Operations | Monitoring | ITSM | DevOps | Cloud

Observability and Security for the AI Era

Datadog has always been driven by a broader vision of helping teams understand and operate complex systems. In this session, you’ll hear from Yrieix Garnier, VP of Product, and Hugo Kaczmarek, Senior Director of Product, as they share the latest updates across the Datadog product suite and discuss how that vision continues to shape the platform’s evolution and support the next generation of AI-driven applications.

Olivier Pomel and Alexis Lê-Quôc on Datadog's origin, AI, and more | This Month in Datadog

Get an insider’s view of Datadog from the people who built it. On a special episode of This Month in Datadog, co-founders Olivier Pomel and Alexis Lê-Quôc sit down for a rare, in-depth look at the challenge that inspired them to build the Datadog platform, what the company is working on today, AI, and more. This Month in Datadog brings you the latest updates on our newest product features, announcements, resources, and events.

Balancing Data Locality, Data Sovereignty, and Data Replication

Modern distributed systems must simultaneously respect where data must live, where it should live for performance, and where it needs to live for resilience. Data sovereignty and residency requirements increasingly affect technical design decisions, not only in regulated industries, but in any global product that must navigate regional expectations, latency constraints, cost structures, and operational realities.

Datadog Data Observability, enables you to detect data quality and pipeline issues early.

See our latest Episode of This Month in Datadog, for a spotlight of Datadog Data Observability, which enables you to detect data quality and pipeline issues early, as well as remediate those issues with end-to-end lineage. We also cover: This Month in Datadog brings you the latest updates on our newest product features, announcements, resources, and events.

Architecting Log Management for Privacy and Scale without the Headache

As companies grow, they inevitably hit a wall: observability data explodes while privacy requirements become stricter. For years, engineers have faced a painful tradeoff—either ship petabytes of sensitive data to a central cloud (incurring egress costs and compliance risks) or manage a complex self-hosted stack that is painful to scale.

Captur: Observability-First Mobile ML Inference for Better Customer Confidence

Captur builds a mobile SDK that brings real-time image recognition and actionable feedback directly into customers’ apps, running complex machine learning models entirely on device without cloud inference. This architecture delivers privacy and performance, but also creates unique challenges when it comes to observability and debugging, especially as crashes can originate from the host app rather than the SDK itself.

Release software with confidence using Datadog Feature Flags

In this technical product demo, see how Datadog Feature Flags helps teams release software with confidence by connecting every feature flag to real-time observability data. Configure progressive, multi-step rollouts with automated guardrails tied to APM, RUM, and Product Analytics so you can pause or roll back instantly if latency, errors, or key business metrics degrade.

Datadog Incident Response: One platform from alert to resolution

When incidents strike, speed and clarity are critical. Datadog Incident Response brings the full incident lifecycle into one platform so teams can move from detection to resolution with confidence. Operate from a single, unified view of your systems, coordinate across the tools your teams already use, and leverage AI that analyzes incidents in real time to surface context, guide decisions, and accelerate resolution.