LinkedIn video status PROCESSING_FAILED: read the reason, fix the clip

When a LinkedIn video shows PROCESSING_FAILED, read processingFailureReason on the video resource, fix the file (size, format or length), and upload it again as a new video. Nothing about the failed asset can be repaired in place, so the cheapest fix is to check the clip before you ever call initializeUpload.

This post covers what the Videos API says about the status, how to read it, and how to use Sume's unbilled probe to catch the common causes first.

What does PROCESSING_FAILED mean on the LinkedIn Videos API?

The Videos API resource has four status values. PROCESSING means LinkedIn is generating missing artifacts, AVAILABLE means every required artifact is ready and the asset can be served, WAITING_UPLOAD means LinkedIn is still waiting for your source file, and PROCESSING_FAILED means processing broke.

LinkedIn's page says the failure can come from a client error such as a file that is too large or an unsupported format, but also from internal problems like a performance issue, a database error or a network failure. The processingFailureReason field is only present when the status is PROCESSING_FAILED, so read it before you decide whether the file or the platform was at fault.

Which limits should you check on the clip first?

The Videos API page lists the high-level size rules for non-connected-television video: length from three seconds to 30 minutes, file size between 75 KB and 500 MB, and MP4 as the file format. The same page says fileSizeBytes in the initialize request can describe a file up to 5 GB, which is a different limit, so treat the 500 MB figure as the one for the video specification and test against it.

A clip that misses any of these is the likeliest client-side cause of a failed processing run. You can verify all three before upload without paying for anything.

How do you probe a Sume clip before uploading it?

Sume's video inspect route reads one media.sume.com clip and returns probe facts. Probe and stills are unbilled, and frames: false gives you the probe alone. Pass the clip, then compare the duration and the container details against the numbers above.

The clip must already be on Sume's media host: the docs say there is no open-internet fetch, so import first with POST /v1/media-imports. Inspect also caps the source at 1800 seconds, which happens to match LinkedIn's 30-minute ceiling.

curl -X POST https://api.sume.com/v1/video-inspect \
  -H "Authorization: Bearer $SUME_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Idempotency-Key: li-preflight-001" \
  -d '{
    "video_url": "https://media.sume.com/artifacts/artf_demo/talk.mp4",
    "frames": false
  }'

What if the clip is too long or has a bad head?

Cut it. Video trim takes a start plus exactly one of end or duration and returns a new MP4. It costs $0.02 per job according to the docs, and the source stays untouched. The default precision: exact re-encodes frame-accurately, while keyframe copies the stream and may start a GOP early.

For a script-driven Avatar 1.0 clip, the planned duration lands in a 4 to 60 second window, so length is rarely the problem there; the cause is more often the file route through your own tooling. See the Avatar video docs for the window and the 720p resolution.

What Sume does not do here

The Sume docs I read describe generation and media preparation, not publishing to LinkedIn. You still call initializeUpload, upload parts, and finalizeUpload yourself with the Linkedin-Version and X-Restli-Protocol-Version: 2.0.0 headers. Sume also cannot tell you why LinkedIn failed an asset; only processingFailureReason can. If the reason points at LinkedIn internals, re-upload once and then contact LinkedIn support.