Operations | Monitoring | ITSM | DevOps | Cloud

How we created a single app to automate repetitive tasks with Datadog Workflow Automation, Datastore, and App Builder

For many organizations, scaling up their systems means incorporating new tools to build out infrastructure, optimize code performance and security, improve communication, and track cost changes. While these changes are necessary to support an increased workload, they often result in a situation where even the most basic tasks involve switching between multiple platforms.

Why GovRAMP-authorized observability matters for state, local, and education IT teams

Building on our FedRAMP Moderate authorization and our “In Process” status for FedRAMP High, Datadog for Government is now "In Process" for GovRAMP High Authorization, giving agencies a unified observability platform that meets the toughest public-sector security bars.

Built for Engineers: Datadog's Vision for the Future

Datadog was built by engineers, for engineers. At, Datadog Co-founder & CEO Olivier Pomel opened the keynote with a clear message: observability, security and AI are converging. From infrastructure to AI Agents, the future of engineering requires one unified platform. Catch all product announcements to see what’s next in observability and security on our Youtube channel!

How we've created a successful FinOps practice at Datadog

When you adopt FinOps to maximize the value of your cloud spending, you may have some simple first steps you can take to gain cost efficiency. For example, you can find and delete any unused resources to quickly realize a one-time optimization. But the ongoing work to manage cloud costs becomes complex as your organization grows, your infrastructure spans multiple clouds, and you can't easily see the full value of your cloud spending by tracking only the bottom line.

Route your monitor alerts with Datadog monitor notification rules

As organizations scale their infrastructure, monitoring systems can become a source of noise rather than insight. A clean, straightforward set of alerts for a handful of services can quickly spiral into a mess of overlapping thresholds, redundant triggers, and inconsequential notifications across hundreds (or thousands) of components. This flood of notifications can slow response times, overwhelm engineers, and increase the chance of overlooking critical problems.

Improve SLO accuracy and performance with Datadog Synthetic Monitoring

SLOs are key for improving user satisfaction, prioritizing engineering projects, and measuring overall performance. Given the important role that SLOs play in determining organizational benchmarks, teams need to ensure that SLO metrics—also called service level indicators (SLIs)—are reported accurately and maintained consistently within an acceptable range.

Trace Distributed Map states for AWS Step Functions with Datadog

AWS Step Functions offers the Distributed Map state, enabling you to coordinate massively parallel workloads within your serverless applications. With this feature, a single Step Functions execution can fan out into up to 10,000 parallel workflows simultaneously, making it possible to efficiently process millions of items in parallel. This capability unlocks new possibilities for large-scale data processing, such as image transformation, log ingestion, or batch analytics.

Stay Compliant: Meet Your Audit Needs with Datadog!

Datadog's internal compliance team has built audit workflows and control monitoring capabilities using the Datadog platform. We actively use these capabilities to scale our audit programs and comply with multiple compliance frameworks. This session will go into the details of how we addressed our compliance use-cases using the Datadog platform and how our customers can get started.

How Cursor scaled infrastructure rapidly and reliably using Datadog

At Datadog, we use Cursor to empower our teams to build more quickly. And we know that building and troubleshooting with AI tools like Cursor is done best with the right observability data and context. Discover how Cursor was able to rapidly and reliably scale their infrastructure 100x using Datadog to meet the needs of a fast growing user base. And learn more about how we’re bring Datadog tools and context to your favorite AI IDEs and agents with our MCP Server and extensions.

AI-Augmented Control Plane: Scaling IT Operations with Intelligent Automation

How do you enable a team of 100 engineers to effectively support 300+ critical applications across five hosting platforms? At Thomson Reuters, we turned to AI - not as a buzzword, but as a genuine force multiplier. Experience our journey of transforming traditional IT operations into an AI-augmented powerhouse, where Datadog, ServiceNow, and custom AI solutions work in harmony to create a next-generation control plane. We'll share real victories, honest challenges, and practical insights from our mission to build a more intelligent operational framework.