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52 lines
1.8 KiB
Markdown
52 lines
1.8 KiB
Markdown
# Google Cloud Run example
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End-to-end deployment + smoke for [`@hyperframes/gcp-cloud-run`](../../packages/gcp-cloud-run) — the Cloud Run + Cloud Workflows adapter for HyperFrames distributed rendering.
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## Layout
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```
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scripts/smoke.sh Real-GCP smoke: build → deploy → render → PSNR → destroy
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sample-events/ Example request bodies for the Cloud Run handler
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(plan.json, render-chunk.json, assemble.json)
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```
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The Terraform module and the Cloud Workflows definition that the smoke deploys live with the package, at `packages/gcp-cloud-run/terraform/` (including `workflow.yaml`).
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## Prerequisites
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- `gcloud` authenticated, with a project that has **billing enabled**
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- `terraform` (≥ 1.5), `docker`, `ffmpeg`, `jq` on PATH
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## Run the smoke
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```bash
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# Renders the mp4-h264-sdr fixture through the workflow and PSNR-compares it
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# against the in-process baseline, then tears the stack down.
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./scripts/smoke.sh --project YOUR_GCP_PROJECT --region us-central1
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# Keep the stack up to poke at it:
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./scripts/smoke.sh --project YOUR_GCP_PROJECT --keep-stack
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# Render at several chunk sizes to see the fan-out scaling:
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./scripts/smoke.sh --project YOUR_GCP_PROJECT --chunk-sizes 30,15,10
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```
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Outputs land in `scripts/gcp-smoke-artifacts/`: `results.json`
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(`chunkSize × wallClockMs × psnrAvgDb`), the rendered MP4s, and each
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workflow execution's describe output.
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## Test the handler locally
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The sample events exercise the same body shape Cloud Workflows sends. With the
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container running locally (`PORT=8080`) and credentials that can reach a GCS
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bucket, you can drive a single action:
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```bash
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curl -sX POST localhost:8080/ \
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-H 'content-type: application/json' \
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--data @sample-events/plan.json | jq .
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```
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Replace the `PROJECT` placeholder bucket names and `REPLACE_WITH_PLAN_HASH`
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with real values from a prior `plan` response.
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