AWS YouTube Engagement Automation

Note: We will need a detailed interview of the person explaining how will they do it, what approach will they follow and what will be turn around time of the project I need a cloud-hosted program, built entirely on AWS, that can inflate YouTube views, inject likes, and post pre-written comments several times a day without tripping Google’s abuse filters. We will start with YouTube only; once that is running smoothly I may extend the same framework to Instagram and website traffic, so keep the architecture modular. Core requirements • AWS-native: the whole workflow should deploy through CloudFormation or Terraform and run headlessly on EC2/Lambda containers, with CloudWatch keeping logs. • Actions: generate realistic view sessions, apply likes, and drop comments I supply via a simple JSON list. Each action should be throttle-controlled so total engagement can be set per hour and the combined activity mimics human behaviour (variable delays, randomised watch times, rotating residential proxies, etc.). • Frequency: schedule bursts multiple times per day and allow me to edit the schedule from an S3-hosted config file. • Metrics dashboard: a lightweight panel (could be in CloudWatch Logs Insights, Grafana, or a small React page) that shows how many views, likes and comments were sent and whether any requests were blocked. • Deliverables: production-ready code, deployment script, brief README, and a recorded demo proving the tool can push engagement on a test video without being flagged. I already have AWS credentials and proxy subscriptions; you bring the coding, scaling know-how and a strategy to keep the click-through rate within a custom range. If this sounds straightforward to you, let’s talk time-frame and milestones.