Join an enablement webinar session
Explore your cloud provider costs and correlate them with real-time telemetry data. Gain actionable insights and alerts on where your cloud costs are coming from, how they are changing, and where to find potential optimizations.
Cloud Cost Management provides insights for engineering and finance teams to understand how infrastructure changes impact costs, allocate spend across your organization, and identify inefficiencies.
Datadog ingests your cloud cost data and transforms it into metrics you can use in a search query on the Explorer page. If costs rise, you can correlate the increase with usage metrics to determine the root cause.
To start managing your cloud costs with Cloud Cost Management, see the following documentation.
Visualize infrastructure spend alongside related utilization metrics with a retention period of 15 months to spot potential inefficiencies and savings opportunities.
When creating a dashboard, select Cloud Cost as the data source for your search query.
Optionally, you can programmatically export a timeseries graph of your cloud cost data by using the Metrics API.
Visualize daily Datadog spending alongside related utilization metrics with a retention period of 15 months to spot potential inefficiencies and savings opportunities.
When creating a dashboard, select Cloud Cost as the data source for your search query.
Optionally, you can programmatically export a timeseries graph of your Datadog cost data by using the Metrics API.
Use Tag Pipelines to ensure comprehensive cost tracking by standardizing the tags across all cloud resources. This prevents any cost data from being overlooked.
You can create tag rules to correct missing or incorrect tags and add inferred tags that align with your organization’s business logic.
Proactively manage and optimize your cloud spending by creating a Cloud Cost Monitor. You can choose Cost Changes or Cost Threshold to monitor your cloud expenses.
Use Container Cost Allocation metrics to discover costs associated with clusters and workloads across Kubernetes, AWS ECS, Azure, and Google Cloud. Gain visibility into pod-level costs, identify idle resource costs, and analyze costs by resource type.
Additional helpful documentation, links, and articles:
