Datadog Cloud Cost Management

About Datadog Cloud Cost Management

Datadog Cloud Cost Management is a comprehensive cost observability solution that unifies engineers and FinOps practitioners in a single platform. By integrating cloud cost data with real time performance telemetry, the platform eliminates barriers between finance and engineering teams, enabling collaborative optimization and waste reduction. The solution ingests billing data from AWS, Azure, and Google Cloud, transforming it into metrics that can be analyzed alongside infrastructure utilization data.

The platform provides granular visibility into cloud spending across multiple dimensions including accounts, services, tags, and resource types. Users can break down costs to the individual resource level and correlate spending changes with performance metrics to identify root causes of cost anomalies. Container Cost Allocation features extend this visibility to Kubernetes clusters, Amazon ECS, Azure, and Google Cloud workloads, providing pod level cost insights and identifying idle resource expenses.

Datadog Cloud Cost Management includes intelligent recommendations for cost optimization, such as identifying opportunities to migrate S3 objects to Intelligent Tiering or optimizing compute resources. The platform supports custom tag pipelines that correct missing or incorrect tags and add inferred tags aligned with organizational business logic. With 15 months of data retention, teams can perform historical analysis and track long term cost trends. The solution integrates seamlessly with Datadog dashboards, monitors, notebooks, and the Service Catalog, embedding cost data directly into existing engineering workflows.

Key Features

• Unified Cost Observability: Correlate cloud costs with real time infrastructure metrics, traces, and logs to understand how performance changes impact spending.
• Container Cost Allocation: Gain visibility into costs associated with clusters and workloads across Kubernetes, Amazon ECS, Azure, and Google Cloud including pod level expenses and idle resource identification.
• Cloud Cost Recommendations: Receive actionable optimization suggestions such as S3 storage class migrations and compute right sizing based on actual usage patterns.
• Tag Management and Cost Allocation: Create tag pipelines to correct missing tags, add inferred tags, and allocate spend across teams, services, or environments with flexible attribution rules.
• Cost Anomaly Detection: Proactively manage spending with Cloud Cost Monitors that alert on cost changes or threshold breaches with actionable context.
• 15 Month Data Retention: Access historical cost data for long term trend analysis, budgeting, and strategic planning with 15 months of metric retention.
• API and Programmatic Access: Export cost data via the Metrics API for integration with external financial systems or custom analysis tools.
• FinOps Collaboration Tools: Use Datadog Notebooks to combine cost data, performance graphs, and recommendations in collaborative workspaces shared between finance and engineering teams.