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Integrate custom applications with AWS Lake Formation – Part 2

AWS Big Data

You can now test the newly created application by running the following command: npm run dev By default, the application is available on port 5173 on your local machine. For simplicity, we use the Hosting with Amplify Console and Manual Deployment options. The base application is shown in the workspace browser.

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Manage Amazon OpenSearch Service Visualizations, Alerts, and More with GitHub and Jenkins

AWS Big Data

It is advised to discourage contributors from making changes directly to the production OpenSearch Service domain and instead implement a gatekeeper process to validate and test the changes before moving them to OpenSearch Service. es.amazonaws.com' # e.g. my-test-domain.us-east-1.es.amazonaws.com, Leave the settings as default.

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Expanding data analysis and visualization options: Amazon DataZone now integrates with Tableau, Power BI, and more

AWS Big Data

Collaborating closely with our partners, we have tested and validated Amazon DataZone authentication via the Athena JDBC connection, providing an intuitive and secure connection experience for users. Choose Test connection. Choose Test Connection. DataZoneEnvironmentId : The ID of your DefaultDataLake environment.

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Federate to Amazon Redshift Query Editor v2 with Microsoft Entra ID

AWS Big Data

Select the Consumption hosting plan and then choose Select. Save the federation metadata XML file You use the federation metadata file to configure the IAM IdP in a later step. In the Single sign-on section , under SAML Certificates , choose Download for Federation Metadata XML. Choose Test this application.

Sales 92
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How REA Group approaches Amazon MSK cluster capacity planning

AWS Big Data

In each environment, Hydro manages a single MSK cluster that hosts multiple tenants with differing workload requirements. To address this, we used the AWS performance testing framework for Apache Kafka to evaluate the theoretical performance limits. The following figure shows an example of a test cluster’s performance metrics.

Metrics 79
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Introducing a new unified data connection experience with Amazon SageMaker Lakehouse unified data connectivity

AWS Big Data

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. The SageMaker Lakehouse data connection testing capability boosts your confidence in established connections. On your project, in the navigation pane, choose Data. Choose Next.

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Disaster recovery strategies for Amazon MWAA – Part 2

AWS Big Data

The solution for this post is hosted on GitHub. Backup and restore architecture The backup and restore strategy involves periodically backing up Amazon MWAA metadata to Amazon Simple Storage Service (Amazon S3) buckets in the primary Region. This is the bucket where you host all of your DAGs for your environment. [1.b]

Strategy 103