New CloudHealth Experience

AI and Tokenomics Dashboard

The AI & Tokenomics dashboard is now available to all customers in the new CloudHealth experience. It provides a centralized, multi-cloud view of AI-related costs across AWS, Azure, and Google Cloud, helping teams identify cost drivers. Key information regarding AI model processing modes and cache usage help the FinOps team understand and influence and optimize model usage across the enterprise.

Key features of the dashboard include:

• Holistic Multi-cloud Visibility: The dashboard offers a consolidated view of model costs, token consumption, comparative cost per 1M token across all models in use and AI infrastructure costs (e.g. GPUs).

• Dynamic User Experience: Supports collapsible sections (with only the "Multicloud" section open by default) and conditional visibility, where sections or widgets are hidden if they lack relevant data for the user.

• Eight Default Widgets: Each widget is backed by a drill-down standard report and offers insights into spending:

  • Total Cost by Provider: Compares investments across AWS, Azure, and Google Cloud using stacked bar charts.

  • Total Cost by Subcategory & Service: Breaks down costs by infrastructure type (e.g., virtual machines) and specific service names.

  • Cost by Model: Highlights daily spend trends for individual foundational AI models.

  • Tokenomics: Compares the effective cost per one million tokens across models based on the previous day's usage.

To access the dashboard in the new CloudHealth experience, navigate to AI & Tokenomics from the left-hand menu. See the help documentation for more on the dashboard contents.

Multi-cloud FOCUS Cost and Usage reports

CloudHealth is excited to announce the multi-cloud FOCUS Cost and Usage Dataset and Standard Report, providing a consolidated and unified view of expenditures across AWS, Azure, and Google Cloud environments. By leveraging the FinOps Open Cost & Usage Specification (FOCUS) version 1.2 metadata mapping, the FOCUS Standard report ensures consistent and comparable multi-cloud analysis.

The dataset features a four-level service categorization structure:

• Level 1: Service Category (e.g., Compute)

• Level 2: Service Subcategory (e.g., Serverless compute)

• Level 3: Service Name (e.g., Lambda)

• Level 4: Service Items (e.g., “Lambda - Requests”), 

Please note, customers with multiple currencies enabled will see only partial data in the multi-cloud FOCUS Cost and Usage Dataset. A FOCUS Cost and Usage Dataset per cloud is also available. 

To access the Multi-cloud FOCUS Cost and Usage report, search for FOCUS under Reporting -> Reports. More details on the dataset is available in the Managing Reports documentation.

Data Connect for OpenAI

In order to support customers who transact directly with OpenAI, we are introducing a new branded Data Connect. By providing the organizationID and an API Key, customers can ingest OpenAI cost and usage data directly from OpenAI. A new Dataset and Standard Report - OpenAI Cost and Usage will be available after ingestion completes. 

Note that user level attribution is still in progress. OpenAI APIs support collecting the username field. This field is intentionally dropped at this time, while we work on building a toggle to allow you to turn it on and off. We do not want to introduce datasets that contain PII without giving the customer control to enable and disable it. User Name level reporting will be coming in a future release. 

Azure Smart Summary 

CloudHealth has extended its industry-leading Smart Summary capability to Azure. Using smart summaries, users may find what kind of usage makes up their cost, deltas, normalized cost and usage differences and unit costs. Drilling down on a smart summary takes you to the names of resources that make up the cost.

See the Smart Summary documentation for more details.

Key Performance Indicators (KPI) dashboard widget

CloudHealth has introduced a new KPI Widget type that allows you to aggregate any measure into a single number KPI. Customers can select any existing report, and choose up to two measures to aggregate. Supported aggregations include Sum, Average, Maximum and Minimum. These widgets can be placed on any dashboard. 

Customers can configure the report selection, time interval, primary and secondary measures, drill settings and comparisons using the configuration wizard after clicking the pencil icon on the widget.

GCP Rightsizing Recommendations 

CloudHealth announces the availability of Google Cloud rightsizing recommendations across a broad set of services, including Compute Instance, Compute Instance Group Manager, Compute Image, Compute Instance IP Address, Disk and CloudSQL Instances. Recommendations are categorized as Terminate, Downsize, Upsize, Autoscale or Optimize Configuration, depending on the service. Google Cloud Rightsizing Recommendations status (Active/Dismissed) is included. Support for perspectives to filter the recommendations, metrics visuals etc. are coming soon. 

 To collect recommendations from various Google Cloud Recommender APIs, the service account used for data collection must have Recommender Viewer access on each target project. Required IAM role: roles/recommender.viewer

For additional details, refer to the associated Help Center article.

Azure Database Savings Plan Recommendations

CloudHealth now supports the newly launched Azure Database Savings Plans within its optimization suite, extending beyond existing Compute Savings Plan recommendations. These Azure-native recommendations are seamlessly surfaced in the CloudHealth platform, enriched with enhanced visibility into key metrics such as coverage, utilization, expiration, and overall Effective Savings Rate.

In the CloudHealth New Experience, both AWS and Azure Savings Plans are unified within a single view, enabling organizations to evaluate commitment opportunities across clouds and prioritize actions based on highest return on investment (ROI). To access this capability, navigate to: CloudHealth New Experience > Recommendations > Commitment Discounts > Spend-Based Opportunities. For additional details, refer to the associated Help Center article.

Data Center Cost & Usage Now available as a Dataset

CloudHealth now brings Data Center cost history data into the new CloudHealth experience as a consumable dataset. Users can perform cross-technology scope analysis by combining public cloud, data center/private cloud, SaaS, and AI consumption data within a single view. All the measures and dimensions available in the Datacenter Machine Cost History Report will be available in the dataset “Datacenter Server Cost and Usage”.

The benchmark cost driver configuration continues to be available in the classic experience and can be adjusted from there.

For additional details, refer to the associated Help Center article. 

Realized Savings: Azure Support for Eliminated & Downsized Resources

CloudHealth has enhanced the quantification of realized savings from eliminated and downsized resources with expanded support for Azure services. Actions such as terminating or downsizing Azure resources - including Virtual Machines, Disks, Scale Sets, SQL Databases, and additional supported services - are now automatically reflected in the Eliminated Resources and Downsized Resources widgets. This enhancement provides greater visibility into the financial impact of Azure optimization actions driven by inefficiency, lifecycle state or business objectives, helping organizations better measure and track realized cost savings across their cloud estate

For additional details, refer to the associated Help Center article. 

Support for Azure Functions and Azure Function Apps

CloudHealth has expanded its asset inventory within the new experience to include support for Azure Functions and Azure Function Apps. Users can now gain visibility into these serverless resources by navigating to Explore > Assets and filtering for the Azure.AppService Inventory tab. These assets support missing tag policy and are categorizable in perspectives. 

UI Changes, Updates, and Fixes

UI Changes

• Default view in “Manage Dashboards” page is now the list view instead of card view

• In the Cost History filter panel, “clear” button will now work for perspective sections

• Removing all provider selections in filters will now show all providers (no filter is the same as selecting all options in a filter)

• Azure statement drilldown now contains the following columns: effective cost, region, resource name, consumed service

• Added filter for Change Reason to Smart Summary

Partner Improvements

• Sharing of saved reports through content package has been enabled

Bug Fixes

• Fix some cases where saving a dashboard would “shift” the layout

• Fixed header names for exported CSV, component/component_name are corrected to resource/resource_name for NX statement exports

• Fixed Change Reason column in Smart Summary exports to match UI cell values instead of exporting raw API enum values

Other Updates

• Tag Value Retention (When Tag Backlinking is OFF): Historical data will now only retain the latest tag value for each month. Users who track multiple tag changes within a month may see changes in historical data when costs are tracked across a tag value. This change does not affect reports where Tag Backlinking is enabled.

• Query Syntax Requirements (When Tag Backlinking is OFF): FlexQuery SQL queries must now include dataset aliases as a prefix for all column references. Error messages will guide users to correct queries that do not follow the new format.

  • Example: Old Query Format: Direct column references (e.g., `timeInterval_Month`) New Query Format: Must use alias (e.g., `awsCur.timeInterval_Month`)