DevSecOps on AWS: Defend Against LLM Scrapers & Bot Traffic

What you'll learnHow CloudFront caching works and how to build intelligent, bot-aware delivery flowsHow to implement degraded-content / traffic-splitting strategies using CloudFront, Lambda@Edge, and S3How to separate cache for bots vs humans using CloudFront FunctionsHow to eliminate “missing assets” issues using immutable asset deploymentsHow to deploy and tune CloudFront Origin ShieldHow to analyze CloudFront logs using Athena for bot and traffic insightsHow to configure AWS WAF to be defensive against bots DoS (IP sets, GEO rules, rate rules, managed rules)How to use JA4 fingerprinting for advanced rate-limit funnelsHow AWS WAF Bot Control really works (COMMON vs TARGETED modes)How to integrate the WAF client-side SDK to unlock advanced detectionsHow to read and interpret Bot Control dashboards and labelsHow to build a real Bot Identification Report in AthenaHow to design, validate, and deploy a complete bot strategy (allow, block, degrade)RequirementsAn active AWS accountA domain name to use with CloudFrontUnderstanding of HTTP, web apps, or APIsGood Terraform knowledgeIT IS NOT THE COURSE FOR BEGINNERSShort descriptionThis course teaches you how to survive — and win — in the new era of AI bots, crawlers, scrapers, and automated traffic. Today bots consume an enormous portion of API, web, and CDN traffic. They cost money, distort analytics, break cache logic, and overload your application.

And traditional protections are no longer enough. This course gives you a complete, practical, battle-tested system to handle AI bots with intelligence, not brute force. Section 1 — Understanding the New Threat LandscapeWe begin from the strategic level:Why AI bots became a real business threat, what their objectives are, how bot traffic harms your infrastructure, and how to think about long-term defense.

You will also get a high-level architecture overview — the big picture of CloudFront, WAF, degraded content, and routing logic. Section 2 — Flask Test Application & Terraform PreparationsBefore we defend anything, we need something to protect. You will create a tiny Flask API app, run it locally, understand its behavior, then prepare Terraform, AWS profiles, and ECR to deploy it later in the cloud.

Section 3 — Full Application Deployment Using TerraformThis is the heart of the infrastructure setup. You will:Build networking componentsDelegate a domainConfigure ACMBuild ALBDeploy EC2 using AutoScalingAttach EC2 to ALBConfigure CloudFrontIntegrate WAFExplore the AWS Console and learn to debug application behaviorThis creates the full “lab environment” used for all bot routing experiments in the later sections. Section 4 — Autoscaling & Real AI Bot Cost SurprisesWe explore what happens when bots hit your infrastructure at scale.

You will see real examples of traffic spikes, CPU burns, cost explosions — and learn why AI bots require a different approach than traditional crawlers. We also discuss AWS Fargate and show a real commercial example of bot impact. Section 5 — Intelligent Traffic Routing with CloudFrontThis is where the course becomes truly unique.

You will learn:How CloudFront actually works at request levelHow to build a degraded content strategy — lightweight static content for botsHow to route bots with Lambda@EdgeHow to tag bots using CloudFront FunctionsHow caching issues arise in real deployments and how to fix themHow to handle static assets, versioning, origin shield, and inline assetsHow to make CloudFront fully bot-aware and resilientBy the end, your CloudFront distribution becomes a smart, bot-sensitive traffic router. Section 6 — AWS WAF: Protecting Against AI Crawlers & Automated BotsWe go deep into WAF from both defensive and analytical perspectives:WAF basics and how it actually inspects trafficCustom black & white lists in the context of AI botsGeo-based filteringAthena quick start using WAF logsJA4 fingerprinting & statistical detectionURL-scoped granular rate rulesReputation-based managed rulesIntelligent Bot Mitigation theoryTurning on Bot Control (COMMON + TARGETED)Integrating Bot Control SDKReading Bot Control metrics and dashboardsUnderstanding bot categories and deducing which real bots sit behind themThis section connects CloudFront & WAF into a unified defensive system. Section 7 — Strategic Bot Policy & AI/Bot Traffic Analysis Using AthenaThis is the analytical and strategic peak of the course.

You will learn how to extract real bot traffic from your logs, build a complete Bot Identification Report, and use it to craft a concrete bot defense strategy. Generating the Bot Identification Report using Athena + real production data samplesStrategic bot policy implementation — part 1 (Terraform logic, CloudFront routing, WAF integration)Strategic bot policy implementation — part 2 (finalizing routing, degraded content, block rules)Final course summary + key takeaways + next stepsWe finish with a clear framework that you can apply in any real-world environment — cloud or on-premise. Who this course is forAnyone responsible for web applications, API performance, cloud security, or cost optimization:Software EngineersDevOps & SRECloud ArchitectsSecurity EngineersCTOs, Tech Leads, StartupsAnyone curious about real-world bot defenses and traffic controlIf you want a practical, battle-tested, deep-technical, and fully reproducible defense methodology against AI bots — this course is for you.