main functionalities: comparing configurations and comparing replays.

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