Operations | Monitoring | ITSM | DevOps | Cloud

Data Observability: Build confidence in the data life cycle

Datadog Data Observability provides a complete solution with quality checks (e.g., volume, row changes, freshness), custom SQL-based monitors, anomaly detection, column-level lineage across systems like Snowflake and Tableau, full pipeline visibility, and targeted alerts when data issues arise.

Explore Cloud Instance Pricing and Performance with Datadog Instance Explorer

Meet Datadog Instance Explorer — a way to explore, compare, and monitor cloud instance pricing and performance across AWS, Azure, and Google Cloud in one place. In this quick overview, you’ll learn how to: Start exploring your instance options today and make smarter, data-driven infrastructure decisions.

Datadog GPU Monitoring: Optimize and troubleshoot AI infrastructure

With Datadog GPU Monitoring, engineering and ML teams can monitor GPU fleet health across cloud, on-prem, and GPU-as-a-Service platforms like Coreweave and Lambda Labs. Real-time insights into allocation, utilization, and failure patterns make it easy to spot bottlenecks, eliminate idle GPU spend, and resolve provisioning gaps. By tying usage metrics directly to cost and surfacing hardware and networking issues impacting performance, Datadog helps teams make fast, cost-efficient decisions to keep AI workloads running reliably at scale.

Bringing Observability to Data

While observability practices have evolved in recent years, they have largely focused on application services and infrastructure. Yet it is data what powers our applications, businesses, and AI models. When data issues occur, the consequences can be far reaching, from poor product experiences to billing errors to misinformed AI outcomes. In this session, Jonathan Morin, Group Product Manager at Datadog, shares real-world examples of incidents and explains how data observability can address them, helping teams detect issues earlier, reduce costly downtime, and restore trust in their data.

The Hidden Bottleneck in Latency: GetYourGuide's Database Performance Journey

Fast front-end and back-end code alone won’t guarantee low end-to-end latency as hidden bottlenecks in the database can undermine even the best engineering efforts. In this session, Oleksii Serhiienko, Senior Site Reliability Engineer at GetYourGuide, will share how his team put database performance at the center of their monitoring strategy. He will highlight how they identified and fixed slow queries, uncovered load balancing issues that drove significant cost savings, and built monitoring practices that improved both reliability and investigation workflows.

Use Grok parsing to extract fields from logs | Datadog Tips & Tricks

When your logs don’t follow a standard format, it can be difficult to extract valuable information, like key-value pairs and nested JSON objects. Grok parsing lets you define flexible patterns that match unstructured log data so you can extract specific fields to query, filter, and visualize. In this video, you’ll learn how to: By refining your Grok parsers, you can make your logs more useful for analytics, dashboards, or alerts, and get even more value from your logs.

Bits AI SRE, Flex Frozen, and GPU Monitoring | DASH 2025

Get a first look at Datadog’s biggest product reveals from DASH 2025. Meet Bits AI SRE, your 24/7 autonomous AI Site Reliability Engineer, Flex Frozen for up to 7 years of managed log retention, and GPU Monitoring for full visibility into your AI workloads. Experience the future of observability in action.

Triaging an Incident with a Critical Data Pipeline at #rivian

Rivian makes electric vehicles to advance its mission to keep the world adventurous forever. As software defined vehicles, Rivian’s R1T and R1S are connected to the cloud from day 1, and telemetry data is at the heart of enabling mobile notifications, remote diagnostics, fleet management, and more. With so many critical pipelines in the cloud, observability is a top priority for the data platform.

Safely Roll Out Features with Datadog Feature Flags

In this short demo, see how Datadog Feature Flags help teams release new functionality safely and efficiently. Datadog provides advanced targeting, progressive rollouts, and automatic rollbacks — all integrated with powerful observability data. Learn how you can use simple on–off flags or multi-variant configurations to test and deploy features with confidence. With built-in monitoring of key guardrail metrics, Datadog can automatically pause or reverse rollouts when issues are detected, keeping your releases stable.

Building Smarter AI Products #Datadog #DASH #AI

AI capabilities are advancing faster than ever — transforming how teams design, build, and ship intelligent products. In this teaser from Building Successful AI-powered Products at Datadog DASH, experts discuss the rise of agent-based systems, evolving model capabilities, and how to stay ahead in the new era of automation.