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Check out what I made: A cost comparison dashboard for pre-Claw vs. post-Claw infra spending.

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(@jakes)
Estimable Member
Joined: 1 week ago
Posts: 74
Topic starter   [#14639]

Our “Cloud Cost Optimization” project started because I don’t trust vendor TCO slides. The forcing function was the new billing dashboard from our cloud provider—lots of green arrows, zero context.

We rebuilt the entire monitoring stack for this. Sequence:
* Ingested raw billing data via their API, tagged by team/project/env.
* Built a collector to pull performance metrics (latency, error rates, throughput) from our APM for the same services/timeframes.
* Correlated spend against performance, pre- and post-“Claw” migration.

Where it slipped: tagging consistency. Old infra wasn't tagged, so we had to backfill using deployment records and config management logs. Took two sprints longer.

Key takeaway: Our “optimized” post-Claw spend showed a 15% reduction. But for 20% of services, error rates doubled. The vendor's case study only mentioned the cost number.

Now we can see both.


Show me the methodology.


   
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(@elizabethb)
Trusted Member
Joined: 1 week ago
Posts: 46
 

Principal engineer at a fintech, 500 headcount. We run a mix of dedicated and serverless for payments processing, so I've done this dance with cost tools a few times.

**Accuracy vs. marketing slides:** Your 15% reduction with doubled errors is the rule. Every vendor TCO case study I've seen ignores performance regressions. Ours claimed 30% savings, actual was 12% with latency spikes for certain transaction types.
**Tagging hell is universal:** You said two sprints for backfill. For our legacy monolith, mapping untagged spend to teams via commit/deploy logs took six weeks of two engineers. The tools that auto-discover resources got about 60% right.
**Real pricing vs. listed:** Expect 2-3x the base platform cost for necessary integrations (like your APM pull) and historical data retention. One major vendor quoted us $15k/month, then the contract had a $0.05 per 1k API call fee for our own data, which added another $8k.
**Where it breaks:** Anomaly detection is mostly theater. It flags a spend increase, but never correlated ours with a matching traffic surge. You still need a person to know that 40% more spend on Tuesday was because of the product launch.

I'd build your own dashboard again. Vendor tools smooth over the inconvenient details. If you need a buy vs. build answer, tell us your team size for maintenance and whether finance needs to pull reports themselves.


—EB


   
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