This project serves as a sample implementation for embedding forensic watermarks using Akamai EdgeWorkers. It provides the basic structure and logic required to deploy watermark embedding functionality at the edge.

For more information, refer to the Akamai EdgeWorkers Documentation.

Update config.js with your specific settings:

export const config = {
    "aesKey": "YOUR_AES_KEY",
    "type" : "unlabeled_a_variant",
    "availableInterval": 60000,
    "prefixFolder": ["folder1", "folder2"],
    "wmtPublicKey": "YOUR_PUBLIC_KEY", // PEM format public key for Akamai WMT
    "wmtPassword": "YOUR_PASSWORD", // Password for WMT token generation/verification
    "cpCode": "YOUR_CP_CODE" // Akamai CP Code
}

wmt_type: Indicates whether the issued token format is AES-encrypted or JWT. This corresponds to the specification provided when requesting the watermark token.

• Watermark Token Request Specification

• Distinguishes A/B files based on folders.

/wm-contents/output_path/cid/{0/1}/dash/stream.mpd
/wm-contents/output_path/cid/{0/1}/dash/video/0/seg-125.m4s
/wm-contents/output_path/cid/{0/1}/hls/master.m3u8
/wm-contents/output_path/cid/{0/1}/hls/video/0/0/stream.m3u8
/wm-contents/output_path/cid/{0/1}/hls/video/0/0/segment-125.ts

• A/B files exist in the same folder and are distinguished by filenames.

/wm-contents/output_path/cid/dash/stream.mpd
/wm-contents/output_path/cid/dash/video/0/seg-125.m4s
/wm-contents/output_path/cid/dash/video/0/b.seg-125.m4s
/wm-contents/output_path/cid/hls/master.m3u8
/wm-contents/output_path/cid/hls/video/0/0/stream.m3u8
/wm-contents/output_path/cid/hls/video/0/0/segment-125.ts
/wm-contents/output_path/cid/hls/video/0/0/b.segment-125.ts

The EdgeWorkers intercepts client requests and routes them based on the URL structure:

1. Akamai WMT: If the path starts with wmt:, it uses akamaiWmt.js to verify the token and rewrite the path.
2. DoveRunner AES: If the path matches one of the prefixFolder entries, it uses doveRunnerAes.js to decrypt the watermark data and generate the appropriate content path.

1. Update the edgeworker-version in bundle.json.

2. Run build-bundle.sh to create a bundle file.

3. Upload the bundle to edgeWorkers.

   3-1. If akamai cli and EdgeWorkers cli are installed, run script.

   akamai edgeworkers upload --bundle doverunner_fwm_embedder_{version}.tgz {YOUR_EW_ID}`.
   

   3-2. If akamai cli is not installed, Go to the Akamai EdgeWorkers IDs page, click the Create version button, and upload the compressed file.

4. Select the Network (stage, production) you want to deploy to and click the Activate version button.