Build visualizations with Amazon Athena and Tableau - DevOps Monitoring Dashboard on AWS

Build visualizations with Amazon Athena and Tableau

You can build visualizations using Tableau and Amazon Athena for the views created by this solution. By default, the solution deploys a set of pre-built Amazon QuickSight dashboards into your account. You can also choose other BI tools, such as Tableau, to build your own visualization. For more information, refer to Building AWS Data Lake visualizations with Amazon Athena and Tableau. The following database information can be used to build database connection:

  • Athena database name: aws_devops_metrics_db_so0143

  • You can build visualizations for the following views:

    • code_change_activity_view: This view contains data related to code pushes to AWS CodeCommit.

    • code_deployment_detail_view: This view contains data related to code deployments using AWS CodeDeploy.

    • code_build_detail_view: This view contains data related to code builds generated by AWS CodeBuild.

    • code_pipeline_detail_view: This view contains data related to code builds generated by AWS CodePipeline.

    • recovery_time_detail_view: This view contains Amazon CloudWatch Alarm data related to MTTR metrics. The duration_minutes column shows how long it takes to restore a service from its failure to success state at one time.

    • github_change_activity_view: This view contains data related to GitHub code change activities generated by changes made to GitHub repositories.

  • Table:

    Note

    Do not directly build visualizations for the following tables as they contain a large amount of unfiltered data. Instead, you must build visualizations for the views that contain a subset of data filtered for specific metrics.

    • aws_devops_metrics_table: This table is the entry point to most of data in the Amazon S3 metrics bucket (s3://YourS3MetricsBucket/DevopsEvents/). It is the base table for all the views except for code_build_detail_view. Do not directly build visualizations for this table. You should build visualizations for the views.

    • aws_codebuild_metrics_table: This table is the entry point to CodeBuild data in the Amazon S3 metrics bucket (s3://YourS3MetricsBucket/CodeBuildEvents/). It is the base table for code_build_detail_view. Do not directly build visualizations for this table. You should build visualizations for the view.

    • aws_github_metrics_table: This table is the entry point to GitHub data in the Amazon S3 metrics bucket (s3://YourS3MetricsBucket/GitHubEvents/). It is the base table for github_change_activity_view.

    • tagged_codecommit_table: This table contains the AWS CodeCommit repositories tagged by the user-specified tags. It points to JSON files in the Amazon S3 metrics bucket (s3://YourS3MetricsBucket/TaggedResources/CodeCommit) , which is used to join aws_devops_metrics_table to get repositories with matching tags.

    • tagged_codepipeline_table: This table contains the AWS CodePipeline pipelines tagged by the user specified tags. It points to JSON files in the Amazon S3 metrics bucket (s3://YourS3MetricsBucket/TaggedResources/CodePipeline), which is used to join aws_devops_metrics_table to get pipelines with matching tags.

    • tagged_codebuild_table: This table contains the AWS CodeBuild projects tagged by the user-specified tags. It points to JSON files in the Amazon S3 metrics bucket (s3://YourS3MetricsBucket/TaggedResources/CodeBuild), which is used to join aws_codebuild_metrics_table to get build projects with matching tags.

For more information about the database schema, refer to Database schema information.