Every dollar you spend on DigitalOcean, from Droplets to inference, in one FinOps view

Bring DigitalOcean cost and usage into the same reports, allocations, and budgets you already run for AWS, Google Cloud, Azure, and Oracle Cloud, with GPU Droplets and Inference Engine spend landing in GenAI Intelligence.

DigitalOcean is often the cloud often not being as closely monitored by the FinOps teams as AWS or Azure. An engineering team spins up a few Droplets, a Kubernetes cluster, a managed database, and pays for it on a card. Call it $18,400 a month, a rounding error next to the AWS bill. Until now, getting any of that next to the rest of your cloud costs meant exporting a CSV and manually importing it to the DataHub in Cloud Intelligence™.

Starting today, you can now connect a DigitalOcean organization to Cloud Intelligence™ directly from Integrations, and it covers both sides of the bill: the infrastructure and the AI, accuretly mapped to Tokenomics spec.

What you get

Cost and usage for the whole DigitalOcean organization, pulled daily through DigitalOcean's Billing Insights API and broken down by the DigitalOcean team that incurred it. Droplets, Kubernetes, App Platform, Managed Databases, Spaces, Volumes, Load Balancers: every SKU arrives with the same dimensions as your other clouds, so the things you already use just work. Reports, allocations, budgets, forecasting, and anomaly detection treat a DigitalOcean team the same way they treat an AWS account or a Google Cloud project.

The AI side gets first-class treatment. DigitalOcean now sells AI at every layer, and each layer bills differently: GPU Droplets and Bare Metal GPUs by the GPU-hour, Serverless Inference and Batch Inference by the token across 70-plus models, Dedicated Inference by the GPU-hour on your own endpoint, Knowledge Bases by embedding tokens plus OpenSearch storage, Agent Platform by the tokens the agent and its guardrails process. Cloud Intelligence™ classifies those charges as AI spend and shows them in the GenAI Intelligence dashboard next to Amazon Bedrock, Vertex AI, OpenAI, and Anthropic, with the same GenAI dimensions for provider, product, and use case. If you moved an inference workload to DigitalOcean because the per-token rate beat the hyperscalers, you can now prove it in one report instead of two spreadsheets.

Get started

1. Connect your DigitalOcean organization from the Integrations page in Cloud Intelligence™.
2. Open the GenAI Intelligence dashboard to see GPU and inference spend alongside your other AI providers.
3. Add DigitalOcean teams to your allocations and budgets so showback and alerts cover them from day one.

DigitalOcean is available to all Cloud Intelligence™ customers with no extra configuration or plan change.