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AWS Cost & EC2 Right-Sizing

What the cloud lab costs to run — per range and at con scale — and why each node is the size it is. All prices are us-east-1 on-demand, Linux (list, mid-2026); your region/discounts will differ.

Right-sizing rationale

The lab looks heavy (31 services across the estate) but almost all of it is lightweight Python mocks. The only real compute is Ollama local inference on dev + ds (~5 tok/s at 2 vCPU); ml runs 13 mock services + a lightweight Ray scheduler; app/attack are proxies/tooling; the k8s node is a single-node k3s. So the sizing is driven by two facts:

  • Ollama is CPU-bound → dev + ds use c6i.large (non-burstable, guaranteed 100% CPU) so sustained multi-attendee inference never hits the t3 CPU-credit cliff.
  • Everything else is idle-light → ml drops from the original 4×-oversized t3.xlarge to t3.large; app/attack to t3.small; k8s to t3.medium.
  • ARM/Graviton is blocked — Weaviate and Qdrant ship x86-only binaries and ds needs both — so all nodes are x86. (Graviton would otherwise save ~20%.)
node instance vCPU / RAM disk $/hr why
ailab-dev c6i.large 2 / 4 20 GB 0.085 Ollama — non-burstable
ailab-ml t3.large 2 / 8 40 GB 0.083 13 mocks + Ray (down from t3.xlarge)
ailab-ds c6i.large 2 / 4 20 GB 0.085 Ollama + Weaviate/Qdrant (x86)
ailab-k8s t3.medium 2 / 4 30 GB 0.042 single-node k3s "ACME cluster"
ailab-app t3.small 2 / 2 20 GB 0.021 LangServe/Streamlit/A2A proxies
ailab-attack t3.small 2 / 2 20 GB 0.021 operator tooling + lab-listener
per range 6 nodes 12 / 24 150 GB ≈ 0.337 compute + 0.015 EBS = 0.35

Cost at scale

scenario cost note
1 range, running ~$0.35/hr ~$2.8 for an 8-hr workshop day
5 ranges, running ~$1.76/hr ~$14 / 8-hr day; ~$42 / 3-day con
5 ranges, left on 24/7 (month) ~$1,290/mo the real cost trap — never leave them running
5 ranges, STOPPED between events $0 compute pay only EBS ≈ $58/mo (or terminate + keep AMIs ≈ $6–12/mo)
testing / non-demo, Spot ~$0.12/hr/range stateless nodes tolerate Spot (~65% off)

The takeaways

  1. At con scale the dollar cost is trivial — ~$14/day for all 5 ranges. The lab is cheap to run.
  2. The only real cost risk is leaving instances running idle. Compute for a stopped EC2 instance is $0 — you pay only ~$0.80/mo of EBS per node. So between events, stop the ranges (aws ec2 stop-instances); after the con, terraform destroy.
  3. Right-sizing is roughly cost-neutral, not a saving — dropping ml t3.xlarge→t3.large funds the c6i upgrade on the two Ollama hosts. You buy predictable performance, not a smaller bill.
  4. The one big lever is the GPU tier — real inference (g5.xlarge ≈ $1.0/hr each) would multiply the bill, which is exactly why it stays an optional tier, off for the talk.
  5. Reset between waves is free — aws-reset-wave.sh restores from the baked lab-ready AMIs + re-seeds; the instances keep running, so there's no extra spend to reset the estate for a new wave.