ffmpeg-cloudflare-containers

name

ffmpeg-cloudflare-containers

description

Complete Cloudflare Container FFmpeg system. PROACTIVELY activate for: (1) Cloudflare Containers setup, (2) Native FFmpeg at edge, (3) GPU-accelerated containers, (4) Durable Objects integration, (5) R2 storage for video files, (6) Container autoscaling, (7) Streaming large files, (8) Workers + Containers architecture, (9) Live streaming relay at edge, (10) Container vs Workers comparison. Provides: Dockerfile examples, Worker code, container configuration, GPU setup, R2 integration, production patterns. Ensures: Native FFmpeg performance at Cloudflare edge with full GPU support.

Quick Reference

Component	Configuration
Container Class	export class FFmpegContainer extends Container
Dockerfile	FROM jrottenberg/ffmpeg:7.1-alpine
wrangler.toml	[[containers]] with class_name and image

Feature	Workers (ffmpeg.wasm)	Containers (Native)
Size Limit	10MB	Unlimited
Performance	10-100x slower	Native speed
GPU Support	None	NVIDIA available
Cold Start	Instant	2-3 seconds

When to Use This Skill

Use for edge video processing at scale:

• Native FFmpeg performance at Cloudflare edge
• GPU-accelerated transcoding in containers
• Large file processing (>10MB)
• Complex FFmpeg pipelines
• R2 storage integration for video files

---

FFmpeg in Cloudflare Containers (2025)

Overview

Cloudflare Containers (launched June 2025) enable running FFmpeg natively in a full Linux container environment at the edge. This overcomes all limitations of Workers-based approaches (ffmpeg.wasm size limits, SharedArrayBuffer restrictions).

Key Benefits

Feature	Workers (ffmpeg.wasm)	Containers (Native)
Binary Size	Limited to 10MB	Unlimited (disk space)
Performance	WebAssembly overhead	Native speed
GPU Support	None	NVIDIA GPUs available
Filesystem	Virtual/memory only	Full Linux FS
Dependencies	Must compile to WASM	Any Linux package
Cold Start	Instant	2-3 seconds

Getting Started

Prerequisites

# Docker must be running locally
docker info

# Verify wrangler installation
npx wrangler --version

Create Container Project

# Create from template
npm create cloudflare@latest -- --template=cloudflare/templates/containers-template

# Or manually configure existing project

wrangler.toml Configuration

name = "ffmpeg-processor"
main = "src/index.ts"
compatibility_date = "2025-12-19"

# Container configuration
[[containers]]
class_name = "FFmpegContainer"
image = "./Dockerfile"
max_instances = 10

# Durable Object binding for container
[[durable_objects.bindings]]
name = "FFMPEG_CONTAINER"
class_name = "FFmpegContainer"

# Required migration for SQLite-backed containers
[[migrations]]
tag = "v1"
new_sqlite_classes = ["FFmpegContainer"]

Dockerfile for FFmpeg

# Use official FFmpeg image
FROM jrottenberg/ffmpeg:7.1-alpine AS ffmpeg

# Production image
FROM node:22-alpine

# Install FFmpeg from the official image
COPY --from=ffmpeg /usr/local /usr/local

# Install additional dependencies
RUN apk add --no-cache \
    libva \
    libva-utils \
    mesa-va-gallium

# Set up application
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production

COPY . .

# Container must listen on a port
EXPOSE 8080

CMD ["node", "server.js"]

Worker Code

// src/index.ts
import { Container, DurableObject } from "cloudflare:workers";

interface Env {
  FFMPEG_CONTAINER: DurableObjectNamespace<FFmpegContainer>;
}

export class FFmpegContainer extends Container {
  // Default port the container listens on
  defaultPort = 8080;

  // Sleep after 5 minutes of inactivity
  sleepAfter = "5m";

  // Environment variables for container
  envVars = {
    NODE_ENV: "production",
    FFMPEG_PATH: "/usr/local/bin/ffmpeg"
  };

  async onStart() {
    console.log("FFmpeg container started");
  }

  async onStop() {
    console.log("FFmpeg container stopped");
  }

  async onError(error: Error) {
    console.error("Container error:", error);
  }
}

export default {
  async fetch(: , : ): <> {
     url =  (request.);

    
     (url..()) {
      
       id = env..(crypto.());
       container = env..(id);

      
       container.(request);
    }

    
     (url. === ) {
       id = env..();
       container = env..(id);
       container.(request);
    }

      (, { :  });
  }
};

Container Server (Node.js)

// server.js - Runs inside the container
import express from 'express';
import { spawn } from 'child_process';
import fs from 'fs/promises';
import path from 'path';

const app = express();
app.use(express.raw({ type: '*/*', limit: '100mb' }));

const TEMP_DIR = '/tmp/ffmpeg-work';

app.post('/transcode', async (req, res) => {
  const jobId = Date.now().toString();
  const workDir = path.join(TEMP_DIR, jobId);

  await fs.mkdir(workDir, { recursive: true });

  try {
    // Write input file
    const inputPath = path.join(workDir, 'input');
    await fs.writeFile(inputPath, req.body);

    // Get output format from query
    const format = req.query.format || ;
     outputPath = path.(workDir, );

    
     result =  ([
      , inputPath,
      , ,
      , ,
      , ,
      , ,
      , ,
      , ,
      outputPath
    ]);

     (result. !== ) {
        (result.);
    }

    
     output =  fs.(outputPath);
    res.(, );
    res.(output);

  }  {
    
     fs.(workDir, { : , :  });
  }
});

app.(,  (req, res) => {
   jobId = .().();
   workDir = path.(, jobId);

   fs.(workDir, { :  });

   {
     inputPath = path.(workDir, );
     palettePath = path.(workDir, );
     outputPath = path.(workDir, );

     fs.(inputPath, req.);

    
    
     ([
      , inputPath,
      , ,
      , palettePath
    ]);

    
     ([
      , inputPath,
      , palettePath,
      , ,
      , outputPath
    ]);

     output =  fs.(outputPath);
    res.(, );
    res.(output);

  }  {
     fs.(workDir, { : , :  });
  }
});

app.(,  {
  res.({ : , : process.. });
});

 () {
    ( {
     proc = (, args, { : [, , ] });

     stdout = ;
     stderr = ;

    proc..(,  { stdout += data; });
    proc..(,  { stderr += data; });

    proc.(,  {
      ({ exitCode, stdout, stderr });
    });
  });
}

  = process.. || ;
app.(,  {
  .();
});

GPU-Accelerated Containers

Cloudflare Containers support NVIDIA GPUs for hardware-accelerated encoding:

GPU Container Configuration

[[containers]]
class_name = "FFmpegGPU"
image = "./Dockerfile.gpu"
max_instances = 5
# GPU instances have higher resource allocation

GPU Dockerfile

FROM nvidia/cuda:12.4-runtime-ubuntu24.04

# Install FFmpeg with NVIDIA support
RUN apt-get update && apt-get install -y \
    ffmpeg \
    libnvidia-encode-550 \
    libnvidia-decode-550 \
    && rm -rf /var/lib/apt/lists/*

# Verify NVENC support
RUN ffmpeg -encoders | grep nvenc

WORKDIR /app
COPY . .

EXPOSE 8080
CMD ["node", "server.js"]

NVENC Encoding in Container

app.post('/transcode-gpu', async (req, res) => {
  const args = [
    '-hwaccel', 'cuda',
    '-hwaccel_output_format', 'cuda',
    '-i', inputPath,
    '-c:v', 'h264_nvenc',
    '-preset', 'p4',
    '-cq', '23',
    '-c:a', 'aac',
    '-b:a', '128k',
    outputPath
  ];

  await runFFmpeg(args);
});

Autoscaling Configuration

export class FFmpegContainer extends Container {
  // Autoscaling based on CPU usage
  static scaling = {
    minInstances: 1,      // Always keep one warm
    maxInstances: 20,
    targetCPU: 75,        // Scale up at 75% CPU
    scaleDownDelay: "5m"  // Wait before scaling down
  };

  sleepAfter = "10m";  // Sleep idle containers after 10 min
}

Pricing Considerations

Metric	Billing
Compute	Per 10ms while active
Idle	No charge (containers sleep)
Storage	Per GB-month
Egress	Standard Cloudflare egress

Best Practices

1. Container Size Optimization

# Use multi-stage builds
FROM jrottenberg/ffmpeg:7.1-alpine AS ffmpeg
FROM node:22-alpine AS builder

WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production

# Final minimal image
FROM node:22-alpine
COPY --from=ffmpeg /usr/local/bin/ffmpeg /usr/local/bin/
COPY --from=ffmpeg /usr/local/bin/ffprobe /usr/local/bin/
COPY --from=builder /app/node_modules ./node_modules
COPY . .

CMD ["node", "server.js"]

2. Warm Instance Strategy

// Keep containers warm for low-latency
export class FFmpegContainer extends Container {
  sleepAfter = "30m";  // Longer idle before sleep
}

// Pre-warm containers on deploy
export default {
  async scheduled(controller: ScheduledController, env: Env) {
    // Ping containers to keep them warm
    const id = env.FFMPEG_CONTAINER.idFromName("warmup");
    const container = env.FFMPEG_CONTAINER.get(id);
    await container.fetch(new Request("http://internal/health"));
  }
};

3. Streaming Large Files

// Stream output instead of buffering
app.post('/transcode-stream', async (req, res) => {
  const ffmpeg = spawn('ffmpeg', [
    '-i', 'pipe:0',
    '-c:v', 'libx264',
    '-f', 'mp4',
    '-movflags', 'frag_keyframe+empty_moov',
    'pipe:1'
  ]);

  req.pipe(ffmpeg.stdin);
  ffmpeg.stdout.pipe(res);

  ffmpeg.stderr.on('data', (data) => {
    console.log('FFmpeg:', data.toString());
  });
});

4. R2 Storage Integration

// Store processed files in R2
export default {
  async fetch(request: Request, env: Env) {
    // Process video in container
    const result = await container.fetch(request);

    // Store in R2
    const key = `processed/${Date.now()}.mp4`;
    await env.R2_BUCKET.put(key, result.body);

    return new Response(JSON.stringify({ key }), {
      headers: { 'Content-Type': 'application/json' }
    });
  }
};

Common Use Cases

Video Thumbnails at Edge

app.post('/thumbnail', async (req, res) => {
  await runFFmpeg([
    '-i', inputPath,
    '-ss', '00:00:01',
    '-vframes', '1',
    '-vf', 'scale=320:-1',
    outputPath
  ]);
});

Audio Extraction

app.post('/extract-audio', async (req, res) => {
  await runFFmpeg([
    '-i', inputPath,
    '-vn',
    '-c:a', 'aac',
    '-b:a', '192k',
    outputPath
  ]);
});

Live Streaming Relay

// Relay RTMP to HLS at edge
const ffmpeg = spawn('ffmpeg', [
  '-i', rtmpInput,
  '-c:v', 'copy',
  '-c:a', 'copy',
  '-hls_time', '4',
  '-hls_list_size', '10',
  '-hls_flags', 'delete_segments',
  '/output/stream.m3u8'
]);

Deployment

# Deploy to Cloudflare
wrangler deploy

# First deployment takes several minutes
# Subsequent deploys are faster with incremental image updates

Monitoring

// Health check endpoint
app.get('/metrics', async (req, res) => {
  const metrics = {
    uptime: process.uptime(),
    memory: process.memoryUsage(),
    deploymentId: process.env.CLOUDFLARE_DEPLOYMENT_ID
  };
  res.json(metrics);
});

Comparison: Workers vs Containers

Use Case	Recommendation
Simple filters (resize, crop)	Workers + ffmpeg.wasm
Full transcoding	Containers
GPU acceleration	Containers (GPU instances)
Low latency (<100ms)	Workers
Large files (>10MB)	Containers
Complex pipelines	Containers

Troubleshooting

Container Not Starting

# Check Docker locally
docker build -t test-ffmpeg .
docker run --rm test-ffmpeg ffmpeg -version

# Verify architecture
docker inspect test-ffmpeg | grep Architecture
# Must be linux/amd64

FFmpeg Not Found

# Ensure FFmpeg is in PATH
ENV PATH="/usr/local/bin:${PATH}"

# Verify installation
RUN which ffmpeg && ffmpeg -version

Timeout Issues

// Increase timeout for long operations
export class FFmpegContainer extends Container {
  // Extend request timeout
  async fetch(request: Request) {
    // Container internal timeout handling
    const controller = new AbortController();
    setTimeout(() => controller.abort(), 300000); // 5 min

    return super.fetch(request, { signal: controller.signal });
  }
}

References

• Cloudflare Containers Documentation
• Cloudflare Containers Announcement
• Container Image Management