Cloud and SaaS spending continues to grow across teams, services, and providers, changing too quickly for retrospective cost management workflows to keep up. Finance and engineering leaders often rely on last month’s reports or manually maintained spreadsheets, which don’t reflect current usage. As a result, teams lack context on how spend is trending and often discover budget overruns only after they’ve occurred. AI spend is especially challenging to predict, with costs varying across providers and model tiers. A new workload or feature can shift a team’s spend trajectory in days rather than weeks.
Datadog Cloud Cost Management (CCM) includes budget forecasting to bring a forward-looking view of spend into the workflows that teams already use. Budget forecasting works on top of existing CCM budgets, combining cost data with machine learning–based forecasts to project what spend will be by the end of a period. Engineers and FinOps practitioners can track progress, receive alerts, and share updates with leadership from a single view.
In this post, we’ll explore how budget forecasting in CCM helps you:
Understand cloud cost trends with forecasts that reflect real billing patternsReview and compare actual and projected spend on the budget status pageStay proactive with alerts from budget monitorsShare budget and forecast insights via reports and dashboards
