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Converting a video to a GIF in Python using the management console

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Updated at April 6, 2026

To create a video-to-GIF conversion framework in Python using the Yandex Cloud management console:

  1. Get your cloud ready.
  2. Create resources.
  3. Create an API function.
  4. Create a converter function.
  5. Create a trigger.
  6. Test the application.

If you no longer need the resources you created, delete them.

Get your cloud ready

Sign up for Yandex Cloud and create a billing account:

  1. Navigate to the management console and log in to Yandex Cloud or create a new account.
  2. On the Yandex Cloud Billing page, make sure you have a billing account linked and it has the ACTIVE or TRIAL_ACTIVE status. If you do not have a billing account, create one and link a cloud to it.

If you have an active billing account, you can create or select a folder for your infrastructure on the cloud page.

Learn more about clouds and folders here.

The infrastructure support cost includes:

Create resources

  1. Clone the repository with configuration files:

    git clone https://github.com/yandex-cloud-examples/yc-serverless-video-gif-converter.git

  2. Create a service account named ffmpeg-sa and assign it the following roles:

    • ymq.reader
    • ymq.writer
    • lockbox.payloadViewer
    • storage.viewer
    • storage.uploader
    • ydb.admin
    • functions.functionInvoker

  3. Create a static key for the service account. Save the Key ID and Your secret key.

  4. Create a secret named ffmpeg-sa-secret in Yandex Lockbox:

    1. Select Secret type: Custom.

    2. Under Version, specify:

      • ACCESS_KEY_ID as the key and Key ID from the previous step as the value.
      • SECRET_ACCESS_KEY as the key and Your secret key from the previous step as the value.

      Save the secret ID from the Information about secret section.

  5. Create a message queue named converter-queue in Yandex Message Queue. Save the queue URL from the General information section.

  6. Create a YDB database in Serverless mode. Save the Endpoint from the Document API endpoint section.

  7. Create a table in the database:

  8. Create a bucket with restricted access in Yandex Object Storage.

Create an API function

The function implements an API which you can use to perform the following actions:

  • convert: Provide a video for conversion. The function writes the task to the tasks table using the Document API.
  • get_task_status: Get the task status. The function checks whether the task has been completed and returns a link to a GIF file.

  1. Create a function named ffmpeg-api.

  2. Create a function version:

    1. Create a file named requirements.txt and specify these libraries in it:

      boto3
yandexcloud

    2. Create a file named index.py and paste into it the contents of the ffmpeg-api.py file from the ffmpeg-api.zip archive.

    3. Specify the following parameters:

      • Runtime environment: python312.
      • Entry point: index.handle_api.
      • Timeout: 5.
      • Service account: ffmpeg-sa.

    4. Add these environment variables:

      • DOCAPI_ENDPOINT: Endpoint from the database configuration.
      • SECRET_ID: Yandex Lockbox secret ID.
      • YMQ_QUEUE_URL: URL of the Message Queue-enabled queue.

Create a converter function

A converter function is run by a trigger. It processes videos and registers the result in the tasks table.

Video conversion is based on the FFmpeg utility. The FFmpeg executable is larger than 70 MB. To upload it along with the function code, create a ZIP archive and upload it via Object Storage. Learn more about code upload formats.

  1. Create a function named ffmpeg-converter.

  2. Create an src.zip archive with the following files:

    • requirements.txt file:

      boto3
requests
yandexcloud

    • The index.py file with the contents of the ffmpeg-converter.py file from the src.zip archive.

    • The FFmpeg executable. On FFmpeg's official website, navigate to the Linux Static Builds section, download the 64-bit FFmpeg archive, and make the file executable by running the chmod +x ffmpeg command.

  3. Upload src.zip to the bucket you created earlier.

  4. Create a function version:

    1. Specify the following parameters:

      • Runtime environment: python312.
      • Code source: Object Storage upload method.
      • Bucket: Name of the bucket you created earlier.
      • Object: src.zip.
      • Entry point: index.handle_process_event.
      • Timeout: 600.
      • Memory: 2048 MB.
      • Service account: ffmpeg-sa.

    2. Add these environment variables:

      • DOCAPI_ENDPOINT: Endpoint from the database configuration.
      • SECRET_ID: Yandex Lockbox secret ID.
      • YMQ_QUEUE_URL: URL of the Message Queue-enabled queue.
      • S3_BUCKET: Name of the bucket you created earlier.

Create a trigger

A message queue is handled using a trigger for Message Queue. It invokes the converter function as messages arrive in converter-queue.

  1. In the management console, select the folder where you want to create a trigger.
  2. Select Cloud Functions.
  3. Navigate to the Triggers tab.
  4. Click Create trigger.
  5. Under Basic settings:
    • Enter a name for the trigger: ffmpeg-trigger.
    • In the Type field, select Message Queue.
  6. Under Message Queue message settings, select the converter-queue message queue and the service account named ffmpeg-sa with permission to read messages from it.
  7. Under Function settings:
    • Select the function for the trigger to invoke: ffmpeg-converter.
    • Specify the function version tag: $latest.
    • Specify the service account which will invoke the function: ffmpeg-sa.
  8. Click Create trigger.

Test the application

Create a task

  1. In the management console, select the folder containing the ffmpeg-api function.

  2. Select Cloud Functions.

  3. Select the ffmpeg-api function.

  4. Navigate to the Testing tab.

  5. In the Payload field, enter:

    {"action":"convert", "src_url":"<link_to_video>"}

    Where <link_to_video> is a link to an MP4 video file saved to Yandex Disk.

  6. Click Run test.

  7. You will see the task ID in the Function output field:

    { "task_id": "c4269ceb-8d3a-40fe-95f0-84cf********" }

View the queue statistics

Once the task is created, the queued message count will increase by one and a trigger will fire. Make sure messages arrive in the queue and are handled. To do this, view the queue statistics.

  1. In the management console, select the folder housing converter-queue.
  2. Select Message Queue.
  3. Select converter-queue.
  4. Under General information, you can see the queued and processed message counts.
  5. Go to Monitoring. View the Overall queue stats charts.

View the function logs

The trigger should invoke the converter function for each message in the queue. To make sure the function is invoked, check its logs.

  1. In the management console, select the folder containing the ffmpeg-converter function.
  2. Select Cloud Functions.
  3. Select ffmpeg-converter.
  4. Go to the Logs tab and specify the period to view the logs for.

  1. In the management console, select the folder containing the ffmpeg-api function.

  2. Select Cloud Functions.

  3. Select the ffmpeg-api function.

  4. Navigate to the Testing tab.

  5. In the Payload field, enter the following request:

    {"action":"get_task_status", "task_id":"<job_ID>"}

  6. Click Run test.

  7. If video conversion to GIF has not been completed, the Function output field will return:

    {
    "ready": false
}

    Otherwise, you will get a link to the GIF file:

    {
    "ready": true,
    "gif_url": "https://storage.yandexcloud.net/<bucket_name>/1b4db1a6-f2b2-4b1c-b662-37f7********.gif?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=qxLftbbZ91U695ysemyZ%2F202********ru-central1%2Fs3%2Faws4_request&X-Amz-Date=20210831T110351Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=f4a5fe7848274a09be5b221fbf8a9f6f2b385708cfa351861a4e69df********"
}

How to delete the resources you created

To stop paying for the resources you created:

  1. Delete converter-queue.
  2. Delete the database.
  3. Delete all objects from the bucket.
  4. Delete the bucket.
  5. Delete the ffmpeg-api and ffmpeg-converter functions.
  6. Delete the ffmpeg-trigger trigger.

See also

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