Zendesk chose Datadog for observability (APM, Log Management) to boost performance, resolve issues faster, and optimize infrastructure. Datadog's tools provided essential per-tenant visibility for their high-cardinality, multi-tenant platform, guiding code and infrastructure decisions. Datadog also helps Zendesk optimize AWS usage in real-time. This led to faster detection and resolution, fewer cross-tenant incidents, right-sized compute/storage, and better customer experience. Attendees will learn how to de-risk migrations and accelerate modernization with Datadog and AWS.
`,
date: 'Tuesday, December 2nd',
time: '1:00 PM—2:00 PM',
venue: 'Wynn',
room: 'Latour 2',
speakers: [{"company":"Zendesk","headshot":"aws-reinvent-2025/speakers/nick-hefty.png","name":"Nick Hefty","title":"Senior Software Engineer"}],
registrationLink: 'https://dtdg.co/session-zendesk',
recorded: false
}">
Zendesk
MAM354 | Finding the Noisy Neighbor: Patterns for Per‑Customer Performance at Scale
Tuesday, December 2nd | 1:00 PM—2:00 PM
Tuesday, December 2nd
1:00 PM—2:00 PM
Venue: Wynn
Room: Latour 2
Session: MAM354
Operational visibility is essential for running AI agents in production. It turns opaque LLM behavior into measurable, improvable workflows. In this session, we’ll walk through building a Strands-based agent, deploying it on Amazon Bedrock AgentCore, and processing telemetry with Datadog LLM Observability. You’ll see end-to-end traces across prompts, tool calls, and multi-agent interactions; improve response quality; tune performance and cost; and apply security and privacy guardrails. Leave with best practices and a runnable reference for production.
`,
date: 'Wednesday, December 3rd',
time: '2:30 PM—3:30 PM',
venue: 'Venetian',
room: 'Murano 3205',
speakers: [{"company":"Datadog","headshot":"aws-reinvent-2025/speakers/kunal-batra.jpeg","name":"Kunal Batra","title":"Senior Technical Advocate"},{"company":"AWS","headshot":"aws-reinvent-2025/speakers/duan-lightfoot.png","name":"Du'An Lightfoot","title":"Senior AI Engineer"}],
registrationLink: 'https://dtdg.co/session-agentcore',
recorded: false
}'>
Datadog
AWS
AIM233 | Build observable AI agents with Strands, AgentCore, and Datadog
Wednesday, December 3rd | 2:30 PM—3:30 PM
Wednesday, December 3rd
2:30 PM—3:30 PM
Venue: Venetian
Room: Murano 3205
Session: AIM233
Security teams face an exponential growth in telemetry data across AWS services, third-party tools, and hybrid infrastructure. The challenge isn't just detecting threats—it's finding the real incidents among millions of daily events without overwhelming your SOC team. Join Riot games and Datadog subject matter experts as we explore battle-tested principles for building effective detection systems at scale. Drawing from real-world implementations at enterprises like Riot Games, we'll demonstrate how to leverage AWS native services alongside Datadog's security platform to create high-fidelity detection rules that actually work.
`,
date: 'Thursday, December 4th',
time: '2:00 PM—3:00 PM',
venue: 'Venetian',
room: 'Murano 3205',
speakers: [{"company":"Datadog","headshot":"aws-reinvent-2025/speakers/andrew-krug.png","name":"Andrew Krug","title":"Manager, Technical Advocacy"},{"company":"Riot Games","headshot":"aws-reinvent-2025/speakers/nathan-pitchaikani.jpg","name":"Nathan Pitchaikani","title":"Senior Security Engineer"}],
registrationLink: 'https://dtdg.co/session-securityoperations',
recorded: false
}'>
Datadog
Riot Games
SEC327 | Detection Engineering at Scale: Building High-Fidelity Security Operations
Thursday, December 4th | 2:00 PM—3:00 PM
Thursday, December 4th
2:00 PM—3:00 PM
Venue: Venetian
Room: Murano 3205
Session: SEC327