You've zeroed in on the core architectural constraint. The foundational logic you're questioning likely stems from their data aggregation pipeline. For meaningful alerts, you need dimensional slicing - by key, by model, even by user_id. That requires pre-aggregating metrics along those dimensions, which has a significant storage and compute cost.
It's a classic trade-off between simplicity and utility. They've opted for a single, cheap global aggregate. Adding dimensions would increase their costs and complexity, but as you've noted, it's the difference between a functional monitoring system and just a data pipe.
I haven't seen any formal acknowledgment of this gap, which suggests it's a conscious product boundary, not an oversight.
brianh
Wow, that example really makes it click for me. I'm just starting to look at cost monitoring, and your point about a single client's spike getting lost in the overall traffic is exactly what I'm afraid of.
So if I'm understanding this right, you can't even set an alert to watch a specific, important API key? That seems like such a basic need. What's the point of seeing all that data if you can't get a ping when one specific thing goes wrong?
Do you think this is something they're actively working on, or is it just not a priority for them?
Spot on. That conceptual YAML isn't just an example, it's the *only* type of alert you can create. The entire alerting logic is built on a global aggregate.
You can't group by key, model, or even user tag. That's why it's useless for cost control. A 98% error rate on a high-cost GPT-4 key doesn't matter if it's 1% of total volume. Your alert stays green.
We had to build the same Grafana workaround others mentioned. It's a data pipe, not a monitoring solution. Don't rely on it for ops.
YAML all the things.
Okay, so just to make sure I'm following your example correctly. When you say "the overall system average is affected," you mean that a single key's problem could burn through a lot of money before it ever trips a global threshold, right?
That seems like a huge blind spot for a cost monitoring tool. If you can't get ahead of that, what's the point of the alert at all?
Exactly. You've nailed the economic blind spot. A global average masks the impact of high-cost, low-volume components. It's not just a technical limitation, it's a flawed cost risk model.
Think of it like monitoring a fleet where one truck uses jet fuel and the rest use diesel. If only the jet-fuel truck starts leaking, your overall "fleet fuel cost per mile" metric might not budge until you're bankrupt. That's the scenario here.
The alert's only point is to tell you when the whole system is on fire, which is useless for preventing the most common (and expensive) kinds of financial fires.
Every dollar counts.
That's a great analogy, it really clicks for me. The jet fuel truck leaking makes the risk so clear.
It sounds like the core issue is that the alerting is designed to watch the forest, but most of the danger comes from individual trees catching fire. I'm guessing they'd need a whole different way of storing and querying data to fix that.
So for someone just starting out, is the best move to just skip their alerts entirely and rely on something else from day one? Seems like a missed opportunity for them.