As AI adoption accelerates on Google Cloud, the challenge for most teams today is no longer just building AI-powered applications. It’s also managing the full AI stack from end to end, including data pipelines, infrastructure, release process, and security operations. Many teams are monitoring these layers with different tools, creating complexity, fragmenting visibility, and slowing decisions on what to do next.
Addressing these challenges is at the heart of Datadog’s long-standing collaboration with Google Cloud. And as a recipient of two 2026 Google Cloud Partner of the Year awards in the categories of AIOps (Technology) and Infrastructure Modernization (Marketplace), Datadog is thrilled to be on site at Google Cloud Next this year.
In this post, we’ll show how Datadog gives teams building AI applications and agents on Google Cloud a single platform to:
Evaluate and troubleshoot AI applications and agentsOptimize cost and performance across GPUs and TPUsImprove data reliability and visibility across your Google Cloud AI stackStrengthen security with AI-powered investigation and response
Evaluate and troubleshoot AI applications and agents on Google Cloud
