Datadog Cloud Cost Management

Get clarity on your total cost of service ownership by ingesting costs across cloud, SaaS providers, and custom costs in FinOps FOCUS format.

Use automated recommendations to optimize spend across resources including containerized environments.

Engineers see costs scoped to teams, products, services, and applications in their daily workflows—Dashboards, Service Catalog, Profiling, and more.

See costs alongside observability data to understand the impact cost changes will have on performance, making costs a key KPI for engineering teams.

Understand Your Total Cost of Service Ownership in a Single Platform

Instantly understand the total cost of services running on AWS, Azure, or Google Cloud, as well as SaaS providers like Snowflake, Databricks, MongoDB, and more
Upload any cost data source in FinOps FOCUS format to Datadog so all costs are accounted for
Attribute costs to specific products, services, and teams to identify the biggest cost changes; drill down to resource-level spend, and make decisions with high confidence
Use Tag Pipelines for seamless cost allocation across cloud resources

Available with: Container Monitoring in AWS, Google Cloud, and Azure

Eliminate container cost uncertainty by seamlessly breaking out costs by cluster, namespace, or pod and across workload usage, workload idle, and cluster idle
Automatically distribute spend by any logical grouping or dimension within Kubernetes, down to the individual pod
Minimize costs by spotting cloud registries that you may be paying for but not actively using, as well as images that are taking up unnecessary disk space in your hosts

Enable teams to take ownership of the costs of their services and applications by surfacing costs in dashboards, Powerpacks, notebooks, and the Service Catalog
Cut through the noise with customizable cost, performance, and unit economic monitors to rapidly respond to unexpected cost changes
Eliminate silos between FinOps and engineering teams by reviewing recommendations and collaborating on cost initiatives with shared dashboards and notebooks
Combine cost data with performance metrics to build service-specific unit economics and easily reduce unnecessary compute, storage, or data-transfer costs

Optimize resources using recommendations that Datadog automatically generates by combining observability data with underlying provider billing data
Review recommendations in dashboards, the Service Catalog, Powerpacks, and more, ensuring that costs are always in front of your teams
Easily identify and terminate orphaned resources, migrate legacy resources, and rightsize underutilized or over provisioned resources