Unlocking Observability:
Understanding Google Kubernetes Engine With Datadog
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In containerized environments, organizations depend on Kubernetes for automated scaling and application deployment management. Kubernetes enhances deployment agility, leading to reduced operating costs. By integrating with your containerized environments, Datadog facilitates seamless monitoring of Kubernetes and container performance in real-time.


As the complexity of managing Kubernetes at scale continues to rise, organizations are seeking assistance from cloud providers such as Google Cloud. Google Cloud offers comprehensive solutions like Google Anthos for Kubernetes management and GKE for cluster autoscaling management.


Join experts from Google Cloud and Scott Mabe from Datadog, to learn more about:

  • Building a platform on Google Cloud and achieving operational excellence in containerized environments
  • Scaling infrastructure in dynamic environments and building applications with Datadog and Kubernetes
  • How to use Datadog to address the challenges of distributed application monitoring and logging

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Scott Mabe

Scott Mabe

Technical Ad

Scott Mabe is a Technical Advocate at Datadog, and lives in Baltimore Maryland. He likes to enjoy things and loves learning. Scott has been working in cloud computing since 2012 and loves dogs. When he’s not working Scott enjoys traveling to see punk rock shows.

Gari Singh-modified

Gari Singh

Product Manager - Google

Gari Singh is a Product Manager at Google based in Cambridge, MA.  He is focused on driving the adoption of Google’s Managed Container offerings (GKE, Cloud Run) across all industries and pushing the adoption of OSS technologies such as Kubernetes.

Before joining Google, Gari was the CTO, Director of Engineering and Director of Product Management for blockchain at IBM.  He was responsible for the IBM Blockchain Platform, which is based on the open source Hyperledger Fabric technology.  He continues to be a core maintainer for Hyperledger Fabric.