# Advanced Advanced Advanced Dashboards require [CID Data Collection Stack](data-collection.md). This section covers the following dashboards: ## Contents + [Compute Optimizer Dashboard](compute-optimizer-dashboard.md) + [Trusted Advisor Organizational (TAO) Dashboard](trusted-advisor-dashboard.md) + [AWS Budgets Dashboard](budgets-dashboard.md) + [AWS News Feeds](news-feeds.md) + [Cost Anomaly Dashboard](cost-anomaly-dashboard.md) + [Extended Support - Cost Projection](extended-support.md) + [Graviton Savings Dashboard](graviton-savings-dashboard.md) + [Health Events Dashboard](health-events-dashboard.md) + [Support Cases Radar Dashboard](support-cases-radar.md) + [AWS End User Computing (EUC) Dashboard](euc-dashboard.md) + [ResilienceVue Dashboard](resiliencevue-dashboard.md) + [Data Collection Monitor](data-collection-monitor.md) + [Media Services Insights Hub](media-services-insights.md) # Compute Optimizer Dashboard Compute Optimizer Dashboard ## Introduction AWS Compute Optimizer recommends optimal AWS resources for your workloads to reduce costs and improve performance by using machine learning to analyze historical utilization metrics. Compute Optimizer Dashboard lets you view cost optimization and risk reduction opportunities for all accounts in your AWS Organizations across all AWS Regions. Out-of-the-box benefits of the COD include (but are not limited to): + Find over and underutilized resources (EC2, AutoScaling Groups, EBS, Lambda). + Get right-sizing recommendations. + Identify potential savings across all payer accounts and regions. + Track optimization progress over time by AWS Account team or business unit. ## Architecture ![\[architecture\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/images/architecture/compute-optimizer-architecture.png) 1. AWS Compute Optimizer Collects the data about running instances and uses Machine Learning to generate recommendations 1. CID Data Collection has a Lambda functions that on schedule assume a role in Management account(s) to trigger an export of AWS Compute Optimizer in each region configured in data collection stack. By default it i scheduled for every 14 days, but it can be changed in the parameters of the Data Collection Stack. 1. The AWS Compute Optimizer exports data to regional buckets. 1. The replication mechanisms consolidates all data from regional buckets to one data bucket. All exports on regional bucket will be deleted after 1 day as per lifecycle policy. 1. Quick Sight Dataset refreshes daily to show the latest state on the dashboard. ## Learn more + [3 New Features on the Compute Optimizer Dashboard](https://www.youtube.com/watch?v=IP_k2OXHPoo) See also: + A basics of Compute Optimizer Right Sizing in a [lab 200 Rightsizing with Compute Optimizer](https://wellarchitectedlabs.com/cost/200_labs/200_aws_resource_optimization/) + [AWS Compute Optimizer FAQ](https://aws.amazon.com/compute-optimizer/faqs/) ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=compute-optimizer-dashboard) ![\[Image of a compute optimizer dashboard in Quick Sight\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_demo.png) ## Prerequisites 1. To get right sizing recommendations you need to [Enroll all accounts to Compute Optimizer](https://docs.aws.amazon.com/compute-optimizer/latest/ug/getting-started.html#account-opt-in). You can use free version that provides recommendations based on 14 days of look-back period. 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure AWS Compute Optimizer Data Collection Module is enabled. 1. Ensure you have [Compute Optimizer enabled at Organization level](https://docs.aws.amazon.com/organizations/latest/userguide/services-that-can-integrate-compute-optimizer.html). ## Deployment **Example** If you already have CUDOS, Cost Intelligence Dashboard or KPI Dashboard installed via CloudFormation as described [here](deployment-in-global-regions.md), you can update the Stack by setting DeployComputeOptimizerDashboard to "yes" and updating the path of Data Collection S3 bucket (if different from default). If you do not have the stack installed, you can install using the instructions [here](deployment-in-global-regions.md) (you can ignore the Cost and Usage report part as it is not required for this dashboard). Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id compute-optimizer-dashboard ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. 1. You can provide also additional tag names. This dashboard supports 2 tags: Primary and Secondary. Tags are the "key" part of the Resource Tag. Please note that Tags here are case sensitive and they not AWS Cost Allocation Tags. Recommendation: You can use one Tag to define ownership of resource and another tag to define if this particular resource is eligible for RightSizing (default) or must be excluded for valid reason (DRP, Vendor Compliance, Test, or any other reason for resource to be over-provisioned).If your are not using tags, leave defaults. Tags that are using a dash as separator (`-`) are not supported by default. If you have this kind of tags you might need additional customization of a dataset compute\$1optimizer\$1all\$1options. For example in `primary_tag` field you can use `parseJson(replace(tags, '-', '_'),'$.My_Tag')` You can also define these tags later and apply to dashboard using `cid-cmd update --force --recursive` ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id compute-optimizer-dashboard ``` ## OPTIONAL STEPS **Manage Business Units Map** For managing Business Units please modify business\$1units\$1map view. You can update view definition providing your values, or you can create an csv file upload to s3, create a table and set business\$1units\$1map view to select from this table. ``` CREATE OR REPLACE VIEW business_units_map AS SELECT * FROM ( VALUES ROW ('`111111111`', '`account1`', '`Business Unit 1`') , ROW ('`222222222`','`account2`', '`Business Unit 2`') ) ignored_table_name (account_id, account_name, bu) ``` Also you can use business\$1units\$1map view as a proxy to other data sources. In case if you do not need Business Units functionality and you have CUDOS dashboard installed with account\$1map, you can use this view to SELECT from account\$1map. ``` CREATE OR REPLACE VIEW business_units_map AS SELECT account_id as account_id, account_name as account_name, '`Undefined`' as bu FROM account_map ``` ## Authors + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager + Voicu Chirtes, Senior Technical Account Manager + Timur Tulyaganov, Ex-Amazonian ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Trusted Advisor Organizational (TAO) Dashboard Trusted Advisor Organizational (TAO) Dashboard ## Introduction Amazon Trusted Advisor helps you optimize your AWS infrastructure, improve security and performance, reduce overall costs, and monitors service limits. Organizational view lets you view Trusted Advisor checks for all accounts in your AWS Organizations. The only way to visualize the organizational view is to use the TAO dashboard. The TAO dashboard is a set of visualizations that provide comprehensive details and trends across your entire AWS Organization. Out-of-the-box benefits of the TAO dashboard include (but are not limited to): + Quickly locate accounts that haven’t rotated their AWS IAM keys. + Find then sort unutilized and underutilized resources by cost or account. + Find accounts with not enabled CloudTrail logs + See a list of accounts that have reached 80% of individual service limits. **Note** All accounts must have a **Business**, **On-Ramp** or **Enterprise** Support Plan. ![\[Architecture\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/images/architecture/ta.png) ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=tao) ![\[Amazon Quick Sight Trusted Advisor demo dashboard\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/tao_demo.png) ## Prerequisites 1. Check Support Plan Make sure all concerned accounts have a **Business**, **On-Ramp** or **Enterprise** [Support Plan](https://console.aws.amazon.com/support/plans/home). 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure Trusted Advisor Data Collection Module is enabled. Version 3.14.1 or higher required. ## Deployment **Example** If you already have CUDOS, Cost Intelligence Dashboard or KPI Dashboard installed via CloudFormation as described [here](deployment-in-global-regions.md), you can update the Stack by setting **DeployTaoDashboard** to "yes" and updating the path of Data Collection S3 bucket (if different from default). If you do not have the stack installed, you can install using the instructions [here](deployment-in-global-regions.md) (Step 3) and setting **DeployTaoDashboard** parameter to "yes" (you can ignore the Cost and Usage report part Step 1 and Step 2 as it is not required for this dashboard). Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id ta-organizational-view ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id ta-organizational-view ``` ## Authors + Yuriy Prykhodko, Principal Technical Account Manager, AWS + Timur Tulyaganov, Ex-Amazonian + Sumit Dhuwalia, Senior Technical Account Manager, AWS ## Contributors + Oleksandr Moskalenko, Ex-Amazonian + Georgios Rozakis, Technical Account Manager, AWS ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # AWS Budgets Dashboard AWS Budgets Dashboard ## Introduction [AWS Budgets](https://aws.amazon.com/aws-cost-management/aws-budgets/) is a service that helps customers plan and track their cloud spending across AWS services. It allows customers to set custom budgets for their AWS costs and usage, enabling better financial management and control over their AWS resources. This dashboard gives you a clear, hierarchical view of your organization’s budgets, from the top-level down to individual departments and applications. Now, you can easily track budgeted, forecasted, and actual spend all in one place. With customizable visualizations and real-time insights, you’ll be empowered to make informed, data-driven decisions that drive strategic alignment and optimization. Identify areas for improvement, forecast future needs, and ensure your financial resources are being used efficiently. ![\[Architecture\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/images/architecture/budgets.png) ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=aws-budgets) ![\[Budget View\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/budgets_view.png) ![\[Budget Levels\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/budgets_view_levels.png) ## Tagging and Hierarchy Using tags with AWS Budgets adds a powerful layer of organization and flexibility to the budgeting process. Tags are key-value pairs that customers can attach to AWS resources as metadata. When applied to budgets, tags allow customers to: 1. Organize budgets hierarchically: Customers can create a tag structure that mirrors their organizational hierarchy, such as department/team/project. 1. Represent their financial structure: Tags can reflect a company’s cost centers, business units, or other financial divisions. 1. Create granular budgets: Set up budgets for specific projects, applications, or environments using relevant tags. 1. Improve cost allocation: Easily track and allocate costs to the appropriate business units or projects based on tags. 1. Enhance reporting: Generate more detailed and meaningful reports by filtering and grouping budget data using tags. By leveraging tags with AWS Budgets, customers can create a more organized and insightful budgeting system that aligns with their organization’s structure and financial practices (refer the below diagram). This approach provides greater visibility into AWS spend and helps make more informed decisions about resource allocation and cost optimization. This Dashboard shows budgets with a specific tag key `cid:budget-level`. ![\[Structure Of Tags\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/budgets-financial-structure.png) ## Prerequisites 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure Budgets and Organization Data collection modules are enabled. Version 3.0.3 or higher required. 1. Tagging your budgets enables the option of introducing hierarchy within the organizational budgets. To achieve this, we recommend to set the tags with a key value pair as below: ``` Key: cid:budget-level Value: Organization ``` ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=AWS-Budgets-Dashboard¶m_DashboardId=aws-budgets¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=AWS-Budgets-Dashboard¶m_DashboardId=aws-budgets¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install ---upgrade cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id aws-budgets ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id aws-budgets ``` ## Troubleshooting **Column "optimization\$1data.budgets\$1data.tags" cannot be resolved** If you see this issue on deployment please make sure you have updated the Data Collection stack to the version required on Prerequisites. ## Authors + Mohideen Hajamohideen, Sr. Cloud Infrastructure Architect + Marco De Bianchi, Sr. Cloud & FinOps Architect ## Contributors + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # AWS News Feeds AWS News Feeds ## Introduction This dashboard provides recent AWS feeds including What’s New, Blog Posts, Videos and Security Bulletins. It allows you to filter news by AWS service, feed type and category and quickly focus on the most important topics. You can deploy dashboard in your AWS account and embed in your internal web sites. We keep our demo dashboard up to date and you are welcome to use it to stay updated with AWS related news and watch youtube videos directly from the demo dashboard. ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=aws-feeds) ![\[AWS Feeds\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/aws-feeds.png) ## Prerequisites Deploy [Data Collection Lab](data-collection.md) and make sure AWS Feeds Module is selected. Version 3.0.8 or higher required. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=AWS-News-Feeds-Dashboard¶m_DashboardId=aws-feeds¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=AWS-News-Feeds-Dashboard¶m_DashboardId=aws-feeds¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Oncecomplete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id aws-feeds --data-collection-database-name optimization_data ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id aws-feeds ``` ## Authors + Francisco Tresgallo, Senior Technical Account Manager ## Contributors + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Cost Anomaly Dashboard Cost Anomaly Dashboard ## Introduction AWS Cost Anomaly Detection uses advanced Machine Learning to identify anomalous spend and root causes, empowering the customers to take action quickly. To make it easier for them to identify any sudden spike in the spends, they can visualize the insights into those anomalous spends across multiple accounts using Amazon Quick Sight that retrieves and refreshes the data periodically. Out-of-the-box benefits of the COD include (but are not limited to): + Early Detection - A centralized cloud cost anomaly dashboard will allow our customers to quickly identify and investigate cost anomalies. + Trend Analysis - identify trends and patterns associated with cost anomalies MOM, Account, Service etc. + Governance - Centralized Dashboard view across organization (Payer) for FinOps Team to track and monitor AWS Cost Anomalies at the Organization level. + Early Resolution - With CAD, FinOps team proactively work with different teams in the organization to prevent overruns. See also: + [AWS Cost Anomaly FAQ](https://aws.amazon.com/aws-cost-management/aws-cost-anomaly-detection/faqs/) ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=cost-anomaly-dashboard) ![\[Image of a cost anomaly dashboard in Quick Sight\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/ca_demo.png) ## Prerequisites 1. To get cost anomalies on abnormal or sudden spend increases in your AWS account you need to [Enable Cost Anomaly Detection in your account](https://docs.aws.amazon.com/cost-management/latest/userguide/settingup-ad.html). AWS Cost Anomaly Detection is a feature within Cost Explorer. To access AWS Cost Anomaly Detection, enable Cost Explorer. For instructions on how to enable Cost Explorer using the console, [see Enabling Cost Explorer](https://docs.aws.amazon.com/cost-management/latest/userguide/ce-enable.html). 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure Cost Anomalies Data Collection Module is enabled. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Cost-Anomaly-Dashboard¶m_DashboardId=aws-cost-anomalies¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Cost-Anomaly-Dashboard¶m_DashboardId=aws-cost-anomalies¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Oncecomplete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id aws-cost-anomalies --athena-database optimization_data ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id aws-cost-anomalies ``` ## Authors + Yash Bindlish, Enterprise Support Manager + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Extended Support - Cost Projection Extended Support - Cost Projection ## Introduction This dashboard provides insights on resources reaching extended support and projects the cost of extended support based on resource usage over a given period of time. Services with extended support covered by this dashboard: **ElastiCache Extended Support** With ElastiCache Extended Support, you can continue running your cache on a major engine version past the end of standard support date for an additional cost. If you don’t upgrade after the end of standard support date, you will be charged. Extended Support provides the following updates and technical support: + Security updates for critical and high CVEs for your cache and cache engine + Bug fixes and patches for critical issues + The ability to open support cases and receive troubleshooting help within the standard ElastiCache service level agreement This dashboard provides a clear view on ElastiCache clusters reaching extended support in the next 3, 6, 12 months, and beyond. It presents the estimated monthly cost of extended support, and allows you to drill down to cluster level, to review where your usage and estimated cost will be if, and when, your clusters enter the extended support period. See also: + [Amazon ElastiCache Extended Support](https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/extended-support.html) **EKS Extended Support** With Amazon EKS Extended Support, you can continue running your EKS clusters on a version that has reached the end of its standard support, for an additional 12 months. During extended support, Amazon EKS clusters will receive ongoing security patches for the Kubernetes control plane. Additionally, Amazon EKS will release patches for specific add-ons. This dashboard provides a clear view on EKS clusters reaching extended support in the next 3, 6, 12 months, and beyond. It presents the estimated monthly cost of extended support, and allows you to drill down to cluster level, to review where your usage and estimated cost will be if, and when, your clusters enter the extended support period. See also: + [Amazon EKS Extended Support FAQs](https://docs.aws.amazon.com/eks/latest/userguide/kubernetes-versions.html#extended-support-faqs) **RDS Extended Support** With Amazon RDS Extended Support, you can continue running your database on a major engine version past the RDS end of standard support date for an additional cost. The dashboard provides a clear view on databases reaching extended support in the next 3, 6, 12 months, and beyond. It presents the estimated monthly cost of extended support, and allows you to drill down to database instance level, to review where your usage and estimated cost will be if, and when, your databases enter the extended support period. See also: + [Using Amazon RDS Extended Support](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/extended-support.html) **OpenSearch Extended Support** With Amazon OpenSearch Extended Support, you can continue running your legacy ElasticSearch and OpenSearch versions beyond end of Standard Support for an incremental flat fee over regular instance pricing. The dashboard provides a clear view on ElasticSearch and OpenSearch domains reaching extended support in the next 3, 6, 12 months, and beyond. It presents the estimated monthly cost of extended support, and allows you to drill down to domain level, to review where your usage and estimated cost will be if, and when, your domains enter the extended support period. See also: + [Using Amazon OpenSearch Extended Support](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/what-is.html#standard-support-extended-suppport) ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=extended-support-cost-projection&sheet=default) ![\[Extended Support Cost Projection Dashboard\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/rdsxtsuppcp.png) ## Prerequisites 1. Deploy the [Foundational dashboards (CUDOS, CID, KPI)](deployment-in-global-regions.md) to ensure cost and usage information is available to produce the cost projection for RDS Extended Support based on actual usage for a given period of time. 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure Inventory Data collection module is enabled. Version 3.2.0 or higher required. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Extended-Support-Cost-Projection¶m_DashboardId=extended-support-cost-projection¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Extended-Support-Cost-Projection¶m_DashboardId=extended-support-cost-projection¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Oncecomplete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id extended-support-cost-projection ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id extended-support-cost-projection ``` ## Authors + Julio Chaves, Technical Account Manager + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Graviton Savings Dashboard Graviton Savings Dashboard ## Introduction The Graviton Savings Dashboard (GSD) visualizes your current usage of [AWS Graviton Processors](https://aws.amazon.com/ec2/graviton/) and estimates potential cost savings when switching to Graviton. This tool helps you make informed decisions about optimizing your cloud infrastructure and track your progress. [AWS Graviton Processors](https://aws.amazon.com/ec2/graviton/) are a CPU developed by Amazon using the Arm instruction set designed to deliver the best price performance for your cloud workloads running in Amazon Elastic Compute Cloud (Amazon EC2). AWS Graviton-based instances cost up to 20% less and use up to 60% less energy than comparable x86-based Amazon EC2 instances. Main features of Graviton Savings Dashboard: + **Current Graviton Usage and Realized Savings** - View your current Graviton usage and realized savings for Amazon EC2, RDS, OpenSearch and Elasticache + **Potential Graviton Savings** - Detect current workloads that are eligible for Graviton and evaluate potential savings from the transition. + **Governance** - Centralized Dashboard view allows FinOps Team to track and monitor AWS Graviton savings and opportunities across one or multiple AWS Organizations (Payers). [![AWS Videos](http://img.youtube.com/vi/https://www.youtube.com/embed/F_wskaHIfUk?rel=0/0.jpg)](http://www.youtube.com/watch?v=https://www.youtube.com/embed/F_wskaHIfUk?rel=0) ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=graviton-savings-dashboard). ![\[EC2 - Existing Usage\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/EC2_Graviton_Opportunity_GSD.png) See more screenshots in the [usage guide](#graviton-savings-usage-overview). ## Architecture Overview The Dashboard uses AWS CUR from [Foundational Dashboards Stack](deployment-in-global-regions.md), and additionally AWS Pricing and Inventory Modules from [Data Collection Stack](data-collection.md). These stacks automatically collect data and store on Amazon S3. Customers can then leverage Amazon Athena and provided Amazon Quick Sight dashboard for visualization and analysis. ![\[Data Collection Overview\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/basic-data-collection.png) ## Prerequisites 1. If you do not have your Cost and Usage Report (CUR) set up, follow Steps 1 and 2 from the [CUDOS, CID, and KPI Dashboard](deployment-in-global-regions.md) deployment guide. 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure Inventory Data collection module is enabled. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Graviton-Savings-Dashboard¶m_DashboardId=graviton-savings¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Graviton-Savings-Dashboard¶m_DashboardId=graviton-savings¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id graviton-savings ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id graviton-savings ``` ## Usage Overview ### Click here for the detailed usage overview The Graviton Savings Dashboard provides the ability for users to track current Graviton usage and realized savings, as well as identify potential migration opportunities. Each of the 4 services represented in the dashboard (EC2, RDS, ElastiCache, and OpenSearch) have dedicated tabs to review current usage and potential savings. **EC2** **Current Usage and Savings** The Current Amazon EC2 Graviton Usage and Savings section provides a comprehensive overview of your current usage of EC2 Graviton-based instances and the potential cost savings you realized by migrating workloads to Graviton. These savings are calculated in comparison to the latest Intel-based instance generation of the same size. The section also allows you to explore Graviton coverage by month, usage/savings by account and instance family, and unit costs trends to see how your Graviton adoption has impacted your workloads. This detailed information can help you assess the benefits and cost optimization opportunities of adopting Graviton-based EC2 instances. ![\[EC2 - Existing Usage\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/EC2_UsageSavings_GSD.png) **Graviton Opportunities** The Amazon EC2 Graviton Opportunity section provides insights into the potential cost savings you could realize by migrating eligible workloads to Graviton-based instances. This section allows you to analyze your Graviton coverage - both at the account level and by instance family. This can help you identify clusters of workloads that present the greatest opportunities to benefit from the cost advantages of Graviton. ![\[EC2 - Opportunities\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/EC2_Graviton_Opportunity_GSD.png) **RDS** **Current Usage and Savings** RDS has a similar Current Usage and Savings visuals to EC2, providing details on your current usage, realized savings, cost, and savings percentage. It also provides details by RDS Engine usage, as this is a large driver of eligibility for Graviton. ![\[RDS - Existing Usage\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/RDS_UsageSavings_GSD.png) **Graviton Opportunities** Eligibility for RDS Graviton is driven based on RDS Type, Engine, and version number. The below table details out eligibility for Graviton: | Type | MySQL | PostgreSQL | MariaDB | | --- | --- | --- | --- | | Amazon RDS | 8.0.17 and higher | 12.3, 13 and higher | 10.4.13, 10.5 and higher | | Amazon Aurora | 2.09.2 and higher | 11.9 and higher, 12.4 and higher | n/a | The RDS Graviton Opportunities section provides a breakdown of your Graviton eligibility based on several criteria. If your current database is using a compatible engine version and meets the required engine version, it will be displayed as "Eligible". If it meets the engine type requirements but does not meet the version number requirements, it will be listed as "Requires Update". Otherwise, it will be listed as "Ineligible". The "Eligibility and Savings by RDS Resource ID" table can be used as an explorer to identify workloads and determine potential savings for particular usage. You can use the controls at the top of the page and the filters on the table to isolate particular usage, and export the report to send to application teams to showcase instance-level savings. You can learn more about RDS Graviton Eligibility [here](https://aws.amazon.com/blogs/database/key-considerations-in-moving-to-graviton2-for-amazon-rds-and-amazon-aurora-databases/) ![\[RDS - Opportunities\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/RDS_Opportunity_GSD.png) **ElastiCache** **Current Usage and Savings** Similar to EC2 and RDS the Current Usage and Savings visuals for Elasticache, provide details on your current usage, realized savings, cost, and savings percentage. It also provides details by cache engine, as this is a large driver of eligibility for Graviton. ![\[ElastiCache\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/ElastiCache_UsageSavings_GSD.png) **Graviton Opportunities** The ElastiCache Graviton Opportunity section highlights the potential monthly savings from using Graviton processors for your ElastiCache clusters. This section identifies the eligible clusters that meet the criteria to migrate to Graviton-based instances. The eligibility for Graviton usage is based on the specific database engine and version running on the cluster. Your caches are eligible to move to Graviton if they are: + Redis - 5.0.6 and above + Memcached - 1.5.16 and above For more information, see the following supported versions documentation for [Redis](https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/supported-engine-versions.html) and [Memcached](https://docs.aws.amazon.com/AmazonElastiCache/latest/mem-ug/supported-engine-versions-mc.html) ![\[ElastiCache\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/ElastiCache_Opportunity_GSD.png) **OpenSearch** **Current Usage and Savings** Similar to other services, the Current Amazon OpenSearch Graviton Usage and Savings section provides insights into your usage by engine to give you context into the eligibility of Graviton usage. ![\[OpenSearch - Existing Usage\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/OpenSearch_UsageSavings_GSD.png) **Graviton Opportunities** OpenSearch Graviton eligibility is a bit more straight forward than other AWS Managed Services. The below table describes eligibility for both Amazon ElasticSearch and AmazonOpenSearch: | Type | Required Version | | --- | --- | | Amazon ElasticSearch | 7.9 or higher | | Amazon OpenSearch | All versions eligible | For more information on supported OpenSearch instance types, read more in the official [Amazon OpenSearch Service Documentation](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/supported-instance-types.html) ![\[OpenSearch - Opportunity Explorer\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/OpenSearch_Opportunity_GSD.png) ### Authors + Rosa Corley, Senior FinOps Commercial Architect + Rajani Guptan, Senior Technical Account Manager + Rem Baumann, Ex-Amazonian + Erik Petersen, Ex-Amazonian ### Contributors + Iakov Gan, Ex-Amazonian + Eric Christensen, Technical Account Manager + Yuriy Prykhodko, Principal Technical Account Manager + Travis James, Optimization Solutions Architect + John Masci, Principle Optimization Solutions Architect + Vinay Gaonkar, Principal Go To Market, EC2 Spot + Hahnara Hyun, Senior Specialist Solutions Architect, EC2 Graviton + Zi Shen Lim, Sustainability GTM, Graviton + Bhavik Gandhi, FinOps Commercial Architect + Shankar Gopalan, WWSO Specialist ## Feedback Support If you have feedback or questions on the dashboard, please send your inquiries to [aws-cid-graviton-savings-dashboard@amazon.com](mailto:aws-cid-graviton-savings-dashboard@amazon.com) **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Health Events Dashboard Health Events Dashboard ## Introduction [AWS Health](https://aws.amazon.com/premiumsupport/technology/aws-health/) is the authoritative data source for events and changes affecting your AWS cloud resources. Through a centralized view across your organization, AWS Health integrates with 200\$1 AWS services to aggregate important information in a timely manner. AWS Health notifies you about service events, planned changes, and other account matters to help you manage your resources and take actions where necessary. The CID Health Events Dashboard uses data collected from [AWS Health Organizational View API](https://docs.aws.amazon.com/health/latest/ug/aggregate-events.html) and creates a variety of visualizations for your past, current, and upcoming AWS Health events. The dashboard’s charts allow you analyze individual or multiple events to raise awareness and facilitate your operational planning. Some of the features of this dashboard include: + Drill down from summary views to granular details - See the most impactful events and drill down to lists of affected resources + Deprecating versions tracking - Analyze and plan for deprecating versions of different AWS services, such as RDS and Lambda + Upcoming event timeline - See the scope and dates of future events to facilitate operational planning + Consolidation - Centralized view of all accounts in an organization or across multiple payer accounts The Data Collection Stack uses AWS Organizations API to collect daily the AWS Health data. See more in [prerequisites](#health-event-dashboard-prerequisites). **Note** Please note that the data on this dashboard may have a lag of 48 hour or more. Please do not use this dashboard for monitoring or real time operational events. This dashboard is exclusively for review and longer term operational planning. Please use [AWS Health Notifications](https://docs.aws.amazon.com/health/latest/ug/manage-user-notifications.html) to get the real time information when needed. **Note** AWS Health might not include records of events that occurred in your organization before you enabled the organizational view feature. This limitation also applies to scheduled change announcements. **Note** You must have a Business, Enterprise On-Ramp, or Enterprise Support plan from AWS Support to use the AWS Health API. ## Architecture We recommend installing the Health Events Dashboards in a separate Data Collection Account (Can be the same with your other CID dashboards). ![\[Architecture\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/aws-health-archi.png) 1. The [Data Collection Stack](data-collection.md) provides an Amazon Lambda function that assumes a role in one or multiple Management accounts to retrieve daily the AWS Health Data and store it on Amazon S3. The Lambda only pulls data that are updated since the last retrieval. The stack also provides AWS Glue Tables to query collected data. 1. Cloud Intelligence Dashboards provide Amazon Athena views for querying data directly from the S3 bucket using an AWS Glue tables and Amazon Quick Sight Datasets and Dashboards, allowing Operation Teams acceding AWS Health data. Access can be secured through AWS IAM, IIC (SSO), and optional Row Level Security. ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo/?dashboard=health-events-dashboard) ![\[Health Dashboard Screenshot\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/he_dashboard.png) ## Prerequisites 1. Enable AWS Health events across accounts with organizational view. For this dashboard you need to [enable the organizational view of Health events](https://docs.aws.amazon.com/health/latest/ug/enable-organizational-view-in-health-console.html#enable-organizational-view-console). By default, you can use AWS Health to view the AWS Health events of a single AWS account. If you use AWS Organizations, you can also view AWS Health events centrally across your organization. This feature provides access to the same information as single account operations and it is the mechanism used to render this dashboard. You must have a Business, Enterprise On-Ramp, or Enterprise Support plan from AWS Support to use the AWS Health API. 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure Health Events Data Collection Module is enabled. Version 3.0.8 or higher required. 1. Prepare Athena If this is the first time you will be using Athena you will need to complete a few setup steps before you are able to create the views needed. If you are already a regular Athena user you can skip these steps and move on to the Enable Amazon Quick Sight section below. ### Click here to get Athena warmed up 1. From the services list, choose **S3** 1. Create a new S3 bucket for Athena queries to be logged to. Keep to the same region as the S3 bucket created for your Compute Optimizer data created via Data Collection Lab. 1. From the services list, choose **Athena** 1. Select **Get Started** to enable Athena and start the basic configuration ![\[Athena getting started page from the AWS console\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_athena.png) 1. At the top of this screen select **Before you run your first query, you need to set up a query result location in Amazon S3**. ![\[Athena Query editor in the AWS console\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_athena_v2.png) 1. Validate your Athena primary workgroup has an output location by + Open a new tab or window and navigate to the **Athena** console + Select **Workgroup: primary** ![\[Athena Query editor with primary workgroup highlighted\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_athena_v3.png) + Confirm your **Query result location** is configured with an S3 bucket path. + If not configured, continue to setting up by clicking **Edit workgroup** ![\[Athena workgroup settings with the edit workgroup button highlighted\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_athena_v4.png) + Add the **S3 bucket path** you have selected for your Query result location and click save ![\[Athena edit workgroup with the query results location input highlighted\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_athena_v5.png) 1. Enable Amazon Quick Sight Amazon Quick Sight is the AWS Business Intelligence tool that will allow you to not only view the Standard AWS provided insights into all of your accounts, but will also allow to produce new versions of the Dashboards we provide or create something entirely customized to you. If you are already a regular Amazon Quick Sight user you can skip these steps. ### Click here to get started with Amazon Quick Sight 1. Log into your AWS Account and search for **Quick Sight** in the list of Services 1. You will be asked to **sign up** before you will be able to use it ![\[Page with a button to sign up for Amazon Quick Sight\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/qs.png) 1. After pressing the **Sign up** button you will be presented with 2 options, please ensure you select the **Enterprise Edition** during this step 1. Select **continue** and you will need to fill in a series of options in order to finish creating your account. + Ensure you select the region that is most appropriate based on where your S3 Bucket is located containing your CO report files. ![\[Quick Sight configuration page with the Amazon S3 checkbox highlighted\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_qs_v2.png) + Enable the Amazon S3 option and select the bucket where your Compute Optimizer data created via Data Collection Lab are located ![\[Quick Sight Amazon S3 bucket selection dialog\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_qs_v3.png) 1. Click **Finish** & wait for the congratulations screen to display 1. Click **Go to Amazon Quick Sight** ![\[Amazon Quick Sight finished configuration page with button to go to Quick Sight\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_qs_v4.png) 1. Check you have **Amazon Quick Sight Enterprise Edition** ![\[Quick Sight page with callouts to select Manage Quick Sight from the menu to confirm the Quick Sight edition\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/co_qs_v5.png) ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Health-Events-Dashboard¶m_DashboardId=health-events-dashboard¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Health-Events-Dashboard¶m_DashboardId=health-events-dashboard¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id health-events-dashboard ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id health-events-dashboard ``` ## Authors + Eric Christensen, Senior Technical Account Manager + Iakov Gan, Ex-Amazonian ## Contributors + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Support Cases Radar Dashboard Support Cases Radar Dashboard ## Introduction AWS Support Cases Radar Dashboard provides a centralized platform to consolidate, monitor and analyze [AWS Support Cases](https://docs.aws.amazon.com/awssupport/latest/user/getting-started.html) across all linked accounts and multiple AWS organizations. With unified view of all support cases, this dashboard empowers cloud governance teams to enhance operational efficiency and maximize the value delivered by AWS Support. ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=support-cases-radar) ![\[image of a support cases radar dashboard in Quick Sight\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/support_cases_radar_dashboard.png) ## Architecture Overview ![\[Data Collection Overview\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/support_cases_radar_arch.png) The Data Collection Stack collects the information about cases on a daily basis. Only the cases which have changes are collected. An Amazon Step Function saves case information on Amazon S3 and sends an event with case reference to the Default Bus of EventBridge. The Quick Sight dashboard is refreshed every night to provide case summary and insights. ## Prerequisites 1. Make sure all concerned accounts have a **Business**, **On-Ramp** or **Enterprise** [Support Plan](https://console.aws.amazon.com/support/plans/home). 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure Support Cases Data Collection Module is enabled. ## Deployment **Example** **Prerequisite:** To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Support-Cases-Radar-Dashboard¶m_DashboardId=support-cases-radar¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Support-Cases-Radar-Dashboard¶m_DashboardId=support-cases-radar¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy ---dashboard-id support-cases-radar ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Optional Plugins Support Cases Radar has optional plugins that can be deployed to enable additional capabilities such as a generative AI case summarization. [Optional Plugins](optional-plugin.md) ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id support-cases-radar ``` ## Authors + Raffy Armistead, Senior Technical Account Manager + Samuel Chniber, Senior Solution Architect + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Optional Plugins Optional Plugins ## Steps + [Summarization Plugin](summarization-plugin.md) # Summarization Plugin Summarization Plugin **Note** The AWS Support Cases Summarization powered by Amazon Bedrock may not capture all nuances of the original conversation with the AWS Support. It should be verified against the full transcript which remains the single source of truth for accuracy and completeness. See [AWS Responsible AI Policy](https://aws.amazon.com/ai/responsible-ai/policy/). **Note** The AWS Support Cases Dashboard is not realtime and might have 24h-48h delay. For the ongoing cases please check AWS Support Center in the respective account. ## Authors + Samuel Chniber, Senior Solution Architect + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide ## Introduction AWS Support Cases Summarization is a Plugin to the AWS Support Cases Radar Dashboard that leverages the power of Generative AI (GenAI) through the use of Amazon Bedrock. This plugin aims at summarizing the [AWS support cases](https://docs.aws.amazon.com/awssupport/latest/user/getting-started.html) problem statement, communications with the AWS Support Engineers and recapping eventual actions to be carried out either by AWS or by the customer for resolution. ## Architecture Overview ![\[Data Collection Overview\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/support_cases_summarization_arch.png) The Summarization Stack deploys a rule to Default Eventbridge bus to capture events sent by the Data Collection Stack. The Eventbridge Rule processes the message by sending it to an Amazon SQS queue. The SQS Queue is responsible for triggering a lambda function that executes Bedrock API call for the summarization and enriches the collected support case data by adding the summaries back to Amazon S3. ## Deployment steps ### Step 1 of 4: Deploy the AWS Support Cases Radar Dashboard This plugin has a dependency on the successful deployment of the AWS Support Cases Radard Dashboard. [Read More](support-cases-radar.md) ### Step 2 of 4: Enable Foundation Model on Amazon Bedrock To get AWS Support Cases Summarized you need to [add access to Amazon Bedrock foundation models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html). #### Click here to see instructions on the AWS Console ![\[Enable Foundation Model on Amazon Bedrock\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/support_cases_summarization_model_access.gif) ### Step 3 of 4: (Optional) Deploy an Amazon Bedrock Guardrail in the Data Collection Account in the Inference Region [Amazon Bedrock Guardrails](https://docs.aws.amazon.com/bedrock/latest/userguide/guardrails.html) is a crucial security feature for generative AI applications that helps implement safeguards based on specific use cases and responsible AI policies. It provides an additional layer of protection on top of the native safeguards offered by foundation models (FMs). We provide an example of Amazon Guardrails stack, but if your company is already using Guardrails you can skip this Step and continue to installation of the Plugin Stack (Step 4). [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?&templateURL=https://aws-managed-cost-intelligence-dashboards-us-east-1.s3.amazonaws.com/cfn/plugins/support-case-summarization/guardrail/guardrail.yaml&stackName=CidSupportCaseBedrockGuardrailStack](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?&templateURL=https://aws-managed-cost-intelligence-dashboards-us-east-1.s3.amazonaws.com/cfn/plugins/support-case-summarization/guardrail/guardrail.yaml&stackName=CidSupportCaseBedrockGuardrailStack) #### Click here to know more about plugin stack parameters This plugin comes with the following reasonable defaults that can be overridden through the parameters exposed by the CloudFormation template: | Parameter | Description | Default | | --- | --- | --- | | BlockedInputMessage | Message to return when the Amazon Bedrock Guardrail blocks a prompt. | \$1"executive\$1summary":"Amazon Bedrock Guardrails has blocked the AWS Support Case Summarization.","proposed\$1solutions":"","actions":"","references":[],"tam\$1involved":"","feedback":""\$1 | | BlockedOutputMessage | Message to return when the Amazon Bedrock Guardrail blocks a model response | ’’ | | IncludeSexualContentFilter | Whether to include Sexual Content Filter in the Guardrail or not | 'yes' | | SexualContentFilterInputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces. | 'HIGH' | | SexualContentFilterOutputStrength | The strength of the content filter to apply to model responses. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | IncludeViolentContentFilter | Whether to include Violent Content Filter in the Guardrail or not | 'yes' | | ViolentContentFilterInputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | ViolentContentFilterOutputStrength | The strength of the content filter to apply to model responses. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | IncludeHateContentFilter | Whether to include Violent Content Filter in the Guardrail or not | 'yes' | | HateContentFilterInputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | HateContentFilterOutputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | IncludeInsultsContentFilter | Whether to include Insults Content Filter in the Guardrail or not | 'yes' | | InsultsContentFilterInputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | InsultsContentFilterOutputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | IncludeMisconductContentFilter | Whether to include Insults Content Filter in the Guardrail or not | 'yes' | | MisconductContentFilterInputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | MisconductContentFilterOutputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | | IncludePromptAttackContentFilter | Whether to include Insults Content Filter in the Guardrail or not | 'yes' | | PromptAttackContentFilterInputStrength | The strength of the content filter to apply to prompts. As you increase the filter strength, the likelihood of filtering harmful content increases and the probability of seeing harmful content in your application reduces | 'HIGH' | ### Step 3 of 4: Deploy the AWS Support Case Summarization Stack In the Data Collection Account In this step we will deploy the summarization Plugin stack via cloud formation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?&templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/case-summarization/case-summarization.yaml&stackName=CidSupportCaseSummarizationStack](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?&templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/case-summarization/case-summarization.yaml&stackName=CidSupportCaseSummarizationStack) #### Click here to know more about plugin stack parameters This plugin comes with the following reasonable defaults that can be overridden through the parameters exposed by the CloudFormation template: | Parameter | Description | Default | | --- | --- | --- | | BedrockRegion | The AWS Region from which the Summarization is performed | us-east-1 | | Instructions | Additional instructions passed to the Large Language Model for the summarization process customizability | ’’ | | Provider | Large Language Model Provider for the summarization process customizability | Anthropic | | FoundationModel | Foundation Model to be used for the summarization process | Claude 3.5 Sonnet | | InferenceType | Summarization process Inference Type | "ON\$1DEMAND" | | Temperature | Summarization process Temperature | 0 | | MaxTokens | Summarization process Maximum Tokens | 8096 | | MaxRetries | Summarization process Maximum Retries | 30 | | Timeout | Summarization process Timeout in seconds | 60 | | BatchSize | Summarization process Batch Size for parallel processing | 1 | | GuardrailId | Amazon Bedrock Guardrail ID to be used (Use this parameter in case you are using an externally managed Guardrail configuration. Leave empty if not planning to use Amazon Bedrock Guardrail) | ’’ | | GuardrailVersion | Amazon Bedrock Guardrail Version to be used (Use this parameter in case you are using an externally managed Guardrail configuration. Leave empty if not planning to use Amazon Bedrock Guardrail) | ’’ | | GuardrailTrace | The trace behavior for the guardrail | "ENABLED" | ## Post Deployment ### Where i can see summarizations? You will be able to see summarizations in the dashboard. There are short executive summaries in the table with cases and also a more detailed information with the summary of solution and current actions in the table below once you select the case. The summaries only appear after 48-24h and only for updated cases. ### Can I force summarization for all cases? Yes, you can trigger the refresh of all Support Cases and it will generate summaries as well. 1. Go to the Amazon S3 Bucket of data collection and delete the folder `support-cases/` to trigger collection for the last 12 months. (Or you can modify `last_read` field in json file `s3://cid-data-XXX/support-cases/support-cases-status/payer_id=XXX/XXX.json` to trigger new collection and summaries generation for less then for 12 months). 1. Go to Amazon Step Functions and execute `CID-DC-support-cases-StateMachine` this must collect all Support Cases. 1. You can check the activity of the lambda `CID-DC-support-case-summarization-Lambda`. Make sure this lambda is not triggered errors (Typical issue is the enabling of access to the model. See above). 1. Go to Quick Sight and refresh the dataset `support_cases_communications_view`. Once the refresh finishes you can check the Dashboard. The table with cases and case details must contain executive and detailed summaries. ### How often Summarization are updates? The summarization plugin automatically generates summaries of support case histories based on past communications. The data collection by default operates on a daily basis. Once the plugin is deployed, the summarization stack enriches cases with summaries right after daily collecting new data. Each day, data collection gathers all communications that have occurred since the previous collection. The Quick Sight dashboard updates data on the daily schedule as well. As a result, there may be up to a 24-hour delay between when a communication occurs and when it appears in the dashboard. We recommend using the AWS Support center to get the latest information on the status of the current cases. # AWS End User Computing (EUC) Dashboard AWS End User Computing (EUC) Dashboard ## Introduction The End User Computing (EUC) Dashboard provides a unified view of your AWS EUC environment through an intuitive Quick Sight interface. Key capabilities include: + Operational visibility into Amazon WorkSpaces and Amazon AppStream 2.0 usage patterns + Cost optimization insights and spending analytics + Performance monitoring with CloudWatch metrics integration + WorkSpaces Logon statistics + Resource utilization tracking and trending + Recommendations for environment optimization This solution helps teams make data-driven decisions to optimize costs, improve operational efficiency, and enhance the end-user experience across their EUC estate. ![\[EUC Dashboard Screenshot\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/euc/executive_summary.png) The dashboard has six tabs: + **Summary**: + Break down of EUC services costs for last 3 months. + Top Spending accounts for each service. + High level summary of your EUC estate. ![\[Insights\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/euc/workspace_insights.png) + **Amazon WorkSpaces Insights**: + In-dept break down of WorkSpaces costs for entire environment, additional insights not available in the Cost Usage Report including: + Protocol + Operating Systems + Daily Cost breakdown. + WorkSpaces Monthly usage. + WorkSpaces Cost Breakdown. + Workspaces Software bundle information. ![\[Insights\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/euc/workspace_usage.png) ![\[Insights\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/euc/workspace_logon_details.png) + **Amazon WorkSpaces Usage**: + WorkSpaces User connections. + Top10 Daily usage. + Directory cost breakdown. + WorkSpaces daily usage and Hours used. + WorkSpaces Logon information + Last Logon + Low Usage + AlwaysOn WorkSpaces Logon information + Never Logged on + **Amazon WorkSpaces Metrics**: + This tab is additional will breaks down Cloudwatch CPU/Memory utilization of WorkSpaces. ![\[AppStream 2.0 Highlights\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/euc/as2_details.png) + **Amazon AppStream 2.0** + Detail overview of AppStream 2.0 environment. + **EUC Cost Optimization** + Cost saving opportunities in your EUC environment. ## Architecture ![\[Image of Amazon EUC Dashboard architecture\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/euc/euc_dashboard_cid.png) 1. The EUC Dashboard is depended on AWS Data Exports service delivers Cost & Usage Report (CUR2) daily to an Amazon S3 Bucket in the Management Account. 1. The EUC Dashboard also requires Data Collection lab for the Amazon Lambda to capture WorkSpaces data and CloudWatch metrics and copies Export data to a dedicated Data Collection Account automatically. EUC Dashboard can be configured during setup to use AWS Organizations (all linked accounts) or specific linked accounts to capture this data. ## Prerequisites 1. Deploy one or more of the foundational dashboards: [CUDOS, Cost Intelligence, or KPI Dashboard](cudos-cid-kpi.md). This will enable CUR and will enable required Quick Sight and Athena resources needed for this dashboard. 1. [Deploy](data-collection-deployment.md) or [Update](data-collection-update.md) the Data Collection Lab and make sure the following modules are enabled. Version 3.2.0 or higher required. + **Include Inventory Collector Module** (Mandatory) - This enables the collection of WorkSpaces environmental information using the WorkSpaces API. + **Include WorkSpaces Utilization Data Collection Module** (Optional) - This enables the collection of Cloudwatch metrics for WorkSpaces. Please see **Visualizing WorkSpaces Cloudwatch Metric** section below to configure this. + **EUC Module Settings** (Optional) - You can choose to scan all linked accounts in an organization or specify accounts that have WorkSpaces deployed, provide a comma-separated list of account IDS in the field to only scan these accounts. Leaving blank will scan all accounts. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=EUC-Dashboard¶m_DashboardId=euc-dashboard¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=EUC-Dashboard¶m_DashboardId=euc-dashboard¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/?tab=readme-ov-file#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id euc-dashboard ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. 1. Select the EUC Dashboard and hit enter 1. Follow any instructions in the command line tool 1. EUC Dashboard will deploy with a link ## **Visualizing WorkSpaces Cloudwatch Metric** (Optional) In the EUC Dashboard, to view the WorkSpaces Cloudwatch metrics in the **WorkSpaces Metrics** tab, follow these steps: + During Deployment, make sure you selected **yes** for the **Include WorkSpaces Utilization Data Collection Module** parameter. + Go to the [Amazon Athena](https://console.aws.amazon.com/athena/) Query Editor. + Select the database that has the views for CID. By default it can be CUR 1 **cid\$1cur** cur or CID 2 **cid\$1data\$1export** cur2 database. + Run the following query to update **euc\$1metrics\$1view** view in Amazon Athena, **replacing the cur table name 'Line 89' based on version of cur running. e.g. "cid\$1data\$1export"."cur2" cur** ### Expand SQL Query ``` CREATE OR REPLACE VIEW "euc_metrics_view" AS WITH workspace_metrics AS ( SELECT m."WorkspaceId" , m."UserName" , CAST(parse_datetime(m.timestamp, 'yyyy-MM-dd HH:mm:ss') AS timestamp) cw_timestamp , m."State" , m."BundleId" , m."DirectoryId" , m."ComputerName" , m."RunningMode" , m."RootVolumeSizeGib" , m."UserVolumeSizeGib" , m."accountid" , m."region" , m."CPUUsage" , m."MemoryUsage" , m."InSessionLatency" , m."UserVolumeDiskUsage" , m."RootVolumeDiskUsage" , m."UpTime" , CAST(parse_datetime(w.lastconnected, 'MM/dd/yy HH:mm:ss') AS timestamp) lastconnected FROM ("optimization_data"."workspaces_metrics_data" m LEFT JOIN "optimization_data"."inventory_workspaces_data" w ON (m."WorkspaceId" = w."WorkspaceId")) ) SELECT wi."WorkspaceId" , wi."UserName" , wi.cw_timestamp , wi."State" , wi."BundleId" , wi."DirectoryId" , wi."ComputerName" , wi."RunningMode" , wi."RootVolumeSizeGib" , wi."UserVolumeSizeGib" , wi."accountid" , wi."region" , wi."CPUUsage" , wi."MemoryUsage" , wi."InSessionLatency" , wi."UserVolumeDiskUsage" , wi."RootVolumeDiskUsage" , wi."UpTime" , wi.lastconnected , split_part(billing_period, '-', 1) year , split_part(billing_period, '-', 2) month , bill_billing_period_start_date billing_period , date_trunc('day', CAST(line_item_usage_start_date AS timestamp)) usage_date , bill_payer_account_id payer_account_id , line_item_usage_account_id linked_account_id , line_item_line_item_type charge_type , line_item_product_code , line_item_usage_type , line_item_operation , line_item_line_item_description , line_item_resource_id , product['product_family'] product_product_family , product_instance_type , product_instance_family , product['product_name'] product_product_name , product['operating_system'] product_operating_system , product['group'] product_group , product['bundle_description'] product_bundle_description , product['bundle_group'] product_bundle_group , product['resource_type'] product_resource_type , product['storage'] product_storage , product['running_mode'] product_running_mode , product['group_description'] product_group_description , product['software_included'] product_software_included , pricing_unit , pricing_term , split_part(line_item_resource_id, '/', 2) resource_id , split_part(line_item_resource_id, ':', 6) resource_type , split_part(line_item_resource_id, 'directory/', 2) resource_directory_id , CAST(line_item_unblended_cost AS DECIMAL(18, 6)) line_item_unblended_cost , CAST(line_item_usage_amount AS DECIMAL(18, 6)) line_item_usage_amount , CAST(pricing_public_on_demand_cost AS DECIMAL(18, 6)) pricing_public_on_demand_cost , sum((CASE WHEN ("line_item_line_item_type" = 'Usage') THEN "line_item_usage_amount" ELSE 0 END)) "usage_quantity" , sum("line_item_unblended_cost") "unblended_cost" FROM ( cur2 LEFT JOIN workspace_metrics wi ON ((split_part(cur2.line_item_resource_id, '/', 2) = wi.workspaceid) AND (cur2.line_item_usage_account_id = wi.accountid))) WHERE ((("bill_billing_period_start_date" >= ("date_trunc"('month', current_timestamp) - INTERVAL '7' MONTH)) AND (CAST("concat"("billing_period", '-01') AS date) >= ("date_trunc"('month', current_date) - INTERVAL '7' MONTH)) AND (line_item_product_code = 'AmazonWorkSpaces')) OR (line_item_product_code = 'AmazonAppStream') OR (line_item_product_code = 'AWSDirectoryService')) GROUP BY 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52 ``` ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id euc-dashboard ``` ## Authors + Christian O’Donoghue, Senior Technical Account Manager ## Contributors + Daniel Matlock, Technical Account Manager + James Gaskell, Ex-Amazonian + Yuriy Prykhodko, AWS Principal Technical Account Manager + Iakov Gan, Ex-Amazonian + Brian Sheppard, AWS Principal Technical Account Manager + Natassa Eleftheriou, Senior Technical Account Manager ## Feedback & Support Have a success story to share with the Team, suggest an improvement or report an error? + Please email: [euc-dashboard@amazon.com](mailto:euc-dashboard@amazon.com) + Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # ResilienceVue Dashboard ResilienceVue Dashboard ## Introduction The ResilienceVue Dashboard provides you with valuable insights into your current AWS workloads assessed by AWS Resilience Hub by consolidating the assessments across accounts and workloads in your AWS Organizations across all AWS Regions and Payer accounts. Out-of-the-box benefits of the ResilienceVue include (but are not limited to): + Monitor Application Resilience across Organization + Assess Application RTO/RPO targets + Quick visibility into Policy breaches across all accounts and regions + Analyze Infrastructure recommendation trends + Track Unimplemented operational recommendations To learn more about AWS Resilience Hub, See: + [How to Manage Application Resilience using AWS Resilience hub](https://catalog.workshops.aws/aws-resilience-hub-lab/en-US) + [AWS Resilience Hub - Getting Started](https://docs.aws.amazon.com/resilience-hub/latest/userguide/getting-started.html) ## Architecture ![\[Architecture\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/images/architecture/rh_architecture.png) 1. The "[Data Collection Lab](data-collection.md)" provides an Amazon Lambda function that assumes a role in one or multiple Linked accounts to retrieve daily the AWS Resilience Hub assessment Data and store it on Amazon S3. The Lambda only pulls data that are updated since the last retrieval. The stack also provides AWS Glue Tables to query collected data. 1. Cloud Intelligence Dashboards provide Amazon Athena views for querying data directly from the S3 bucket using an AWS Glue tables and Amazon Quick Sight Datasets and Dashboards, allowing Enterprise Teams access to AWS Resilience Hub data. Access can be secured through AWS IAM, IIC (SSO), and optional Row Level Security. ## Demo Dashboard Get more familiar with Dashboard using the live, interactive demo dashboard following this [link](https://cid.workshops.aws.dev/demo?dashboard=resiliencevue) ![\[Image of ResilienceVue dashboard in Quick Sight\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/rv_demo.png) ## Prerequisites 1. To assess resilience for an application, you need to [Add an application to AWS ResilienceHub](https://docs.aws.amazon.com/resilience-hub/latest/userguide/describe-applicationlication.html). You can try AWS Resilience Hub free for 6 months, for your first 3 applications. For more information on pricing, follow [AWS Resilience Hub pricing](https://aws.amazon.com/resilience-hub/pricing/) 1. Deploy or update [Data Collection Lab](data-collection.md) and make sure ResilienceVue Data Collection Module is enabled. Version 3.12.0 or higher required. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Resiliencevue-Dashboard¶m_DashboardId=resiliencevue¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Resiliencevue-Dashboard¶m_DashboardId=resiliencevue¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id resiliencevue ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id resiliencevue ``` ## Authors + Subha Kalia, Senior Technical Account Manager + Ravindra Kori, Senior Solutions Architect + Praney Mahajan, Senior Technical Account Manager + Beau Henry, Technical Account Manager ## Contributors + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Data Collection Monitor Data Collection Monitor ## Introduction The [Data Collection Lab](data-collection.md) tooling provides instrumentation log data to help you monitor the executions of the various modules of the Data Collection Framework. Starting with version 3.11, most Data Collection modules emit basic log data to track module execution and potential errors encountered. This dashboard reads that instrumentation data to present multiple views to track historical executions as well as troubleshoot any issues. As of this version, the monitoring is based on Step Function execution. Failures in individual Lambda functions are caught by the module’s Step Function and, in some circumstances, the Lambda error is available through the dashboard. Errors for any given execution will be listed on the dashboard with a link to the Step Function execution instance pertaining to it. You can investigate the error by clicking on the link. Errors are also reported to CloudWatch metrics under the namespace "CID-DataCollection", for which you can optionally setup an alarm for more active monitoring. Future releases will convey more granular Lambda error details and links to those execution logs. ## Preview ![\[Data Collection Monitor Screenshot\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/data_collection_monitor_01.png) ## Prerequisites Deploy or update the [Data Collection Lab](data-collection.md) to version 3.11 or higher and include whatever modules you intend to use. Once deployed, any modules installed or updated will automatically be enabled for logging and picked up by the dashboard with the exception of the Feeds and Pricing modules. They will be enabled for instrumentation at a later time. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install Foundational Dashboards CFN with version v4.0.0 or above as described [here](deployment-in-global-regions.md#deployment-in-global-region-deploy-dashboard) 1. Log in to to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Data-Collection-Monitor¶m_DashboardId=dc-monitor¶m_RequiresDataCollection=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Data-Collection-Monitor¶m_DashboardId=dc-monitor¶m_RequiresDataCollection=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id dc-monitor ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that dashboards are not updated with update of CloudFormation Stack. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id dc-monitor ``` ## Authors + Eric Christensen, Senior Technical Account Manager ## Contributors + Iakov Gan, Ex-Amazonian + Yuriy Prykhodko, Principal Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide **Note** These dashboards and their content: (a) are for informational purposes only, (b) represent current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. # Media Services Insights Hub Media Services Insights Hub ## Introduction The Media Services Insights Hub (MSIH) dashboard provides comprehensive visibility into AWS Elemental Media Services usage, costs, and performance metrics. This dashboard leverages AWS Cost and Usage Report (CUR) data to deliver actionable insights for optimizing media workflows and managing costs across your media infrastructure. The dashboard covers key AWS Elemental Media Services including: + [AWS Elemental MediaConnect](https://aws.amazon.com/mediaconnect/) - Secure, reliable live video transport + [AWS Elemental MediaConvert](https://aws.amazon.com/mediaconvert/) - File-based video transcoding + [AWS Elemental MediaLive](https://aws.amazon.com/medialive/) - Live video processing + [AWS Elemental MediaPackage](https://aws.amazon.com/mediapackage/) - Video origination and packaging + [AWS Elemental MediaTailor](https://aws.amazon.com/mediatailor/) - Video personalization and monetization ![\[Image of Media Services Insights Hub architecture\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/media_services_insights_02.png) The MSIH dashboard is organized into intuitive tabs: 1. **Executive Summary** High-level overview of media services costs, usage trends, and key performance indicators across all services. 1. **MediaLive Reservations & Savings** Deep-dive into current and potential savings achieved through AWS Elemental MediaLive reservations. 1. **MediaConnect** Detailed analysis of live video transport costs, connection usage, and data transfer metrics. 1. **MediaConvert** Comprehensive view of transcoding job costs, queue utilization, and processing time analysis. 1. **MediaLive** In-depth monitoring of live streaming costs, channel utilization, and reservation optimization opportunities. 1. **MediaTailor** Insights into ad insertion costs, session metrics, and revenue optimization opportunities. 1. **MediaPackage** Analysis of video packaging and origination costs, endpoint usage, and content delivery metrics. Each tab provides progressively detailed insights to help you optimize your media workflows and control costs effectively. ## Demo Dashboard Get more familiar with the dashboard using the live, interactive demo by following this [link](https://cid.workshops.aws.dev/demo?dashboard=media-services-insights) ![\[Image of Media Services Insights Hub in Quick Sight\]](http://docs.aws.amazon.com/guidance/latest/cloud-intelligence-dashboards/images/media_services_insights_01.png) ## Prerequisites Deploy the [CID Foundational Dashboards](dashboard-foundational.md) stack. This will enable your CUR, Amazon Athena and Quick Sight resources required for this and other dashboards. ## Deployment **Example** **Prerequisite**: To install this dashboard using CloudFormation, you need to install the [Data Exports Lab](data-exports.md) 1. Log in to your **Data Collection** Account. 1. Click the Launch Stack button below to open the **pre-populated stack template** in your CloudFormation. [https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Media-Services-Insights-Hub¶m_DashboardId=media-services-insights¶m_RequiresDataExports=yes](https://console.aws.amazon.com/cloudformation/home#/stacks/create/review?templateURL=https://aws-managed-cost-intelligence-dashboards.s3.amazonaws.com/cfn/cid-plugin.yml&stackName=Media-Services-Insights-Hub¶m_DashboardId=media-services-insights¶m_RequiresDataExports=yes) 1. You can change **Stack name** for your template if you wish. 1. Leave **Parameters** values as it is. 1. Review the configuration and click **Create stack**. 1. You will see the stack will start in **CREATE\$1IN\$1PROGRESS**. Once complete, the stack will show **CREATE\$1COMPLETE** 1. You can check the stack output for dashboard URLs. **Note** **Troubleshooting:** If you see error "No export named cid-CidExecArn found" during stack deployment, make sure you have completed prerequisite steps. Alternative method to install dashboards is the [cid-cmd](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) tool. 1. Log in to your **Data Collection** Account. 1. Open up a command-line interface with permissions to run API requests in your AWS account. We recommend to use [CloudShell](https://console.aws.amazon.com/cloudshell). 1. In your command-line interface run the following command to download and install the CID CLI tool: ``` pip3 install --upgrade cid-cmd ``` If using [CloudShell](https://console.aws.amazon.com/cloudshell), use the following instead: ``` sudo yum install python3.11-pip -y python3.11 -m pip install -U cid-cmd ``` 1. In your command-line interface run the following command to deploy the dashboard: ``` cid-cmd deploy --dashboard-id media-services-insights ``` Please follow the instructions from the deployment wizard. More info about command line options are in the [Readme](https://github.com/aws-solutions-library-samples/cloud-intelligence-dashboards-framework/blob/main/CID-CMD.md#command-line-tool-cid-cmd) or `cid-cmd --help`. ## Update Please note that currently dashboards can be initially deployed via CloudFormation but they cannot be updated through CloudFormation Stack updates. When new version of the dashboard template is released, you can update your dashboard by running the following command in your command-line interface: ``` cid-cmd update --dashboard-id media-services-insights ``` ## Dashboard Customization 1. Unleash your data creativity\$1 Dive into custom analysis by creating your own visuals from this dashboard. Follow our quick [guide](create-analysis.md) to get started. 1. To integrate CID with AWS Organizations for enhanced cost visibility across multiple accounts and organizational units follow the [documentation to add taxonomy details](add-org-taxonomy.md) 1. To set up cost allocation tags for better resource tracking and cost attribution across your media services, follow the [Cost Allocation Tags documentation](https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html) ## Usage Guide There are multiple tabs available in this dashboard. **Example** Start with the Executive Summary to get a high-level view of your media services spending and usage patterns. This tab provides: + Total media services costs and month-over-month trends + Service-wise cost breakdown and utilization metrics + Top spending accounts and regions + Cost per service comparison and growth trends + Key performance indicators and cost optimization opportunities + Regional distribution of media services usage + Monthly cost forecasting and budget tracking Monitor live video transport costs and connection performance: + Connection usage patterns and data transfer volumes + Cost breakdown by connection type and region + Bandwidth utilization and peak usage analysis + Source and destination flow analysis + Data transfer cost optimization opportunities + Connection uptime and reliability metrics + Regional cost comparison for optimal placement Track transcoding job costs and queue performance: + Job processing costs by queue and priority + Queue utilization and processing time analysis + Input/output format cost comparison + Reserved capacity utilization and recommendations + Job failure rates and retry costs + Processing time trends and optimization opportunities + Cost per minute of content processed + Peak usage periods and capacity planning Analyze live streaming costs and channel utilization: + Channel costs by type and configuration + Input/output bandwidth utilization + Reserved instance vs on-demand cost analysis + Channel uptime and availability metrics + Regional deployment cost comparison + Encoding profile cost optimization + Redundancy configuration cost impact + Peak concurrent channel usage Review packaging and origination costs: + Endpoint usage and request volume analysis + Content delivery cost breakdown + Origin request patterns and caching efficiency + Packaging format cost comparison + Regional endpoint performance and costs + Content protection and DRM costs + Harvest job costs and optimization + CDN integration cost analysis Examine ad insertion costs and session analytics: + Session volume and ad request patterns + Personalization costs and revenue impact + Configuration usage and optimization + Ad decision server integration costs + Content delivery network costs + Session duration and engagement metrics + Revenue per session analysis + Peak traffic handling and scaling costs ## Cost Optimization Recommendations There are a several ways to optimize your Elemental costs. Below are some of them. **Example** + Purchase MediaLive reserved instances for predictable live streaming workloads (up to 75% savings) + Consider MediaConvert reserved capacity for consistent transcoding volumes + Analyze usage patterns to determine optimal reservation terms (1-year vs 3-year) + Monitor reservation utilization and adjust capacity as needed + Review MediaLive channel configurations and encoding profiles + Optimize MediaConvert job settings for cost-effective processing + Implement appropriate redundancy levels based on content criticality + Use efficient encoding presets to reduce processing time and costs + Leverage CloudFront for global content delivery and reduced origin costs + Place MediaConnect flows and MediaLive channels in optimal regions + Implement efficient caching strategies for MediaPackage endpoints + Use VPC endpoints to reduce data transfer costs between services + Implement automated scaling for MediaLive channels based on demand + Use MediaTailor’s server-side ad insertion to reduce CDN costs + Monitor and optimize MediaPackage harvest jobs scheduling + Implement proper content lifecycle management to reduce storage costs + Set up cost anomaly detection for unusual spending patterns + Create budget alerts for each media service + Monitor service-specific metrics to identify optimization opportunities + Regular review of unused or underutilized resources ## Authors & Contributors + Krutarth Doshi, Sr. Technical Account Manager + Eric Christensen, Sr. Technical Account Manager + Ala Muhtaseb, Sr. Solutions Architect + Imane Zeroual, Sr. Cloud Operations Architect + Guillaume Girault, Technical Account Manager ## Feedback & Support Follow [Feedback & Support](feedback-support.md) guide Have a success story to share with the Team, suggest an improvement or report an error? + Please email: [cloud-intelligence-dashboards-media-services@amazon.com](mailto:cloud-intelligence-dashboards-media-services@amazon.com) **Note** These dashboards and their content: (a) are for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS content, products or services are provided "as is" without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers.