* feat(gcp-cloud-run): add Google Cloud Run + Workflows distributed render adapter Adds @hyperframes/gcp-cloud-run, the GCP counterpart to @hyperframes/aws-lambda (issue #932). The OSS distributed primitives (plan, renderChunk x N, assemble) are unchanged; this package is the storage/compute/orchestration glue. Package: Cloud Run handler (one image, three actions), runs under bun; GCS transport; in-image chrome-headless-shell resolver; client SDK (renderToCloudRun, getRenderProgress, deploySite, computeRenderCost); Dockerfile; Cloud Workflows definition; Terraform module; CLI cloudrun deploy|sites|render|render-batch|progress|destroy with --output-resolution and --strict-variables; 62 unit tests + docs + live smoke script. Shared extraction (removes ~640 lines of adapter duplication): move the cloud-agnostic config validator + content-hash into producer/distributed; both adapters import them. Validated end-to-end on GCP at 37.4 dB PSNR vs baseline. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(cli): resolve @hyperframes/gcp-cloud-run in the CLI build + root build The CLI bundle (esbuild) couldn't resolve `@hyperframes/gcp-cloud-run/sdk`, failing Build/Typecheck/CLI-smoke (and the perf/windows/regression jobs that build first). Mirror the aws-lambda handling: mark the gcp adapter + its /sdk subpath external in tsup.config.ts with a source alias, and add gcp-cloud-run to the root `build` filter so its dist exists for publish + runtime. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(ci): copy gcp-cloud-run manifest in Dockerfile.test for frozen install The regression test image runs `bun install --frozen-lockfile` after copying each workspace package.json individually. The CLI now depends on @hyperframes/gcp-cloud-run (workspace:*), so the frozen install fails to resolve it unless its manifest is present. Add the COPY line. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(cli): add machine-sizing flags to `cloudrun deploy` Closes the parity gap with `lambda deploy` (which exposes --memory etc.). `cloudrun deploy` now threads --cpu, --memory, --max-instances, and --timeout into the Terraform apply; omitted flags keep the module defaults (4 vCPU / 16Gi / 100 instances / 3600s). For finer control, apply the module directly. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(gcp-cloud-run): address PR review (security, waste, limits, alerts) - server.ts: bucket-allowlist guard no longer fails open silently. Unset env logs a one-time WARNING; "*" is an explicit opt-out; otherwise it enforces. - server.ts: stop double-shipping audio.aac. It already rides in the plan tarball every consumer downloads, so drop the redundant standalone upload (plan) + re-download/overwrite (assemble); assemble reads it from the untar, falling back to a supplied AudioGcsUri for compat. - server.ts: chunk extension via path.extname() instead of slice(lastIndexOf). - workflow.yaml: clamp parallel concurrency_limit to math.min(chunkCount, 20) — Cloud Workflows hard-caps concurrent iterations at 20. - Dockerfile: pin bun (bun-v1.3.9) so an interop change can't silently break the image rebuild. - terraform: add min_instances var (default 0); add a workflow-failure alert (finished_execution_count status=FAILED) alongside the request-count one. - costAccounting: document that displayCost excludes GCS storage/egress. Verified against the actual APIs: @google-cloud/workflows@4.4.0 ICreateExecutionRequest has no executionId (so the idempotency-token suggestion isn't available in this client); Workflows concurrency cap is 20; failure metric is workflows.googleapis.com/finished_execution_count (status label). 174 adapter tests pass, fallow/oxlint/oxfmt/terraform clean. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(gcp-cloud-run): address round-2 review — error code + CFR forwarding - workflow.yaml: rename the zero-chunk failure code PLAN_TOO_LARGE → PLAN_PRODUCED_ZERO_CHUNKS. The old code implied a size-ceiling breach (the opposite cause), misleading anyone triaging the alert. - workflow.yaml: forward Config.cfr to the assemble step (`Cfr: ${("cfr" in config) and config.cfr}`). It was read by the handler but never sent, so exact-CFR was silently off for every Cloud Run render. Uses the same `in`-operator guard already proven in the retryable predicate. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(release): include gcp-cloud-run in set-version PACKAGES list set-version.ts (driven by release:prepare) bumps an explicit package list to the shared version on each release. gcp-cloud-run was wired into the build + publish.yml but missing here, so a release would leave it at a stale version and publish.yml would push the wrong version. Add it so the new package version-bumps + publishes in lockstep with the others. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
@hyperframes/aws-lambda
AWS Lambda adapter for HyperFrames distributed rendering. Ships three things together:
- The Lambda handler that wraps the OSS
plan/renderChunk/assembleprimitives behind a single dispatch boundary Step Functions can drive (src/handler.ts). - A client-side SDK —
renderToLambda,getRenderProgress,deploySite, plusvalidateDistributedRenderConfigandcomputeRenderCost(src/sdk/). - An
aws-cdk-libL2 construct (HyperframesRenderStack) that provisions the same topology asexamples/aws-lambda/template.yamlinside an adopter's own CDK app (src/cdk/).
The handler ZIP and the SAM template still drive a maintainer-run real-AWS smoke flow; the SDK + CDK are the supported public surface for adopters.
Architecture
┌──────────────────────────────────────────────────────────────────┐
│ Step Functions state machine │
│ Plan → Map(N) RenderChunk → Assemble │
└──────────────────────────────────────────────────────────────────┘
│ dispatches by event.Action
▼
┌──────────────────────────────────────────────────────────────────┐
│ One Lambda function (this package's `dist/handler.zip`) │
│ handler.mjs │
│ ├─ Action="plan" → @hyperframes/producer/distributed │
│ ├─ Action="renderChunk" → @hyperframes/producer/distributed │
│ └─ Action="assemble" → @hyperframes/producer/distributed │
│ bin/ffmpeg — ffmpeg-static │
│ node_modules/@sparticuz/chromium/ — Lambda-optimised Chromium │
└──────────────────────────────────────────────────────────────────┘
│ pure functions over local paths
▼
┌──────────────────────────────────────────────────────────────────┐
│ S3 bucket — plan tarball + per-chunk outputs + final mp4 │
└──────────────────────────────────────────────────────────────────┘
The handler downloads inputs from S3 into /tmp, calls the OSS primitive,
uploads outputs back to S3, and returns a small JSON result that fits
inside Step Functions' history budget (under 200 bytes per chunk).
Chrome runtime
The package supports two Chromium sources:
| Source | Default | Size | When to pick it |
|---|---|---|---|
@sparticuz/chromium |
yes | ~70 MiB compressed | Lambda. Decompresses into /tmp at runtime; the rest of the ecosystem already uses it for headless-Chrome-in-Lambda. |
Bundled chrome-headless-shell |
no | ~140 MiB | Fallback. Used if @sparticuz/chromium ever drops HeadlessExperimental.beginFrame support. |
Pick the source at build time:
bun run --cwd packages/aws-lambda build:zip
bun run --cwd packages/aws-lambda build:zip -- --source=chrome-headless-shell
The handler reads HYPERFRAMES_LAMBDA_CHROME_SOURCE at boot. The build
script sets that env var via Lambda function configuration in
examples/aws-lambda/template.yaml.
BeginFrame regression guard
HyperFrames' renderer drives Chrome via the CDP
HeadlessExperimental.beginFrame command — same path the K8s deploy uses.
The Lambda adapter assumes that @sparticuz/chromium's
chrome-headless-shell build honours BeginFrame. To prove it (and re-prove
it on every release), the package ships a Docker probe:
# Build the Lambda-like container and run the probe.
bun run --cwd packages/aws-lambda probe:beginframe:docker
The probe boots @sparticuz/chromium inside
public.ecr.aws/lambda/nodejs:22 and asserts CDP beginFrame with
screenshot: true returns a PNG buffer. Exit code 0 = green; non-zero =
fall back to bundling chrome-headless-shell directly via --source=chrome-headless-shell.
Building the ZIP
bun install # at the monorepo root
bun run --cwd packages/aws-lambda build:zip # → packages/aws-lambda/dist/handler.zip
bun run --cwd packages/aws-lambda verify:zip-size # CI gate
The build script bundles src/handler.ts via esbuild, stages
@sparticuz/chromium and puppeteer-core under node_modules/, copies
ffmpeg-static into bin/, and zips the result. The unzipped layout is
designed to extract cleanly into Lambda's /var/task/.
verify:zip-size enforces:
- Unzipped ≤ 248 MiB (in-house budget; Lambda hard ceiling is 250 MiB unzipped — AWS docs label this "250 MB" but use binary mebibytes)
- Zipped ≤ 150 MiB (in-house budget; Lambda has no hard zipped cap for S3-deployed functions)
CI fails the PR if either is exceeded.
Running tests
bun run --cwd packages/aws-lambda test # unit tests (no Chrome)
bun run --cwd packages/aws-lambda probe:beginframe # local probe (Linux only)
Using the SDK
After deploying the stack (via the SAM template, CDK construct below, or your own CFN of choice), drive renders from Node:
import { deploySite, getRenderProgress, renderToLambda } from "@hyperframes/aws-lambda";
// One-time upload per project version.
const site = await deploySite({
projectDir: "./my-composition",
bucketName: "hyperframes-render-bucket",
});
// Start a render. Returns immediately — does NOT poll.
const handle = await renderToLambda({
siteHandle: site,
bucketName: site.bucketName,
stateMachineArn: "arn:aws:states:us-east-1:123:stateMachine:hyperframes-render",
config: {
fps: 30,
width: 1920,
height: 1080,
format: "mp4",
chunkSize: 240,
maxParallelChunks: 16,
runtimeCap: "lambda",
},
});
// Poll progress + cost on your own cadence.
const progress = await getRenderProgress({ executionArn: handle.executionArn });
console.log(progress.overallProgress, progress.costs.displayCost);
if (progress.status === "SUCCEEDED" && progress.outputFile) {
console.log("Render landed at", progress.outputFile.s3Uri);
}
renderToLambda validates the config client-side via
validateDistributedRenderConfig and throws a typed InvalidConfigError
before the Step Functions execution starts, so shape errors surface
synchronously instead of as opaque ExecutionFailed results.
getRenderProgress reports an approximate per-render cost
(accruedSoFarUsd plus a formatted displayCost) derived from Lambda
billed-duration × memory × the us-east-1 on-demand rate plus the Step
Functions transition price. The math is documented in
src/sdk/costAccounting.ts; numbers are best-effort and exclude S3
transfer.
Using the CDK construct
import { App, Stack } from "aws-cdk-lib";
import { HyperframesRenderStack } from "@hyperframes/aws-lambda/cdk";
const app = new App();
const stack = new Stack(app, "MyApp");
const render = new HyperframesRenderStack(stack, "Render", {
// optional: reservedConcurrency: 8,
// optional: lambdaMemoryMb: 10240,
// optional: chromeSource: "sparticuz",
});
// Re-export so an adopter app can wire dashboards / SNS topics.
new CfnOutput(stack, "RenderBucketName", { value: render.bucket.bucketName });
new CfnOutput(stack, "StateMachineArn", { value: render.stateMachine.stateMachineArn });
aws-cdk-lib and constructs are optional peer dependencies: SDK-only
consumers don't pull them at runtime. The construct itself imports from
@hyperframes/aws-lambda/cdk.
What's still ahead
hyperframes lambdaCLI (deploy / sites create / render / progress / destroy) — PR 6.5.- IAM bootstrap subcommand (
policies role | user | validate) — PR 6.9. - Lambda-local regression harness (
--mode=lambda-local) — PR 6.6. - Adopter-facing migration guide — PR 6.8.