# AWS Lambda + Step Functions deployment

Reference SAM template for deploying HyperFrames distributed rendering on
AWS. One Lambda function, three roles (Plan / RenderChunk / Assemble),
choreographed by a Step Functions standard workflow with a Map state for
parallel chunk rendering.

See [`packages/aws-lambda/README.md`](../../packages/aws-lambda/README.md)
for the Lambda handler architecture.

## Prerequisites

- AWS account with IAM permissions to deploy CloudFormation stacks
  containing Lambda, Step Functions, S3, IAM, and CloudWatch resources.
- [`sam` CLI](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/install-sam-cli.html)
  installed (≥ 1.100).
- [`bun`](https://bun.sh) installed (≥ 1.3) to build the handler ZIP.

## One-shot deploy

```bash
# 1. Build the handler ZIP that `template.yaml`'s CodeUri points at.
bun install                                       # at repo root
bun run --cwd packages/aws-lambda build:zip

# 2. Deploy. First time: `--guided` to set stack name + region.
cd examples/aws-lambda
sam deploy --guided --resolve-s3
```

`--resolve-s3` lets SAM pick (or create) a per-account bucket to host the
uploaded ZIP. After the first deploy, subsequent updates can omit
`--guided` and `--resolve-s3` — SAM remembers your choices in
`samconfig.toml`.

## What gets created

| Resource                                 | Purpose                                                                                            |
| ---------------------------------------- | -------------------------------------------------------------------------------------------------- |
| `Render Lambda`                          | Single function, handler `handler.handler`. Dispatches on `event.Action`.                          |
| `Render State Machine`                   | Step Functions standard workflow. Plan → Map(N) RenderChunk → Assemble.                            |
| `Render Bucket`                          | S3 bucket for plan tarballs, chunk outputs, and final mp4. `renders/` prefix expires after 7 days. |
| IAM role for the state machine           | Invokes the Lambda; writes CloudWatch logs; X-Ray traces.                                          |
| IAM role for the Lambda (managed by SAM) | S3 CRUD on the render bucket; CloudWatch logs.                                                     |
| Runaway-invocation alarm                 | Fires if RenderChunk runs more than `ChunkInvocationAlarmThreshold` times in an hour.              |

## Running a render

Upload your project as a zip to the render bucket, then start a Step
Functions execution:

```bash
STACK_NAME=hyperframes-render          # whatever you picked at deploy
RENDER_BUCKET=$(aws cloudformation describe-stacks \
  --stack-name "$STACK_NAME" \
  --query 'Stacks[0].Outputs[?OutputKey==`RenderBucketName`].OutputValue' \
  --output text)
STATE_MACHINE_ARN=$(aws cloudformation describe-stacks \
  --stack-name "$STACK_NAME" \
  --query 'Stacks[0].Outputs[?OutputKey==`RenderStateMachineArn`].OutputValue' \
  --output text)

# Tar + upload the project directory. The handler uses `tar` (not
# `unzip`, which Lambda's base image doesn't ship), so the on-the-wire
# archive format is `.tar.gz`.
tar -czf my-project.tar.gz -C ./my-project .
aws s3 cp my-project.tar.gz "s3://${RENDER_BUCKET}/projects/my-project.tar.gz"

# Start the execution. The input JSON tells the state machine where to
# read inputs and write outputs.
aws stepfunctions start-execution \
  --state-machine-arn "$STATE_MACHINE_ARN" \
  --input "$(cat <<EOF
{
  "ProjectS3Uri": "s3://${RENDER_BUCKET}/projects/my-project.tar.gz",
  "PlanOutputS3Prefix": "s3://${RENDER_BUCKET}/renders/$(date +%s)/",
  "OutputS3Uri": "s3://${RENDER_BUCKET}/output.mp4",
  "PlanProtocol": "v2",
  "Config": {
    "fps": 30,
    "width": 1920,
    "height": 1080,
    "format": "mp4",
    "chunkSize": 240,
    "maxParallelChunks": 8,
    "runtimeCap": "lambda"
  }
}
EOF
)"
```

The Step Functions execution kicks off Plan, fans out RenderChunk via
the Map state, and finally Assemble. Final mp4 lands at `OutputS3Uri`.
Plan v2 is recommended for new integrations. `PlanProtocol` may be `"v1"` or
`"v2"`; absent still defaults to v1 for backwards compatibility. V2 uses
separate manifest and content-addressed artifact locators throughout the
workflow and never places a v2 object in `PlanS3Uri`.

## Local invocation

You can test the Lambda handler without deploying anything via SAM
local:

```bash
# Build the ZIP first.
bun run --cwd packages/aws-lambda build:zip

# Launch a local Lambda runtime emulator and run a sample plan event.
cd examples/aws-lambda
sam validate
sam local invoke RenderFunction --event sample-events/plan.json
```

The `sample-events/` directory ships small JSON payloads for each of the
three actions. They reference fake S3 URIs — useful for sanity-checking
the handler's dispatch logic; not for full end-to-end testing (real S3
calls require credentials and a project zip to actually exist).

## End-to-end smoke + benchmark

For full end-to-end validation against real AWS — the gate that proves
the architecture works on a deployed Lambda — use the local smoke
script:

```bash
# Defaults use the fixture's meta.json minPsnr (30 dB for mp4-h264-sdr).
./scripts/smoke.sh

# Customised:
./scripts/smoke.sh \
  --fixture mp4-h264-sdr \
  --chunk-counts 2,4,8,16 \
  --plan-protocol both \
  --psnr-threshold 40 \
  --reserved-concurrency 8

# Keep the stack alive for inspection afterward:
./scripts/smoke.sh --keep-stack

# Show all flags including cost notes:
./scripts/smoke.sh --help
```

The script builds the handler ZIP, deploys this template under a
per-run stack name, renders the fixture at each chunk count via the
Step Functions state machine, PSNR-compares against the in-process
baseline (which is git-LFS tracked under
`packages/producer/tests/distributed/<fixture>/output/`), captures
per-execution Step Functions history, and tears the stack down. Use
`--plan-protocol both` to run v1 and v2 through the same deployed Lambda
package and baseline. Each v1/v2 pair is also gated directly on per-chunk
hashes from Step Functions history, normalized decoded RGBA frame hashes,
decoded 48 kHz stereo s16le PCM hashes and byte counts, normalized stream
metadata, and duration. Encoded MP4 SHA equality is reported but is
informational unless `--require-encoded-sha-equal` is set. The script
assigns unique function/state-machine names, uses a
dedicated temporary SAM artifact bucket, and removes render objects,
retained buckets, the implicit Lambda log group, and deployment artifacts
on teardown. Suspended-version buckets are purged in 1,000-entry batches,
including concrete versions, null versions, and delete markers. It then
verifies that the stack, both buckets, Lambda, state-machine, and both log
groups are absent; an otherwise-successful run fails if cleanup cannot be
proven.

**Wall-clock methodology caveat (`eval.sh` only).** `eval.sh` reports a
local-vs-Lambda "speedup" column. The local timing includes `bun` +
`tsx` + harness scaffolding (not just renderer-internal time); the
Lambda timing measures Step Functions execution only. This biases the
speedup against Lambda on tiny fixtures and in favour of Lambda on
larger ones. Treat the number as "end-to-end CLI experience," not as a
renderer-vs-renderer benchmark. Cold-start variance is ±5-10s per
chunk; run with `--iterations 3+` to report medians.

**Cost per pass.** Each `eval.sh` invocation runs `SAM deploy` (~$0.01
in CFN operations) plus N fixtures × ITERATIONS × CHUNK_COUNT Lambda
invocations at `MemorySize` (default 10 GiB) × per-chunk wall clock.
With defaults (4 fixtures, 1 iteration, chunk-count 4) the Lambda
spend is roughly $0.10-$0.20 per pass before S3 transfer. Lower
`--reserved-concurrency` for cost-conscious accounts; higher
`--iterations` improves median stability at proportional cost.

Outputs land under `<repo-root>/lambda-smoke-artifacts/`:

- `results.json` — `planProtocol × chunkCount × wallClockMs × psnrAvgDb`
- `semantic-comparisons.json` — direct v1/v2 semantic gate results
- `renders/<protocol>-N<N>-output.mp4` — each rendered variant
- `renders/<protocol>-N<N>-history.json` — full Step Functions execution history
- `renders/v1-v2-N<N>.*` — normalized frame hashes, ffprobe metadata, and comparison JSON

Prerequisites: `aws` (v2), `sam` (≥ 1.100), `bun` (≥ 1.3), `ffmpeg`,
`jq`, `zip`. AWS credentials come from the standard resolution chain
(env vars → `~/.aws/credentials` → SSO → IMDS). Pin a specific profile
with `--profile <name>` or `AWS_PROFILE=<name>`.

## Parameters

| Parameter                       | Default       | Notes                                                                                           |
| ------------------------------- | ------------- | ----------------------------------------------------------------------------------------------- |
| `ProjectName`                   | `hyperframes` | Prefix for created resource names.                                                              |
| `LambdaMemoryMb`                | `10240`       | Lambda memory; Lambda allocates CPU proportionally. 10 GB recommended for 1080p.                |
| `LambdaTimeoutSec`              | `900`         | Per-invocation timeout. 15 min is Lambda's hard ceiling.                                        |
| `ReservedConcurrency`           | `-1`          | Hard cap on simultaneous Lambda invocations. `-1` = unreserved. Set to e.g. `50` to bound cost. |
| `ChromeSource`                  | `sparticuz`   | Must match the `--source=` flag passed to `build-zip.ts`.                                       |
| `ChunkInvocationAlarmThreshold` | `1000`        | CloudWatch alarm threshold (RenderChunk invocations per hour).                                  |

## Cleanup

```bash
sam delete --stack-name hyperframes-render
```

S3 buckets are `Retain`ed on delete to protect rendered artifacts.
Empty + delete the bucket manually after `sam delete` if you want to
fully tear down.

## Cost model

| Service                 | Driver                                  | Approximate cost                                               |
| ----------------------- | --------------------------------------- | -------------------------------------------------------------- |
| Lambda                  | Per-invocation billed duration × memory | ≈ $0.0000167/GB-s; a 10 GB function running 5 min costs ~$0.50 |
| Step Functions Standard | Per state transition                    | $0.025/1k transitions                                          |
| S3                      | Storage + GET/PUT                       | Dominated by mp4 storage; plan tarballs expire in 7 days       |
| CloudWatch Logs         | Ingestion + storage                     | Logs are not throttled; set retention manually if cost matters |

A 60-second 1080p30 composition at default chunkSize=240 (8 chunks)
typically costs ~$0.04 in Lambda time + ~$0.001 in Step Functions.
The eval script under `scripts/eval.sh` produces real per-fixture cost
numbers when you run it against your own AWS account.

## Troubleshooting

- **"Chrome failed to launch"** — the ZIP was likely built with the wrong
  `--source`. Match `ChromeSource` to the build flag.
- **"PLAN_HASH_MISMATCH"** — non-retryable. The plan tarball was written
  by a different version of the producer than the chunk worker is
  running. Re-plan from scratch.
- **"BROWSER_GPU_NOT_SOFTWARE"** — Chromium fell back to a hardware GL
  backend. Should not happen in Lambda (no GPU); file an issue.
- **CloudWatch alarm firing on `runaway-chunk-invocations`** — check
  the state machine execution history for an unintended Map fan-out, or
  raise the threshold if your workload genuinely exceeds it.

## What's NOT in this directory

- CDK construct shipping the same topology programmatically — follow-up.
- `hyperframes lambda deploy / render / progress / destroy` CLI — follow-up.
- Migration guide — follow-up.
- Lambda RIE local smoke harness mode — follow-up.
