Google Cloud Platform

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Overview

Connect to Google Cloud Platform to see all your Google Compute Engine (GCE) hosts in Datadog. You can see your hosts in the infrastructure overview in Datadog and sort through them, since Datadog automatically tags them with GCE host tags and any GCE labels you may have added.

Related integrations include:

Integration	Description
App Engine	PaaS (platform as a service) to build scalable applications
Big Query	Enterprise data warehouse
Bigtable	NoSQL Big Data database service
CloudSQL	MySQL database service
Cloud APIs	Programmatic interfaces for all Google Cloud Platform services
Cloud Composer	A fully managed workflow orchestration service
Cloud Dataproc	A cloud service for running Apache Spark and Apache Hadoop clusters
Cloud Filestore	High-performance, fully managed file storage
Cloud Firestore	A flexible, scalable database for mobile, web, and server development
Cloud Interconnect	Hybrid connectivity
Cloud IoT	Secure device connection and management
Cloud Load Balancing	Distribute load-balanced compute resources
Cloud Memorystore for Redis	A fully managed in-memory data store service
Cloud Router	Exchange routes between your VPC and on-premises networks by using BGP
Cloud Run	Managed compute platform that runs stateless containers through HTTP
Cloud Tasks	Distributed task queues
Cloud TPU	Train and run machine learning models
Compute Engine	High performance virtual machines
Container Engine	Kubernetes, managed by google
Datastore	NoSQL database
Firebase	Mobile platform for application development
Functions	Serverless platform for building event-based microservices
Machine Learning	Machine learning services
Pub/Sub	Real-time messaging service
Spanner	Horizontally scalable, globally consistent, relational database service
Stackdriver Logging	Real-time log management and analysis
Storage	Unified object storage
VPN	Managed network functionality

Setup

Metric Collection

Installation

The Datadog <> Google Cloud integration uses Service Accounts to create an API connection between Google Cloud and Datadog. Below are instructions for creating a service account and providing Datadog with service account credentials to begin making API calls on your behalf.

Navigate to the Google Cloud credentials page for the Google Cloud project where you would like to setup the Datadog integration.
Press Create credentials and then select Service account key.
In the Service account dropdown, select New service account.
Give the service account a unique name.
For Role, select Compute engine —> Compute Viewer, Monitoring —> Monitoring Viewer, and Cloud Asset —> Cloud Asset Viewer
Note: You must be a Service Account Key Admin to select Compute Engine and Cloud Asset roles. All selected roles allow Datadog to collect metrics, tags, events, and user labels on your behalf.
Select JSON as the key type, and press create. Take note where this file is saved, as it is needed to complete the installation.
Navigate to the Datadog Google Cloud Integration tile.
On the Configuration tab, select Upload Key File to integrate this project with Datadog.
Optionally, you can use tags to filter out hosts from being included in this integration. Detailed instructions on this can be found below.
Press Install/Update.
If you want to monitor multiple projects, use one of the following methods:
- Repeat the process above to use multiple service accounts.
- Use the same service account by updating the project_id in the JSON file downloaded in step 6. Then upload the file to Datadog as described in steps 7-10.

Google Cloud billing, the Stackdriver Monitoring API, the Compute Engine API, and the Cloud Asset API must all be enabled for the project(s) you wish to monitor.

Configuration

Optionally, you can limit the GCE instances that are pulled into Datadog by entering tags in the Limit Metric Collection textbox. Only hosts that match one of the defined tags are imported into Datadog. You can use wildcards (? for single character, * for multi-character) to match many hosts, or ! to exclude certain hosts. This example includes all c1* sized instances, but excludes staging hosts:

datadog:monitored,env:production,!env:staging,instance-type:c1.*

Log Collection

For applications running in GCE or GKE, the Datadog Agent can be used to collect logs locally. GCP service logs are collected via Stackdriver and sent to a Cloud Pub/Sub with a HTTP Push forwarder. The log collection requires 5 steps:

If you haven’t already, set up the Google Cloud platform integration first.
Create a new Cloud Pub/Sub.
Setup the Pub/Sub to forward logs to Datadog.
Configure exports from Stackdriver logs to the Pub/Sub.

Warning: Pub/subs are subject to Google Cloud quotas and limitations. If the number of logs you have is higher than those limitations, Datadog recommends you split your logs over several subscriptions. See the Monitor the Log Forwarding section for information on how to set up a monitor to be automatically notified if you get close to those limits.

Create a Cloud Pub Sub

Go to the Cloud Pub Sub console and create a new topic.
Give that topic an explicit name such as export-logs-to-datadog and Save.

Configure the Pub/Sub to forward logs to Datadog

Dropdown

Go back to the Pub/Sub that was previously created, and add a new subscription:
Select the Push method and enter the following: https://gcp-intake.logs.datadoghq.com/v1/input/<DATADOG_API_KEY>/
Hit Create at the bottom.

The Pub/Sub is now ready to receive logs from Stackdriver and forward them to Datadog.

Go back to the Pub/Sub that was previously created, and add a new subscription:
Select the Push method and enter the following: https://gcp-intake.logs.datadoghq.eu/v1/input/<DATADOG_API_KEY>/
Hit Create at the bottom.

The Pub/Sub is now ready to receive logs from Stackdriver and forward them to Datadog.

Export logs from Stackdriver to the Pub/Sub

Go to the Stackdriver page and filter the logs that need to be exported.
Hit Create Export and name the sink accordingly.
Choose Cloud Pub/Sub as the destination and select the Pub/Sub that was created for that purpose. Note that the Pub/Sub can be located in a different project.
Hit Create and wait for the confirmation message to show up.

Note: It is possible to create several exports from Stackdriver to the same Pub/Sub with different sinks.

Warning: Pub/subs are subject to Google Cloud quotas and limitations. If the number of logs you have is higher than those limitations, Datadog recommends you split your logs over several subscriptions. See the Monitor the Log Forwarding section for information on how to setup a monitor to be automatically notified if you get close to those limits.

Monitor the Log Forwarding

Pub/subs are subject to Google Cloud quotas and limitations. If the number of logs you have is higher than those limitations, Datadog recommends you split your logs over several subscriptions.

To be automatically notified when you reach this quota, activate the Pub/Sub metric integration and set up a monitor on the metric gcp.pubsub.subscription.backlog_bytes. Filter this monitor on the subscription that exports logs to Datadog to make sure it never goes above 1MB, as per the below example:

Data Collected

Metrics

See the individual Google Cloud integration pages for metrics.

Events

All service events generated by your Google Cloud Platform are forwarded to your Datadog event stream.

Service Checks

The Google Cloud Platform integration does not include any service checks.

Troubleshooting

Incorrect metadata for user defined gcp.logging metrics?

For non-standard gcp.logging metrics (i.e. metrics beyond Datadog’s out of the box logging metrics), the metadata applied may not be consistent with Stackdriver.

In these cases, the metadata should be manually set by navigating to the metric summary page, searching and selecting the metric in question, and clicking the pencil icon next to the metadata.

Need help? Contact Datadog support.