MongoDB Cost Optimization
Cut your MongoDB bill from inside the cluster. OhChimp finds unused indexes, fragmented collections, and TTL gaps, verified on your real bill.
How does OhChimp connect to MongoDB?
With a database user that has the clusterMonitor role plus read access. OhChimp verifies the connection with serverStatus and listDatabases, then runs probe queries against catalog and statistics views (collStats, $indexStats, serverStatus). It uses readPreference secondaryPreferred so those queries land on a secondary where one exists and your primary stays clear.
Does OhChimp need write access or see my data?
No. OhChimp uses a read-only user and reads metadata and storage statistics through probe queries. It samples a small batch of documents per collection to map field names and types for schema waste, and it never stores your application documents, secrets, or workload contents.
What MongoDB costs can OhChimp actually reduce?
The main ones are unused indexes wasting disk and write throughput, fragmented collections that compaction can reclaim, TTL coverage gaps on growing collections, a cache hit ratio that shows the cluster is mis-sized, oversized databases ripe for archiving, and idle secondaries that let you downsize the primary.
Who applies the changes, and can they be rolled back?
You do. Each fix is a reviewable plan with a confidence score, a risk level, and rollback steps. Nothing changes until you click apply, and OhChimp applies the matching code and infrastructure changes together.
How are the savings verified, and how is it priced?
Against your real bill. A plan is marked VERIFIED only after 7 or more days, a drop of at least 10%, and 3 consecutive positive checks. Otherwise it stays flagged not implemented. Pricing is flat monthly, OhChimp never takes a cut of your savings, and paid plans carry a year-one ROI guarantee: a full refund of subscription fees if it does not pay for itself in the first 12 months.