AWS tutorial: fleet-wide edge CV model lifecycle with SageMaker SDK v3, ~$0.07 per run
AWS ML Blog · rss · 2026-10-27
AWS ML Blog publishes an end-to-end tutorial for scaling visual quality inspection beyond PoC: 40 production lines, multiple cameras each, each needing its own fine-tuned model. The pattern uses a dual-branch SageMaker Pipeline (conv autoencoder for anomaly detection + fine-tuned ResNet18 classifier per camera), ONNX export, quality gates, and SageMaker Neo compilation for device-optimized artifacts, with SQS FIFO + Lambda + Step Functions + a DynamoDB semaphore pacing fleet training to 5 concurrent executions. Deployed via CDK; a full pipeline run on synthetic data costs $0.07. Sample is open-sourced in aws-samples, and the post flags SDK v3's modular packages, two undocumented breaking behaviors, CDK version requirements (≥2.1131.0), and multi-region env-var pitfalls.
More from Infra
- Sail equivalence proof and riscv-coq cross-checks uncover real RISC-V spec bugs — xennygrimmato_ · 2026-10-27
- xAI's Colossus 1 hits ~14.6 exaflops FP64, ~5x Top500 leader — cis_female · 2026-10-27
- Lambda runs 19 B200 nodes in a 16-node power budget, boosting throughput 24% — TheZachMueller · 2026-10-27
- Podcast: Micron's HBM roadmap, Meta's AI infra, and NVIDIA's supply chain lock-in — BenBajarin · 2026-10-27
- SGLang MegaKernel + PD Pushes the TCO-Latency Frontier on GB300, SemiAnalysis Benchmarks Show — AccBalanced · 2026-10-27
- Scaling self-hosted Convex: compiling TypeScript Convex functions to WASM — leventov · 2026-10-27