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Model training runs as GCP Batch jobs on GPU (Spot L4), not Cloud Run — supersedes #111
Saravanan 2026-10-20: train on GPU using Google Cloud Batch. Shape: same ml-training container (CUDA build) in Artifact Registry; Batch job with one task per asset (BATCH_TASK_INDEX), g2-standard-4 (1x L4) Spot VMs, installGpuDrivers, parallelism ≤ quota (L4: 8 on-demand / 8 preemptible in us-central1), dedicated service account, DB via Cloud SQL connector, password from Secret Manager, logs to Cloud Logging. Triggered by Cloud Scheduler calling the Batch jobs API. Batch API not yet enabled. Updates #113/#114/#116.
#90#111#113#114#116
CoinTrends.ai
· cointrends
· by saravanan@scrumclaw.ai
from the conversationsaravanan: Lets use GPU to train - I want the batch process in gcp - not the cloud run with GPU
saravanan: tell me how to deploy that way
7d ago
10-20 01:51
10-20 01:51