CostGoblin syncs your AWS billing data locally and queries it with DuckDB. No servers. No SaaS fees. Your data never leaves your machine.
Cloud cost visibility shouldn't be a finance-only perk. CostGoblin is a desktop app for anyone curious about their AWS bill — and especially the engineers, architects, and small teams who can act on what they see.
Delete the orphaned RDS instance. Right-size the cluster. Kill the forgotten NAT gateway.
No sales call. No cross-account IAM role. No annual contract.
Seven views, one local DuckDB. From raw line items to AI-driven Q&A — every dollar accounted for, every query in milliseconds.
Before setting up any exports, make sure the tags you want to slice costs by are activated in the AWS Billing Console → Cost Allocation Tags.
Activate any user-defined tag you plan to use as a dimension in CostGoblin (e.g. team, environment, service). Tags that aren't activated here won't appear in the CUR exports, no matter how they're configured.
Pick a dedicated bucket (or prefix) for all CostGoblin data. We recommend this structure so each export lands in its own namespace:
In the AWS Billing Console → Data Exports, create two exports. Select Cost and usage report (CUR) as the data table and configure each one as follows:
Under Column selection, enable these and disable the rest to keep file sizes small:
In the AWS Billing Console → Cost Optimization Hub → Preferences, enable the S3 data export:
Open CostGoblin, go to Sync and point each data source to its S3 prefix. Once the first sync completes, head to Dimensions to map your tags to cost allocation dimensions. This is where CostGoblin shines — for each dimension you can:
Automatic alerts when spending deviates from historical patterns. Catch surprises before the bill lands.
Set spending targets per team, product, or environment. Track burn rate against budget in real time.
Share dashboards and cost reports with your team. Collaborative triage for cost spikes.
GCP and Azure billing support alongside AWS. One interface for all your cloud spend.
New features, releases, and cloud cost insights. Low volume, high signal.