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Dimensions, labels, and tags

Dimensions are attributes or categorical variables that describe or add context to quantitative data. Labels and tags are key-value pairs that are used for identifying, organizing, and grouping resources. Dimensions, labels, and tags serve similar purposes in Cloud Analytics. They help you break down your cloud spend and build a granular view of your data, making it easier to identify trends, patterns, or relationships.

Note

This page mainly covers dimensions, labels, and tags when the data source is Billing data. For reports with BigQuery Lens as their data source, see Analyze BigQuery activities using audit data: Metrics and dimensions.

Overview​

Cloud Analytics supports a variety of dimensions, labels, and tags, grouped into multiple sections.

Dimensions​

In the DoiT console, dimensions are grouped into the following sections:

  • Recent: The three most recent dimensions you selected when building a report.

  • Popular: The most chosen dimensions in reports.

  • Standard: This section contains dimensions such as logical groupings of resources (e.g., accounts, projects), resource metadata, and dimensions about costs, credits, and discounts.

  • Attribution groups: All the available attribution groups that you can use to distribute the data collected for a particular metric. For example, to split unallocated costs.

  • Google Kubernetes Engine: See Google Kubernetes Engine dimensions.

  • Date/Time: The Date/Time dimensions are related with the report setting Time Interval. When creating a new report, the Year, Month, and Day dimensions are added by default.

Labels and tags​

Labels and tags can be user-defined or generated by cloud providers or DoiT. In the DoiT console, you will see labels and tags in the following sections:

  • Labels: This section includes AWS cost allocation tags, Google Cloud labels, Azure tags assigned to resources (no resource group tags), Snowflake QUERY_TAG, Datadog tags, and custom labels defined in the DataHub API.

  • System labels: Labels systematically generated by DoiT and data providers.

  • Project Labels (Google Cloud specific): Labels set on the Google Cloud project level.

  • GKE Labels: See Analyze GKE cost.

  • GCP Tags: Google Cloud tags are resources attached to other resources for cost allocation analysis or fine-grained access control. See Tags overview .

  • AWS Organization tags: Organization tags are custom attribute labels that you can use to track AWS resources across your organization's accounts.

See also

  • Service: The name or short description of the service that the usage is associated with. A service is the high-level type of cloud technology that can be broken down into SKUs. See also Service ID.

    For Microsoft Azure, the Service dimension maps to the cost details field MeterCategory, which is the name of the classification category for the meter. For example, Cloud services and Networking.

  • SKU: A description of the resource type used by the service. A SKU (Stock Keeping Unit) is the resource itself for which there's a given Price Per Unit. See also SKU ID.

    For SKU prices, check the pricing pages of the corresponding service providers, for example, AWS Cloud Services Pricing and prices for Google's cloud services. Azure SKU descriptions map to the cost details field MeterSubCategory.

  • Provider: Data providers. For example: Amazon Web Services, Google Cloud, Microsoft Azure, Snowflake, and Datadog. If your data source includes DataHub data, this dimension also identifies the provider of the ingested data.

  • Project/Account ID: See also Hierarchy groups.

Standard​

Hierarchy groups​

  • Billing Account: This is your billing account ID in the DoiT Platform.

    • Amazon Web Services: Your DoiT customer ID if you're on a Dedicated payer account, or your CloudHealth account ID and account name if you're on a Consolidated billing account.

    • Google Cloud: Your Google Cloud Billing account ID and account name. You can also find this information on the DoiT console's Assets page or the Google Cloud console's Manage Billing Accounts page.

    • Microsoft Azure: The unique identifier for your Azure subscription. It maps to the cost details field SubscriptionId. You can also find the Subscription ID on the DoiT console's Assets page.

  • Folder: Folders are nodes in the Google Cloud resource hierarchy. A folder can contain projects, other folders, or both.

    When using the Folder dimension, make sure to include the folders that are parents of the target projects. For example, to view the costs of a folder and all its nested folders, you can use the regexp /{ORG_ID}/{FOLDER_ID}/(/[0-9]*)+ as the filter; selecting /{ORG_ID}/{FOLDER_ID}/ will return only the direct cost of the top-level folder.

  • Project/Account name:

  • Project/Account number: For Google Cloud, this is the automatically generated project number.

Resource metadata​

  • Resource: An identifier of the resource that generated relevant usage. This dimension can be used to list individual virtual machines or Identify granular cost data by service.

    • Amazon Web Services: The ID of the resource that you provisioned. For an Amazon EC2 compute instance, this field contains the instance ID. See AWS Cost and Usage Reports Line item details: lineItem/ResourceId and Resource IDs for more information.

    • Google Cloud: Derived from the resource.name field in the detailed usage cost data export. It contains the name provided by the user. For a Compute Engine virtual machine (VM) instance, this field contains the instance name of the VM. For example, projects/{PROJECT_ID}/instances/{INSTANCE_NAME}.

    • Microsoft Azure: Unique identifier of the Azure Resource Manager resource. It maps to the cost details field ResourceId and is the fully qualified ID of the resource, including the resource name and resource type.

    • Snowflake: Unique identifier of a Snowflake resource, for example, compute resources (virtual warehouse for query processing), storage (managed structured and semi-structured data), access control (roles, users, and privileges). See Snowflake.

  • Service: The name or short description of the service that the usage is associated with. A service is the high-level type of cloud technology that can be broken down into SKUs. Azure Service maps to the cost details field MeterCategory, which is the name of the classification category for the meter. For example, Cloud services and Networking.

  • Service ID: The identifier of the service that the usage is associated with. See also Service.

    For Microsoft Azure, the Service ID dimension maps to the cost details field MeterId.

  • SKU ID: The identifier of the resource used by the service. See also SKU, AWS Cost and Usage Reports Product details: product/sku, and Google Cloud SKUs. For Microsoft Azure, SKU IDs map to the cost details field ProductId.

  • Marketplace: This dimension helps distinguish between services purchased from Marketplace and services provided by cloud providers. See Marketplace expenses for an example.

  • Global Resource (Google Cloud specific): A globally unique Google Cloud service identifier for the resource that generated relevant usage. This dimension is based on the resource.global_name field in the Google Cloud Billing detailed usage cost data export.

    • For a Compute Engine virtual machine (VM) instance, this field contains the instance ID of the VM and is a unique numeric string assigned by Google Cloud. For example, //compute.googleapis.com/projects/{PROJECT_ID}/zones/{ZONE}/instances/{INSTANCE_ID}.

    • For Cloud Storage, the first full day of granular cost data is February 13, 2024. See GCS Cost by Bucket for an example of viewing granular Cloud Storage bucket-level cost data.

    Note that not all resources have an identifier. Resources without Global Resource identifiers are shown as Global Resource N/A in Cloud Analytics reports. See also Identify granular cost data by service.

  • Operation:

    • Amazon Web Services: The specific AWS operation that generated relevant usage. For example, a value of RunInstances indicates the operation of an Amazon EC2 instance.

    • Microsoft Azure: The name for the meter. It maps to the cost details field MeterName.

Credits and discounts​

The dimensions below help you view and analyze your costs, credits, and discounts.

  • Cost Type: The type of charge. Cost types are defined by cloud providers and DoiT. Note that DoiT recalculates billing data from cloud providers to factor in DoiT discounts, custom pricing, Flexsave, and other items when applicable.

    Tip

    Unless stated otherwise, this section describes cost types as measured in the Cost metric.

    Cost types relevant to Amazon Web Services:

    • BundledDiscount: A usage-based discount of a service or feature based on the usage of another service or feature.

    • Credit: DoiT promotional credits and any credits that AWS applied to your bill.

    • DiscountedUsage: For the Cost metric, this item is always 0; for the Usage metric, it shows the usage of any instances covered by your own Reserved Instances (RI).

    • EDP: AWS Enterprise Discount Program (EDP).

    • Fee: EDP on upfront charges and exchange charges that you paid for RIs.

    • Flexsave: Savings generated by DoiT Flexsave AWS. Valid for consolidated resold accounts.

    • FlexsaveCoveredUsage: The on-demand cost of Compute and SageMaker covered by Flexsave. Flexsave covered usage items are offset by the corresponding Flexsave negation items. This and the following Flexsave items are valid for dedicated resold accounts.

    • FlexsaveNegation: The Compute savings and SageMaker savings generated by Flexsave.

    • FlexsaveRecurringFee: Recurring charges related to Flexsave Savings Plans. The Flexsave recurring fee is always 0 for the Cost metric.

    • FlexsaveRIFee: The monthly recurring fee for Reserved Instances (RI) attached to your organization by Flexsave. You incur this cost only when the RI utilization is above 50%.

    • FlexsaveRefund: The refund for RIs attached to your organization by Flexsave. You get a refund when the RI utilization is below 50%.

    • FlexsaveManagementFee: Administrative fees charged by DoiT for the Flexsave for RDS service.

    • FlexsaveUsage: The rate for DB instances covered by Flexsave. Due to an known issue, savings generated by Flexsave for RDS are currently attached to the cost type FlexsaveManagementFee when the metric is Savings.

    • RIFee: The monthly recurring charges for your own Partial Upfront RIs and No Upfront RIs. The RI fee is charged on the first day of each month.

    • RiVolumeDiscount: Amazon EC2 Standard Reserved Instance Volume Discounts applied to your bill.

    • PrivateRateDiscount: Private Pricing Agreement (PPA) discounts applied to your bill.

    • Refund: Negative charges applied to your bill.

    • SavingsPlanCoveredUsage: Any on-demand cost that is covered by your own Savings Plan. Savings Plan covered usage items are offset by the corresponding Savings Plan negation items.

    • SavingsPlanNegation: Any offset cost through your Savings Plan benefit that's associated with the corresponding Savings Plan covered usage item. See AWS Savings Plans line items.

    • SavingsPlanRecurringFee: Any recurring hourly charges that correspond with your No Upfront or Partial Upfront Savings Plans.

    • SavingsPlanUpfrontFee: Any one-time upfront fee from your purchase of All Upfront or Partial Upfront Savings Plans.

    • SppDiscount: AWS Solution Provider Program discount. This item is valid only if you do not purchase AWS from DoiT and you have AWS activate or migrate credits.

    • Tax: Taxes that DoiT applied to your bill based on your billing profile.

    • Usage: Usage charged at AWS On-Demand Instance rates.

    Cost types relevant to Google Cloud:

    Cost types relevant to Microsoft Azure: The cost types listed below correspond to the cost details field PricingModel.

  • Credit: AWS credits, DoiT promotional credits, and Google Cloud's credits such as Committed Usage Discount, sustained Usage Discount, or Free tier discount.

  • Savings Type (AWS specific): This dimension is used together with the Savings metric. It allows you to view your savings accrued on AWS through your relationship with DoiT across various pricing programs. You can monitor the savings generated by DoiT Flexsave, Enterprise Discount Program (EDP), and Private Pricing Agreement (PPA).

See also

System labels​

System Labels are systematically generated by DoiT and data providers (AWS, Google Cloud, Microsoft Azure, and Snowflake).

Note

Most of the system labels generated by DoiT or Google Cloud are automatically replaced with a short name or alias once selected. Other labels are not assigned any alias and stay the same whether selected or not.

By DoiT​

  • cmp/commitment_type (alias: CUD Type): Commitment types. Examples: General purpose N1 commitments, Compute-optimized C2 commitments.

  • cmp/compute_resource_name (alias: GCE Resource): Google Compute Engine resource names. Examples: CPU, memory, extended memory.

  • cmp/eligible_for_commitment (alias: CUD Eligible): Workloads eligible for committed use discounts (CUDs).

  • cmp/flexsave_eligibility: Flexsave eligibility of AWS workloads. See Flexsave coverage for its application in the preset report.

  • cmp/machine_type (alias: Machine Type): Machine types. Examples: C2 Compute-optimized, E2 General-purpose.

  • cmp/memory_to_core_ratio (alias: GB/CPU): The amount of memory (RAM) per CPU core.

  • pricebook/rule_name: The rule name defined in the price book. It helps identify the specific rule applied to a given resource and understand the context of the applied pricing structure. For example, choosing the rule name EDP allows you to analyze your AWS Enterprise Discount Program contract pricing. See AWS Enterprise Discount Program (EDP) analysis for its application.

  • pricebook/rate_value: The applied discount rate to your AWS resources. For example, a 7% EDP will be displayed as 0.93.

By Google Cloud​

  • compute.googleapis.com/cores (alias: Cores): The number of vCPUs available to the virtual machine.

  • compute.googleapis.com/memory (alias: Memory): The amount of memory (in GB) available to the virtual machine.

  • compute.googleapis.com/machine_spec (alias: Machine Spec): The machine types for your VMs.

  • compute.googleapis.com/is_unused_reservation (alias: Unused Reservation): Unused zonal reservations.

See also

Google Cloud Docs: Available system labels

By AWS​

This section highlights AWS system labels that are of particular interest when analyzing AWS cost and usage data.

  • aws/item_desc: The description of the line item. For example, the type of usage incurred during a specific time period.

    You can use this label to check discounts or rates of your AWS support plans. See AWS support plan charges.

See also

Columns in AWS Cost and Usage Reports (AWS CUR): Data dictionary

By Microsoft Azure​

Azure system labels in the DoiT console are mapped from the cost details fields. Below is a non-exhaustive list of available Azure system labels:

  • azure/charge_type: Indicates whether the charge relates to Usage, a Purchase, or a Refund. See Azure usage, purchases, and refunds for an example report.

  • azure/ReservationId: Unique identifier for the purchased reservation instance.

  • azure/ServiceInfo: Service-specific metadata.

  • azure/product_order_name: Unique name for the product order.

  • azure/publisher_name: The name of the publisher.

  • azure/service_family: Service family that the service belongs to.

  • azure/subscription_name: Name of the Azure subscription.

  • Labels mapped from the AdditionalInfo field: Service-specific metadata. For example, an image type for a virtual machine.

By Datadog​

See System labels by Datadog.

By OpenAI​

See System labels by OpenAI.

By Snowflake​

See System labels by Snowflake.

Data ingestion limits​

To ensure optimum performance, the DoiT console limits the maximum number of values it can store and load on a user's browser to 5,000 per dimension/label. Values beyond the limit are not visible when editing reports.

Suppose your environment has over 5,000 resources, regardless of their types (S3 buckets, EC2 instances, etc.). If you use the Resource dimension to filter results, you'll notice that only the first 5,000 resources (in alphabetical order) are available.

In such a case, you can use the Advanced option to add a regular expression to include the desired values. If you're looking for a specific value, you can also click + to add the exact value to the filters.

Add a new filter

See also​

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