README.md

Automating MediaConvert Jobs with Lambda

NOTE: Please also see Workflow-WatchfolderAndNotification for a Lambda sample that includes job status notificatins.

In this module you'll use Amazon S3 events and Lambda to automatically trigger AWS Elemental MediaConvert jobs. The ability to watch S3 folders and take action on incoming items is a useful automation technique that enables the creation of fully unattended workflows. In our case, the user will place videos in a folder on AWS S3 which will trigger an ingest workflow to convert the video. We'll use the job definition from the previous modules as the basis for our automated job.

You'll implement a Lambda function that will be invoked each time a user uploads a video. The lambda will send the video to the MediaConvert service to produce several outputs:

• An Apple HLS adaptive bitrate stream for playout on multiple sized devices and varying bandwiths.
• An MP4 stream
• Thumbnails for use in websites to show a preview of the video at a point in time.

Converted outputs will be saved in the S3 MediaBucket created in earlier in the lab.

Implementation Instructions

Each of the following sections provide an implementation overview and detailed, step-by-step instructions. The overview should provide enough context for you to complete the implementation if you're already familiar with the AWS Management Console or you want to explore the services yourself without following a walkthrough.

A CloudFormation template is provided for this module in the file WatchFolder.yaml, if you would prefer to build the automated workflow automatically. Note: Run the CloudFormation template in us-west-2.

1. Create an Amazon S3 bucket to use for uploading videos to be converted

Use the console or AWS CLI to create an Amazon S3 bucket. Keep in mind that your bucket's name must be globally unique across all regions and customers. We recommend using a name like vod-watchfolder-firstname-lastname. If you get an error that your bucket name already exists, try adding additional numbers or characters until you find an unused name.

1. In the AWS Management Console choose Services then select S3 under Storage.

2. Choose +Create Bucket

3. Provide a globally unique name for your bucket such as vod-watchfolder-firstname-lastname.

4. Select the Region you've chosen to use for this workshop from the dropdown.

5. Choose Create in the lower left of the dialog without selecting a bucket to copy settings from.

   

2. Create an IAM Role for Your Lambda function

Background

Every Lambda function has an IAM role associated with it. This role defines what other AWS services the function is allowed to interact with. For the purposes of this workshop, you'll need to create an IAM role that grants your Lambda function permission to interact with the MediaConvert service and with the DynamoDB table created in the last step.

High-Level Instructions

Use the IAM console to create a new role. Name it VODLambdaRole and select AWS Lambda for the role type.

Attach the managed policy called AWSLambdaBasicExecutionRole to this role to grant the necessary CloudWatch Logs permissions.

Use inline policies to grant permissions to other resources needed for the lambda to execute.

Step-by-step instructions

1. From the AWS Management Console, click on Services and then select IAM in the Security, Identity & Compliance section.

2. Select Roles in the left navigation bar and then choose Create new role.

3. Select AWS Service and Lambda for the role type, then click on the Next:Permissions button.

   Note: Selecting a role type automatically creates a trust policy for your role that allows AWS services to assume this role on your behalf. If you were creating this role using the CLI, AWS CloudFormation or another mechanism, you would specify a trust policy directly.

4. Begin typing AWSLambdaBasicExecutionRole in the Filter text box and check the box next to that role.

5. Choose Next:Review.

6. Enter VODLambdaRole for the Role name.

7. Choose Create role.

8. Type VODLambdaRole into the filter box on the Roles page and choose the role you just created.

9. On the Permissions tab, expand the Add Inline Policies section and choose the JSON tab.

10. Copy and paste the following JSON in the Policy Document Box. You will need to edit this policy in the next step to fill in the resources for your application.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Action": [
                "logs:CreateLogGroup",
                "logs:CreateLogStream",
                "logs:PutLogEvents"
            ],
            "Resource": "*",
            "Effect": "Allow",
            "Sid": "Logging"
        },
        {
            "Action": [
                "iam:PassRole"
            ],
            "Resource": [
                "<ARN for VODMediaConvertRole>"
            ],
            "Effect": "Allow",
            "Sid": "PassRole"
        },
        {
            "Action": [
                "mediaconvert:*"
            ],
            "Resource": [
                "*"
            ],
            "Effect": "Allow",
            "Sid": "MediaConvertService"
        }
    ]
}

1. Replace tag in the policy with the ARN for the VODMMediaConvertRole you created earlier.

2. Click on the Review Policy button.

3. Enter VODLambdaPolicy in the Policy Name box.

4. Click on the Create Policy button.

3. Create a Lambda Function for converting videos

Background

AWS Lambda will run your code in response to events such as a putObject into S3 or an HTTP request. In this step you'll build the core function that will process videos using the MediaConvert python SDK. The lambda function will respond to putObject events in your S3 source bucket. Whenever a video file is added, the lambda will start a MediaConvert job.

This lambda will submit a job to MediaConvert, but it won't wait for the job to complete. In a future module you'll use cloudwatch events to automatically monitor your MediaConvert jobs and take an action when they finish.

High-Level Instructions

Use the AWS Lambda console to create a new Lambda function called VODLambdaConvert that will process the API requests. Use the provided convert.py example implementation for your function code.

Make sure to configure your function to use the VODLambdaRole IAM role you created in the previous section.

Step-by-step instructions

1. Choose Services then select Lambda in the Compute section.

2. Choose Create a Lambda function.

3. Choose the Author from scratch button.

4. On the Author from Scratch panel, enter VODLambdaConvert in the Name field.

5. Select Python 2.7 for the Runtime.

6. Choose Use and existing role from the Role dropdown.

7. Select VODLambdaRole from the Existing Role dropdown.

8. Click on Create function.

   

9. Create a zip file containing the lambda code and JSON job settings. In a terminal, navigate to the directory where you cloned this git repository and zip the code for the lambda.

cd aws-mediaservices-simple-vod-workflow/7-MediaConvertJobLambda
zip -r lambda.zip convert.py job.json

1. On the Configuration tab of the VODLambdaConvert page, in the function code panel:

   1. Select Upload a zip file for the Code entry type

   2. Click Upload and select the zip file you created in the previous step from the dialog box.

   3. Enter convert.handler for the Handler field.

      

2. On the Environment Variables panel of the VODLambdaConvert page, enter the following keys and values:

   1. DestinationBucket = vod-site-firstname-lastname (or whatever you named your static S3 website bucket in module 1)
   2. MediaConvertRole = arn:aws:iam::ACCOUNT NUMBER:role/VODMediaConvertRole

   

3. On the Basic Settings panel, enter the following:

   1. Timeout = 2 min

4. Scroll back to the top of the page and click on the Save button.

Test the lambda

1. From the main edit screen for your function, select Actions then Configure test event.

   

2. Copy and paste the following test event into the editor:

   {
   "Records": [
     {
       "eventVersion": "2.0",
       "eventTime": "2017-08-08T00:19:56.995Z",
       "requestParameters": {
         "sourceIPAddress": "54.240.197.233"
       },
       "s3": {
         "configurationId":   "90bf2f16-1bdf-4de8-bc24-b4bb5cffd5b2",
       "object": {
       "eTag": "2fb17542d1a80a7cf3f7643da90cc6f4-18",
           "key": "vodconsole/TRAILER.mp4",
           "sequencer": "005989030743D59111",
           "size": 143005084
         },
         "bucket": {
           "ownerIdentity": {
             "principalId": ""
           },
           "name": "rodeolabz-us-west-2",
           "arn": "arn:aws:s3:::rodeolabz-us-west-2"
         },
         "s3SchemaVersion": "1.0"
       },
       "responseElements": {
         "x-amz-id-2": "K5eJLBzGn/9NDdPu6u3c9NcwGKNklZyY5ArO9QmGa/t6VH2HfUHHhPuwz2zH1Lz4",
         "x-amz-request-id": "E68D073BC46031E2"
       },
       "awsRegion": "us-west-2",
       "eventName": "ObjectCreated:CompleteMultipartUpload",
       "userIdentity": {
         "principalId": ""
       },
       "eventSource": "aws:s3"
     }
   ]
   }

3. Choose Save and test.

4. Verify that the execution succeeded and that the function result looks like the following:

{
  "body": "{}",
  "headers": {
    "Access-Control-Allow-Origin": "*",
    "Content-Type": "application/json"
  },
  "statusCode": 200
}

6. Create a S3 PutItem Event Trigger for your Convert lambda

Background

In the previous step, you built a lambda function that will convert a video in response to an S3 PutItem event. Now it's time to hook up the Lambda trigger to the watchfolder S3 bucket.

High-Level Instructions

Use the AWS Lambda console to add a putItem trigger from the vod-watchfolder-firstname-lastname S3 bucket to the VODLambdaConvert lambda.

Step-by-step instructions

1. In the Configuration->Designer panel of the VODLambdaConvert function:

   1. Click on *S3 under Add triggers

   

2. Scroll down to the Configure triggers panel:

   1. Select vod-watchfolder-firstname-lastname or the name you used for the watchfolder bucket you created earlier in this module for the Bucket.
   2. Select PUT for the Event type.
   3. Leave the rest of the settings as the default and click the Add button.

   

Test the watchfolder automation

You can use your own video or use the test.mp4 video included in this folder to test the workflow.

In the next module of this lab, we will setup automated monitoring of jobs created using the watchfolder workflow. Until then, you can monitor the the MediaConvert console.

1. Open the S3 console overview page for the watchfolder S3 bucket you created earlier.

2. Select Upload and then choose the file test.mp4 from the directory for this lab module on your computer.

3. Note the time that the upload completed.

4. Open the MediaConvert jobs page and find a job for the input 'test.mp4' that was started near the time your upload completed.

   

5. Navigate to the MP4 or HLS output and play the test video by clicking on the test.mp4 output http resource.