Build and operate the data processing systems behind analytics and ML on Google Cloud, including BigQuery, Dataflow, and Pub/Sub, and track your readiness for the Professional Data Engineer exam.
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Google Cloud service
Cloud DNS
Topic in 2 exam domains
Also called: Google Cloud DNS, managed DNS services
A managed DNS service in Google Cloud used to host private zones and create DNS records for endpoint resolution.
Where this appears on the exam
2 objectives in 2 of 5 domains
Related topics
FoundationsThis topicBuilds on theseBuilds on theseAppliedIdentity and Access ManagementServiceVPC Service ControlsService
Cloud DNSService
Cloud MonitoringServiceBigQueryServiceArtifact RegistryServiceWorkflowsServiceCompute EngineServiceCloud RunServiceCloud SQLServiceGKEServiceDataflowServicewrite endpointFeaturePoints to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
- Cloud DNS works with GKE From the official documentation: “To create a new managed private zone using Cloud DNS for the GKE cluster, complete the following step.”
- Cloud DNS works with Identity and Access Management From the official documentation: “Cloud DNS supports IAM permissions at the project level and individual DNS zone level.”
- VPC Service Controls secures Cloud DNS From the official documentation: “You can use VPC Service Controls to secure your Cloud DNS configuration.”
- Cloud DNS works with Cloud Monitoring From the official documentation: “Cloud DNS exports monitoring metrics to [Cloud Monitoring](/monitoring/docs/monitoring-overview).”
- Cloud DNS works with Compute Engine From the official documentation: “Cloud DNS uses the following procedure to answer queries from Compute Engine virtual machine (VM) instances and Google Kubernetes Engine (GKE) nodes.”
- Cloud DNS depends on Identity and Access Management From the official documentation: “Therefore, you must have the proper IAM roles and permissions to use managed DNS services in GDC.”
- Compute Engine depends on Cloud DNS From the official documentation: “Configure Cloud DNS to forward DNS requests for your Windows domain to your Windows DNS servers to enable your Google Cloud Compute Engine virtual machines to resolve Active Directory hostnames, like the Netbios name used by Google Cloud NetApp Volumes.”
- Identity and Access Management secures Cloud DNS From the official documentation: “Cloud DNS uses Identity and Access Management (IAM) for authorization.”
- write endpoint depends on Cloud DNS From the official documentation: “If you don't enable the Cloud DNS API for your Google Cloud project, and then you create, promote, or upgrade your instance, Cloud SQL doesn't assign the write endpoint to the instance automatically.”
- BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
- BigQuery works with Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
- Cloud Run works with Cloud SQL From the official documentation: “Learn how to connect to Cloud SQL from Cloud Run”
- VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
- BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
- Cloud SQL works with Compute Engine From the official documentation: “Create a Compute Engine VM Instance to host a sample web app that connects to Cloud SQL.”
- Compute Engine is an alternative to GKE From the official documentation: “To use TPU7x, you can use Google Kubernetes Engine (GKE) or Compute Engine.”
- Cloud Monitoring works with Cloud SQL From the official documentation: “You can also get more details by viewing the Cloud Monitoring logs for your Cloud SQL destination instance.”
- Cloud Monitoring works with GKE From the official documentation: “Enable Cloud Monitoring on GKE Clusters”
- Cloud SQL works with Identity and Access Management From the official documentation: “This page describes how Cloud SQL is integrated with IAM .”
- Cloud Run is an alternative to GKE From the official documentation: “The app uses Cloud SQL, Vertex AI, and either Google Kubernetes Engine (GKE) or Cloud Run.”
- Cloud Run works with Workflows From the official documentation: “Route Workflows events to Cloud Run”
- Cloud SQL depends on Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
- Artifact Registry works with Cloud Run From the official documentation: “Cloud Run recommends using Artifact Registry.”
- Cloud Monitoring works with Dataflow From the official documentation: “Dataflow is fully integrated with Cloud Monitoring.”
- Cloud SQL works with GKE From the official documentation: “[From an application running on GKE](/sql/docs/postgres/connect-kubernetes-engine)”
- Identity and Access Management secures BigQuery From the official documentation: “Access to BigQuery data from AlloyDB is managed through IAM.”
- Artifact Registry works with Compute Engine From the official documentation: “Compute Engine can pull containers directly from Artifact Registry repositories.”
- Artifact Registry works with GKE From the official documentation: “In the next tutorial, you deploy those images from the Artifact Registry repository to a GKE cluster:”
- BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
- GKE depends on Compute Engine From the official documentation: “For example, GKE deploys clusters on Compute Engine VMs.”
- VPC Service Controls secures Artifact Registry From the official documentation: “If your VPC Service Controls settings are blocking access to Artifact Registry, you must add the Artifact Registry service to the service perimeter of your VPC Service Controls.”
- VPC Service Controls secures Cloud SQL From the official documentation: “VPC Service Controls perimeters protect the Cloud SQL Admin API.”
- BigQuery works with Cloud Run From the official documentation: “You can then use Cloud Run to transcode data present in the bucket and move it to BigQuery.”
- BigQuery works with Workflows From the official documentation: “To learn more about using Workflows with BigQuery, see [Run multiple BigQuery jobs in parallel](/workflows/docs/tutorials/bigquery-parallel-jobs).”
- Cloud Monitoring works with Cloud Run From the official documentation: “Cloud Monitoring records metrics regarding the execution of Cloud Run.”
- Cloud Monitoring works with Compute Engine From the official documentation: “Many Google services like Compute Engine send telemetry to Cloud Monitoring.”
- Cloud Run works with GKE From the official documentation: “Leverage Google Kubernetes Engine (GKE) and Cloud Run to deploy applications to the Google Cloud, optimizing costs, performance, and management overhead.”
- Cloud Run works with Identity and Access Management From the official documentation: “Cloud Run also offers the ability to control access to a service with Identity and Access Management (IAM).”
- Dataflow depends on Compute Engine From the official documentation: “When you run your pipeline on the Dataflow service, Dataflow creates Compute Engine instances to run your pipeline code.”
- Identity and Access Management secures Compute Engine From the official documentation: “Compute Engine uses Identity and Access Management (IAM) for authorization.”
- Identity and Access Management works with VPC Service Controls From the official documentation: “VPC Service Controls perimeters and Identity and Access Management (IAM) roles work together.”
- Identity and Access Management secures Workflows From the official documentation: “This page describes the Identity and Access Management (IAM) roles and permissions available to control access to Workflows resources.”
- VPC Service Controls secures Compute Engine From the official documentation: “To further protect your Compute Engine resources, you can protect them using [VPC Service Controls](/vpc-service-controls/docs/overview).”
- VPC Service Controls works with Workflows From the official documentation: “You can use VPC Service Controls with Workflows to help protect your services.”
- write endpoint is part of Cloud SQL From the official documentation: “A write endpoint is available only for Cloud SQL Enterprise Plus edition instances that have private IP addresses and associated networks.”
- Artifact Registry works with Cloud Monitoring From the official documentation: “By default, Artifact Registry is configured to do the following: - Send system logs and audit logs to Cloud Logging - Send system metrics and resource metrics to Cloud Monitoring”
- Artifact Registry secures Cloud Run From the official documentation: “You can use Artifact Registry together with other Google Cloud products and features to improve the security posture of developer workflows and tools, software dependencies, CI/CD systems used to build and deploy your software, and runtime environments such as Google Kubernetes…”
- Artifact Registry works with Dataflow From the official documentation: “To use Artifact Registry with Dataflow, you must grant at least [Artifact Registry Writer access](/artifact-registry/docs/access-control#permissions) (`role/artifactregistry.writer`) to the [worker service account](#worker-service-account) that runs the Dataflow job.”
- BigQuery works with Compute Engine From the official documentation: “Compute Engine integrates with Google Cloud technologies such as Cloud Storage, Google Kubernetes Engine, and BigQuery, to extend beyond the basic computational capability to create more complex and sophisticated applications.”
- BigQuery is an alternative to Dataflow From the official documentation: “To automate the EDA process, use BigQuery or a managed data processing service like Dataflow.”
- BigQuery works with GKE From the official documentation: “Subsequently, by integrating BigQuery with GKE, you can use BigQuery to efficiently handle massive datasets (like Google Analytics) and the model's natural language understanding capabilities to generate meaningful insights.”
- BigQuery works with VPC Service Controls From the official documentation: “BigQuery integrates with VPC Service Controls to restrict access to your BigQuery resources from specific networks.”
- Cloud Monitoring depends on Identity and Access Management From the official documentation: “To use Monitoring, you must have the appropriate [Identity and Access Management](/iam/docs/overview) (IAM) permissions.”
- Cloud Monitoring works with VPC Service Controls From the official documentation: “Cloud Monitoring performs the VPC perimeter check when a project is *added* to a metrics scope:”
- Cloud Monitoring works with Workflows From the official documentation: “Use [Monitoring](/monitoring/docs) to get visibility into the performance, uptime, and overall health of your workflows.”
- Cloud Run depends on Artifact Registry From the official documentation: “Cloud Run function deployments use Artifact Registry to store artifacts and manage container images.”
- Cloud Run works with Compute Engine From the official documentation: “This lets Cloud Run clients use this backend service route to send requests directly to Compute Engine instances.”
- Cloud Run is an alternative to Compute Engine From the official documentation: “The decision of whether to use Cloud Run, GKE, or Compute Engine as your application host involves trade-offs between configuration flexibility and management effort.”
- Cloud Run works with Dataflow From the official documentation: “Route Dataflow events to Cloud Run”
- Cloud SQL works with VPC Service Controls From the official documentation: “Make sure that you configure VPC Service Controls so that the project that hosts the CA Service CA pool and CA<br>and the project that hosts Cloud SQL belong to the same service perimeter.”
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