Macroeconomic uncertainty is changing how organizations think about cost, and encouraging teams and SREs to consider both scalability and efficiency when deploying and managing resources. But understanding the true cost of an application, service, or team is a significant challenge—cloud billing data is hard to allocate, especially across multiple providers. It’s also isolated from where engineers work and, most importantly, is disjointed from application and infrastructure performance information. That’s why teams need ways to easily contextualize cost with metrics to better understand which applications are most efficient and which are contributing to wasted cloud spend. In this session, you’ll learn how you can use Datadog Cloud Cost Management to deliver cost data where engineers work. By combining this data with resource-level context, such as CPU and memory usage and request throughput—all easily scoped to their services and applications—your teams can take the appropriate action and spend effectively.