Asynchronous Image and Video Processing

After upload, publish an asset-processing job. Workers can inspect the file, generate thumbnails, transcode video into multiple resolutions, extract metadata, and update the asset's processing state. Queue-based processing isolates CPU-intensive tasks from interactive API traffic.

Make jobs idempotent and version outputs so a retry or new processing profile does not overwrite a newer result incorrectly. Track states such as uploaded, validating, processing, ready, rejected, and failed. Expose status to the client and distinguish retryable infrastructure failures from permanent invalid input.

Scale workers by queue age and processing cost, not only CPU. Video duration and resolution create very different workloads, so use weighted scheduling or separate queues for expensive jobs. Apply quotas to prevent a small number of users from monopolizing processing capacity.

Key Takeaways
  • Move CPU-heavy media work off the interactive request path.
  • Make processing retries idempotent and outputs versioned.
  • Scale based on workload cost and queue delay.