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.

Setup

Set up Datadog’s Google Cloud integration to collect metrics and logs from your Google Cloud services.

Prerequisites

• If your organization restricts identities by domain, you must add Datadog’s customer identity as an allowed value in your policy. Datadog’s customer identity: C0147pk0i

• Service account impersonation and automatic project discovery relies on you having certain roles and APIs enabled to monitor projects. Before you start, ensure the following APIs are enabled for the projects you want to monitor:

  • Cloud Resource Manager API
  • Google Cloud Billing API
  • Cloud Monitoring API
  • Compute Engine API
  • Cloud Asset API
  • IAM API

Metric collection

Installation

You can use service account impersonation and automatic project discovery to integrate Datadog with Google Cloud.

This method enables you to monitor all projects visible to a service account by assigning IAM roles in the relevant projects. You can assign these roles to projects individually, or you can configure Datadog to monitor groups of projects by assigning these roles at the organization or folder level. Assigning roles in this way allows Datadog to automatically discover and monitor all projects in the given scope, including any new projects that may be added to the group in the future.

1. Create your Google Cloud service account

1. Open your Google Cloud console.
2. Navigate to IAM & Admin > Service Accounts.
3. Click on Create service account at the top.
4. Give the service account a unique name, then click Create and continue.
5. Add the following roles to the service account:
   • Monitoring Viewer
   • Compute Viewer
   • Cloud Asset Viewer
   • Browser
6. Click Continue, then Done to complete creating the service account.

2. Add the Datadog principal to your service account

1. In Datadog, navigate to the Integrations > Google Cloud Platform.
2. Click on Add GCP Account. If you have no configured projects, you are automatically redirected to this page.
3. If you have not generated a Datadog principal for your org, click the Generate Principal button.
4. Copy your Datadog principal and keep it for the next section.
   Keep this window open for the next section.
5. In Google Cloud console, under the Service Acounts menu, find the service account you created in the first section.
6. Go to the Permissions tab and click on Grant Access.

7. Paste your Datadog principal into the New principals text box.
8. Assign the role of Service Account Token Creator and click Save.

Note: If you previously configured access using a shared Datadog principal, you can revoke the permission for that principal after you complete these steps.

3. Complete the integration setup in Datadog

1. In your Google Cloud console, navigate to the Service Account > Details tab. There, you can find the email associated with this Google service account. It resembles <sa-name>@<project-id>.iam.gserviceaccount.com.
2. Copy this email.
3. Return to the integration configuration tile in Datadog (where you copied your Datadog principal in the previous section).
4. In the box under Add Service Account Email, paste the email you previously copied.
5. Click on Verify and Save Account.

In approximately fifteen minutes, metrics appear in Datadog.

4. Assign roles to other projects (optional)

Automatic project discovery simplifies the process of adding additional projects to be monitored. If you grant your service account access to other projects, folders, or orgs, Datadog discovers these projects (and any projects nested in the folders or orgs) and automatically adds them to your integration tile.

1. Make sure you have the appropriate permissions to assign roles at the desired scope:
   • Project IAM Admin (or higher)
   • Folder Admin
   • Organization Admin
2. In the Google Cloud console, go to the IAM page.
3. Select a project, folder, or organization.
4. To grant a role to a principal that does not already have other roles on the resource, click Grant Access, then enter the email of the service account you created earlier.
5. Assign the following roles:
   • Compute Viewer
   • Monitoring Viewer
   • Cloud Asset Viewer Note: The Browser role is only required in the default project of the service account.
6. Click Save.

Configuration

Optionally, you can limit the GCE instances that are pulled into Datadog by entering tags in the Limit Metric Collection textbox under a given project’s dropdown menu. 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.*

See Google’s documentation on Creating and managing labels for more details.

Log collection

Forward logs from your Google Cloud services to Datadog using Google Cloud Dataflow and the Datadog template. This method provides both compression and batching of events before forwarding to Datadog. Follow the instructions in this section to:

1. Create a Pub/Sub topic and pull subscription to receive logs from a configured log sink
2. Create a custom Dataflow worker service account to provide least privilege to your Dataflow pipeline workers
3. Create a log sink to publish logs to the Pub/Sub topic
4. Create a Dataflow job using the Datadog template to stream logs from the Pub/Sub subscription to Datadog

You have full control over which logs are sent to Datadog through the logging filters you create in the log sink, including GCE and GKE logs. See Google’s Logging query language page for information about writing filters.

Note: You must enable the Dataflow API to use Google Cloud Dataflow. See Enabling APIs in the Google Cloud documentation for more information.

To collect logs from applications running in GCE or GKE, you can also use the Datadog Agent.

1. Create a Cloud Pub/Sub topic and subscription

1. Go to the Cloud Pub/Sub console and create a new topic. Select the option Add a default subscription to simplify the setup.

   Note: You can also manually configure a Cloud Pub/Sub subscription with the Pull delivery type. If you manually create your Pub/Sub subscription, leave the Enable dead lettering box unchecked. For more details, see Unsupported Pub/Sub features.

2. Give that topic an explicit name such as export-logs-to-datadog and click Create.

3. Create an additional topic and default subscription to handle any log messages rejected by the Datadog API. The name of this topic is used within the Datadog Dataflow template as part of the path configuration for the outputDeadletterTopic template parameter. When you have inspected and corrected any issues in the failed messages, send them back to the original export-logs-to-datadog topic by running a Pub/Sub to Pub/Sub template job.

4. Datadog recommends creating a secret in Secret Manager with your valid Datadog API key value, for later use in the Datadog Dataflow template.

Warning: Cloud Pub/Subs are subject to Google Cloud quotas and limitations. If the number of logs you have exceeds those limitations, Datadog recommends you split your logs over several topics. See the Monitor the Pub/Sub Log Forwarding section for information on setting up monitor notifications if you approach those limits.

2. Create a custom Dataflow worker service account

The default behavior for Dataflow pipeline workers is to use your project’s Compute Engine default service account, which grants permissions to all resources in the project. If you are forwarding logs from a Production environment, you should instead create a custom worker service account with only the necessary roles and permissions, and assign this service account to your Dataflow pipeline workers.

1. Go to the Service Accounts page in the Google Cloud console and select your project.
2. Click CREATE SERVICE ACCOUNT and give the service account a descriptive name. Click CREATE AND CONTINUE.
3. Add the roles in the required permissions table and click DONE.

Required permissions

Note: If you don’t create a custom service account for the Dataflow pipeline workers, ensure that the default Compute Engine service account has the required permissions above.

3. Export logs from Google Cloud Pub/Sub topic

1. Go to the Logs Explorer page in the Google Cloud console.

2. From the Log Router tab, select Create Sink.

3. Provide a name for the sink.

4. Choose Cloud Pub/Sub as the destination and select the Cloud Pub/Sub topic that was created for that purpose. Note: The Cloud Pub/Sub topic can be located in a different project.

5. Choose the logs you want to include in the sink with an optional inclusion or exclusion filter. You can filter the logs with a search query, or use the sample function. For example, to include only 10% of the logs with a severity level of ERROR, create an inclusion filter with severity="ERROR" AND sample(insertId, 0.01).

6. Click Create Sink.

Note: It is possible to create several exports from Google Cloud Logging to the same Cloud Pub/Sub topic with different sinks.

4. Create and run the Dataflow job

1. Go to the Create job from template page in the Google Cloud console.

2. Give the job a name and select a Dataflow regional endpoint.

3. Select Pub/Sub to Datadog in the Dataflow template dropdown, and the Required parameters section appears.
   a. Select the input subscription in the Pub/Sub input subscription dropdown.
   b. Enter the following in the Datadog Logs API URL field:

   https://
   

   Note: Ensure that the Datadog site selector on the right of the page is set to your Datadog site before copying the URL above.

   c. Select the topic created to receive message failures in the Output deadletter Pub/Sub topic dropdown.
   d. Specify a path for temporary files in your storage bucket in the Temporary location field.

4. If you created a secret in Secret Manager with your Datadog API key value as mentioned in step 1, enter the resource name of the secret in the Google Cloud Secret Manager ID field.

See Template parameters in the Dataflow template for details on using the other available options:

• apiKeySource=KMS with apiKeyKMSEncryptionKey set to your Cloud KMS key ID and apiKey set to the encrypted API key
• Not recommended: apiKeySource=PLAINTEXT with apiKey set to the plaintext API key

5. If you created a custom worker service account, select it in the Service account email dropdown.

6. Click RUN JOB.

Note: If you have a shared VPC, see the Specify a network and subnetwork page in the Dataflow documentation for guidelines on specifying the Network and Subnetwork parameters.

Validation

New logging events delivered to the Cloud Pub/Sub topic appear in the Datadog Log Explorer.

Note: You can use the Google Cloud Pricing Calculator to calculate potential costs.

Monitor the Cloud Pub/Sub log forwarding

The Google Cloud Pub/Sub integration provides helpful metrics to monitor the status of the log forwarding:

• gcp.pubsub.subscription.num_undelivered_messages for the number of messages pending delivery
• gcp.pubsub.subscription.oldest_unacked_message_age for the age of the oldest unacknowledged message in a subscription

Use the metrics above with a metric monitor to receive alerts for the messages in your input and deadletter subscriptions.

Monitor the Dataflow pipeline

Use Datadog’s Google Cloud Dataflow integration to monitor all aspects of your Dataflow pipelines. You can see all your key Dataflow metrics on the out-of-the-box dashboard, enriched with contextual data such as information about the GCE instances running your Dataflow workloads, and your Pub/Sub throughput.

You can also use a preconfigured Recommended Monitor to set up notifications for increases in backlog time in your pipeline. For more information, read Monitor your Dataflow pipelines with Datadog in the Datadog blog.

Data Collected

Metrics

See the individual Google Cloud integration pages for metrics.

Cumulative metrics

Cumulative metrics are imported into Datadog with a .delta metric for each metric name. A cumulative metric is a metric where the value constantly increases over time. For example, a metric for sent bytes might be cumulative. Each value records the total number of bytes sent by a service at that time. The delta value represents the change since the previous measurement.

For example:

gcp.gke.container.restart_count is a CUMULATIVE metric. While importing this metric as a cumulative metric, Datadog adds the gcp.gke.container.restart_count.delta metric which includes the delta values (as opposed to the aggregate value emitted as part of the CUMULATIVE metric). See Google Cloud metric kinds for more information.

Events

All service events generated by your Google Cloud Platform are forwarded to your Datadog Events Explorer.

Service Checks

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

Tags

Tags are automatically assigned based on a variety of Google Cloud Platform and Google Compute Engine configuration options. The project_id tag is added to all metrics. Additional tags are collected from the Google Cloud Platform when available, and varies based on metric type.

Additionally, Datadog collects the following as tags:

• Any hosts with <key>:<value> labels.
• Custom labels from Google Pub/Sub, GCE, Cloud SQL, and Cloud Storage.

Troubleshooting

Incorrect metadata for user defined gcp.logging metrics?

For non-standard gcp.logging metrics, such as metrics beyond Datadog’s out of the box logging metrics, the metadata applied may not be consistent with Google Cloud Logging.

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.

Further reading

Additional helpful documentation, links, and articles:

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