Stop the Stampede: Scaling and Defending Drupal in the Age of AI Scrapers

Session Room
Room 2 (Indigital)
Time Slot
Duration
40 min
Speaker(s)
Full name
Michael Riley Jr
Gender Pronouns
He/Him
Company
Upsun,
Session track
InfoSec & DevOps
Experience level
Intermediate

Are your servers ready for the "AI stampede"? Learn how to protect your Drupal site from aggressive AI scrapers and infrastructure failures using advanced support engineering tactics, observability, and proactive defense at the edge.

Prerequisite

Basic familiarity with web infrastructure (CDNs, Caching, WAFs) and experience managing Drupal sites in production.

Outline

Drawing from years of Elite Cloud Support experience, this session breaks down the critical technical layers needed to keep Drupal stable under extreme conditions:

  • The Content Delivery Budget: Strategies to prevent origin-killing "cache stampedes" where database calls wait for slower requests during traffic spikes.
  • The AI Threat: Identifying and rate-limiting devious AI scrapers that mask their identity using rotated IP blocks.
  • Diagnose with Data: Moving beyond "IP Whac-A-Mole" by extracting JA3/JA4 fingerprints from logs to identify bot patterns.
  • Observability over Guesswork: Setting up APM and historical metrics to find the "needle in the haystack" and build a proper RCA (Root Cause Analysis).
  • War Stories: Real-world lessons from high-stakes outages where flushed caches and unexpected marketing promotions brought sites to their knees.
Learning Objectives
  • Design for Stability: Create a "Day 2" health checklist to ensure Drupal sites remain performant under massive load.
  • Mitigate Cache Abuse: Implement logic to prevent "stampede" scenarios from crashing your database.
  • Extract Identity from Logs: Use log-parsing data to identify JA3/JA4 hashes that distinguish bots from legitimate users.
  • Master Edge Security: Configure VCL snippets and JA4 hash blocks to identify malicious traffic without blocking legitimate users.

Diagnose with Data: Use APM and resource footprint metrics to pinpoint inefficient code and application latency.

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