Building IoT platformPrimustech, 2026 · Case study
Cutting cloud spend by ~15%
Measured first, then cut monitoring, database and compute, with every trade-off written down.
- cloud spend cut, with no alert dropped
- ~15%
- orphaned Kafka topics reaped, 86% of all topics
- 914
- samples per scrape from the Kafka exporter
- 10,386 → 2,891
A small working model of the real system. Press the buttons.
The problem
Nobody had measured where the money went. Managed Prometheus alone was about US$106 a month, the third-largest line item, and climbing with no matching growth in traffic.
What I did
- 1
Traced the metric bill to 914 orphaned Kafka topics, 86% of all topics, and shipped a scheduled reaper. Samples per scrape from Kafka fell from 10,386 to 2,891.
- 2
Dropped three metric packages that no alert or dashboard used, a 40% cut in samples per scrape, and kept cAdvisor because three memory alerts depend on it.
- 3
Right-sized Cloud SQL from 4 vCPU/16 GiB to 2 vCPU/12 GiB and moved it from regional HA to zonal, with the recovery trade-off documented.
- 4
Cut Core API pod requests from 1 CPU/4 GiB to 0.5 CPU/3 GiB so pods pack onto fewer nodes, and retired a replaced ingestion lane end to end.
Cut cloud spend by about 15%, without dropping a single alert.
Stack
- Managed Prometheus
- Kafka
- Kubernetes CronJob
- Cloud SQL
- GKE autoscaling
- Terraform