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Monitor Google Cloud Run with Datadog

Author Daniel Langer
/ / / /
Published: April 9, 2019

Google Cloud Run is a new compute platform for running stateless containers without having to manage the underlying infrastructure. You can choose between a fully managed version of Cloud Run, or run container workloads in your existing Google Kubernetes Engine (GKE) clusters with Cloud Run on GKE. With Cloud Run, deploying is as easy as specifying a container image, along with settings such as environment variables, memory limits, and concurrency, or the maximum number of requests that can be sent to a container instance at any time.

Datadog is proud to be a launch partner for Cloud Run and Cloud Run on GKE at Google Cloud Next ‘19, and we are excited to provide visibility for our customers who are adopting serverless container workloads. In this post, we’ll show you how you can monitor both flavors of Cloud Run with Datadog.

Taking GKE to the next level

Google Cloud Run is powered by Knative, a Kubernetes-based open API and runtime environment for serverless computing. And because Cloud Run on GKE runs Kubernetes under the hood, you can use Datadog’s Google Cloud and Kubernetes integrations to monitor your Cloud Run services. (Note: when deploying the Datadog Agent DaemonSet, make sure hostNetwork: true is set within the pod spec.)

Once you integrate Cloud Run on GKE with Datadog, you’ll automatically see data from your cluster streaming into Datadog. You can collect metrics, traces, and logs from across your cluster, and you’ll see every container in your environment in the Live Container view. You can search and filter your container fleet using tags that we ingest automatically from Google Cloud and Kubernetes, or you can inspect any individual container to see high-resolution CPU and memory metrics, real-time container logs, and the full process tree running inside the container.

A detailed view of a Google Cloud Run container in Datadog

No nodes, no problem

If you use the fully managed version of Cloud Run, Google Cloud manages and automatically scales the underlying infrastructure needed to handle your application’s load. Since the servers powering your service aren’t exposed, the Datadog integration gathers metrics and logs via brand-new integrations with Google Cloud monitoring APIs rather than from the Datadog Agent. Whichever flavor of Cloud Run you choose, Datadog provides comprehensive visibility into your container workloads.

Once you install the Google Cloud integration, metrics for your Cloud Run revisions (deployments of a specific service) will be available in Datadog under the gcp.run.* namespace. You can group, filter, and query your Cloud Run metrics using automatically generated tags such as region, configuration_name, revision_name, and service_name, and visualize them alongside data from the rest of your Google Cloud environment.

Audit logs

Cloud Run also exposes rich audit logs so you can keep close tabs on the activity surrounding your services, revisions, and configurations. You can send these logs into Datadog using our Stackdriver Logs integration, so you can monitor and analyze them alongside the logs from the rest of your Google Cloud services.

Datadog’s prebuilt processing pipeline for Cloud Run logs automatically parses out important attributes from your logs so you can search, filter, and group them by the data that matters to you most.

Get started today

Whether you’re building new workloads on top of Google Cloud Run or migrating existing Kubernetes workloads to Cloud Run on GKE, you can start monitoring your containers and services in minutes by setting up our Cloud Run integration. Visit our documentation for Cloud Run or Cloud Run on GKE to get started.

If you aren’t already using Datadog to monitor your infrastructure and applications, you can .