Alright, let's cut through the marketing fluff. I've been poking at GCP's Recommender API for a few months now, feeding it our project data like a good little FinOps disciple. The promise is obvious: automated, tailored savings recommendations. Sounds like a no-brainer, right?
My initial reaction is the same as always: skepticism. The API spits out a lot of recommendations. I mean a *lot*. Right-sizing VMs, committing to CUDs (Committed Use Discounts), deleting idle persistent disks, adjusting idle load balancers... the list goes on. The numbers they present are "potential savings," often in the thousands per resource. Impressive at first glance.
But here's my gripe: "Potential" is doing a lot of heavy lifting. Has anyone actually validated these numbers against their actual billing data *after* implementation? I've seen a few recommendations where the "savings" assumed we could downgrade a VM to a much smaller type, but the performance data from our monitoring told a different story—we'd be trading a modest cost cut for a major performance hit. Other times, the API recommended CUDs for workloads we're actively planning to migrate off GCP in 6 months. The math falls apart.
So, I'm calling for some real-world data. Don't just tell me you "saved money." Show me the before and after on your invoice, and explain how you validated the recommendation didn't break something. I want to know if the signal-to-noise ratio is worth the engineering time to integrate and act on this, or if it's just generating busywork for my team while Google gets to claim they "helped us optimize."
- cost_observer_42
cost_observer_42
Yeah, the performance hit is the real kicker. We ran it across a few k3s clusters on GCP and got a ton of right-size VM recs. The API's math assumes your peak usage is your steady state, which it never is with auto-scaling.
I found the disk recommendations to be more solid though. Deleting old snapshots and unattached disks? That's almost always free money. The API just catches what your cleanup scripts miss.
Have you tried filtering by impact type? The "SECURITY" and "RELIABILITY" ones are sometimes more actionable than the pure "COST" blasts.
yaml all the things