1. Developing a video analytics platform using AWS Elemental MediaConvert for video processing and insights extraction via Rekognition

    TypeScript

    Given your requirements, we will structure our application to use AWS Elemental MediaConvert to convert and compress video data and AWS Rekognition to perform video analysis.

    Using Pulumi's AWS Provider, we can manage AWS resources like Elemental MediaConvert and Rekognition.

    Here's a basic outline of how we could structure the program:

    1. We'll create an AWS S3 bucket to store the videos you want to process.
    2. Use Elemental MediaConvert to apply video processing on the video files stored in the S3 bucket.
    3. Publish the processed video data from MediaConvert to another S3 bucket.
    4. Use Rekognition to extract insights from the videos in the second S3 bucket.

    The high-level program is as follows:

    import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

// Create an AWS resource (S3 Bucket) for raw videos
const rawVideosBucket = new aws.s3.Bucket("rawVideosBucket");

// Configure AWS Elemental MediaConvert
const mediaConvertRole = new aws.iam.Role("mediaConvertRole", {
    assumeRolePolicy: JSON.stringify({
        Version: "2012-10-17",
        Statement: [
            {
                Action: "sts:AssumeRole",
                Effect: "Allow",
                Sid: "",
                Principal: {
                    Service: "mediaconvert.amazonaws.com",
                },
            },
        ],
    }),
});

// Attach the necessary policy for the mediaConvertRole
new aws.iam.RolePolicyAttachment("mediaConvertRolePolicyAttachment", {
    role: mediaConvertRole.name,
    policyArn: aws.iam.ManagedPolicies.AWSLambdaVPCAccessExecutionRole,
});

// Create a MediaConvert Queue
const mediaConvertQueue = new aws.mediaconvert.Queue("mediaConvertQueue", {
    description: "Queue for converting raw videos",
    status: "ACTIVE",
});

// Use MediaConvert Queue to apply video processing on the videos from the rawVideosBucket
// The actual implementation will require you to specify the appropriate settings
// For simplicity, this resource is not created in this example

// Create another AWS resource (S3 Bucket) for processed videos
const processedVideosBucket = new aws.s3.Bucket("processedVideosBucket");

// Configure AWS Rekognition to extract insights from the processed videos
const rekognitionRole = new aws.iam.Role("rekognitionRole", {
    assumeRolePolicy: JSON.stringify({
        Version: "2012-10-17",
        Statement: [
            {
                Action: "sts:AssumeRole",
                Effect: "Allow",
                Sid: "",
                Principal: {
                    Service: "rekognition.amazonaws.com",
                },
            },
        ],
    }),
});

// Attach the necessary policy for the rekognitionRole
new aws.iam.RolePolicyAttachment("rekognitionRolePolicyAttachment", {
    role: rekognitionRole.name,
    policyArn: aws.iam.ManagedPolicies.AWSLambdaVPCAccessExecutionRole,
});

// Use Rekognition to extract insights from the videos in the processedVideosBucket
// The actual implementation will require you to specify the appropriate video
// model and analysis type. For simplicity, this resource is not created in this example

// Export the name of the buckets
export const rawVideosBucketName = rawVideosBucket.id;
export const processedVideosBucketName = processedVideosBucket.id;

    Please note, AWS Elemental MediaConvert settings for applying video processing, and AWS Rekognition settings for extracting insights from videos, were not fully implemented, as they are quite vast and depend on your specific application's need.

    Resource documentation links:


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