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RapDev Webinar

AI & Datadog: A Three-Phased Approach to Monitoring and Securing What Matters

Wednesday

Jun 24, 2026

June 24, 2026 12:30 PM

-

June 24, 2026 1:30 PM

ET

Online (Zoom)

Webinar

Join our experts as they break down RapDev's phased approach to AI in Datadog, from monitoring your LLM applications, to securing AI coding assistants and running proactive AI-powered observability across your entire environment.

Don't Miss the Expert Session

AI is moving fast and so is the attack surface it creates. Most organizations are already using LLMs in production or rolling out AI coding assistants to their developer teams, but few have visibility into what those tools are actually doing. Meanwhile, the volume and complexity of alerts has outpaced what any team can triage manually. RapDev has built a structured, three-phased approach to help security and engineering teams get ahead of it within Datadog.

We'll deep dive into our three-phased approach:

  • Phase 1 — LLM Observability: Instrument and monitor your LLM-powered applications in Datadog with full visibility into token usage, latency, prompt/response tracing, and model cost.
  • Phase 2 — AI Coding Assistant Security Monitoring: Monitor coding agent activity, cost, and output via Datadog's Agent Console. Use Code Security and PR Gates to catch bad code, ingest DLP logs for defense-in-depth, and leverage SIEM to correlate threats from developer endpoints. Track governance effectiveness through Dashboards and Reporting.
  • Phase 3 — Proactive AI-Powered Monitoring: Leverage Datadog's native AI capabilities like Watchdog, anomaly detection, and intelligent alerting to shift your team from reactive firefighting to proactive observability.

AI is moving fast and so is the attack surface it creates. Most organizations are already using LLMs in production or rolling out AI coding assistants to their developer teams, but few have visibility into what those tools are actually doing. Meanwhile, the volume and complexity of alerts has outpaced what any team can triage manually. RapDev has built a structured, three-phased approach to help security and engineering teams get ahead of it within Datadog.

We'll deep dive into our three-phased approach:

  • Phase 1 — LLM Observability: Instrument and monitor your LLM-powered applications in Datadog with full visibility into token usage, latency, prompt/response tracing, and model cost.
  • Phase 2 — AI Coding Assistant Security Monitoring: Monitor coding agent activity, cost, and output via Datadog's Agent Console. Use Code Security and PR Gates to catch bad code, ingest DLP logs for defense-in-depth, and leverage SIEM to correlate threats from developer endpoints. Track governance effectiveness through Dashboards and Reporting.
  • Phase 3 — Proactive AI-Powered Monitoring: Leverage Datadog's native AI capabilities like Watchdog, anomaly detection, and intelligent alerting to shift your team from reactive firefighting to proactive observability.

Speakers

Sean McDonough

SOC Analyst

RapDev