Operations | Monitoring | ITSM | DevOps | Cloud

Discover how Datadog APM & Continuous Profiler can help you identify the most resource-intensive and time-consuming lines of code. Through always-on production code profiling and thread-level visibility, you can reduce application latency, optimize your code's CPU and memory consumption, and minimize cloud costs.

Datadog is constantly elevating the approach to cloud monitoring and security. This Month in Datadog updates you on our newest product features, announcements, resources, and events. This month, we put the Spotlight on a trio of serverless monitoring releases..

Hear from a Statsig software engineer how Datadog’s platform helps them better manage their increasing data volume and improve the experiences of their global end users.

Datadog Cloud Cost Management brings fine-grained cost data that’s scoped to teams and services onto the same monitoring platform engineers already use, so costs can be understood alongside observability data and made actionable.

Learn how to debug slow p95 requests or timeouts using the new timeline feature of Datadog's Continuous Profiler.

Datadog is constantly elevating the approach to cloud monitoring and security. This Month in Datadog updates you on our newest product features, announcements, resources, and events. This month, we’re recapping DASH 2023..

Understanding the health and user experience of your mobile application is critical in order to avoid user frustration, understand application crashes, and reduce bugs mean time to resolution. To help with that task, Datadog has a mobile monitoring solution that allows developers to better understand and improve their application. But what are the things to take into account when building observability mobile SDKs? How can we gather the right telemetry without affecting the underlying application?

Datadog provides full visibility into your AWS-hosted infrastructure and applications at scale. This demo shows you how Datadog monitors and secures your AWS environment in minutes with powerful observability features, such as preconfigured dashboards and monitors, faster troubleshooting with machine learning, and a single unified platform.

One of the biggest challenges in observability is separating the signal from the noise. As artificial intelligence (AI) tools become more powerful and accessible, it has generated a lot of buzz around the role of AI with respect to the performance and reliability of our technical systems and the teams that build and operate them. In this fireside chat, Michael Gertenhaber (Datadog VP of Product) and Sajid Mehmood (Datadog VP of Engineering) will sift through the hype to chat about what generative AI and Large Language Models (LLMs) will really mean for the future of observability and how it can benefit your teams today.

WIth unlimited money, most technology problems become easy to solve. But how do you design, build, and operate large scale, performant systems without breaking the bank? In this session, Chandru Subramanian (Director of Engineering, Runtime Efficiency at Datadog) and Neil Innes (Sr. Engineering Manager, DevOps at FanDuel) will discuss how they balance efficiency and effectiveness to save money while also meeting key goals.