Hey everyone! I've been diving into cloud cost analysis at my new role, and I'm trying to wrap my head around the best path forward. We're using AWS and GCP, and the native billing exports are... a lot to handle manually. I'm excited to set up a proper system, but I'm stuck on a fundamental question.
I see amazing third-party tools out there like CloudHealth, Cloudability, or even open-source options like OpenCost. But part of me wonders if we should just build our own aggregator using BigQuery/Cloud SQL and some Looker dashboards. We have the analytics skills in-house, but I don't want to underestimate the effort.
Could you share your experiences? I'm especially curious about:
* **Long-term maintenance**: For those who built custom solutions, how much ongoing engineering time does it really eat up for new cloud services or API changes?
* **Hidden costs**: Beyond the SaaS subscription, what are the less obvious pros/cons of third-party tools? I've heard some are great for showback/chargeback but maybe less flexible.
* **Core features**: What are the must-have features you'd want in either approach? I'm thinking things like anomaly detection, RI/SP coverage tracking, and tagging enforcement.
I'm leaning towards a third-party tool to get started quickly, but I'd love a detailed walkthrough of what we might be signing up for—both in terms of cost and lock-in. Any beginner-friendly recommendations or lessons learned would be super helpful!
I'm a cloud engineer at a 120-person SaaS company, and we manage costs for a hybrid AWS and GCP environment. We ran a custom-built tool for about a year before switching to a third-party platform.
**Upfront and ongoing engineering cost**: A custom solution needs about 3-4 weeks of initial dev work for basic pipelines and dashboards. The real cost is maintenance, which ate 6-8 engineering hours monthly to handle API changes, new service mappings, and pipeline bugs.
**Total cost of ownership**: Our third-party tool (CloudHealth) costs roughly $70k annually. Building our own seemed cheaper, but when we factored in 8-10 hours a month of our $120k engineer's time, it was nearly a wash, and we lost the pre-built features.
**Feature gap and time-to-value**: With a third-party tool, we had RI/SP recommendations and anomaly alerts on day one. Building those ourselves would have taken another 2-3 months of development. The custom tool only showed past spend; it couldn't recommend actions.
**Flexibility vs. standardization**: Our custom BigQuery setup let us model costs exactly how we wanted for our weird Kubernetes setup. The third-party tool is less flexible; we had to adjust some of our tagging to fit its schema for accurate chargeback.
I'd recommend starting with a third-party tool, especially if your main goal is getting control and recommendations fast. The only reason to build is if you have a very unique cost structure that commercial tools can't model. For a clean call, tell us your team's size and if your spend has any unusual patterns, like heavy custom discounts or a lot of container spend.