network attachment

Related topics

• Eventarc depends on network attachment From the official documentation: “To publish events, Eventarc uses the network attachment to establish a connection to the internal HTTP endpoint hosted in a VPC network.”
• BigQuery Data Transfer Service depends on network attachment From the official documentation: “To let BigQuery Data Transfer Service securely connect to external databases or third-party cloud data sources with a private IP address inside a private network, configure a [network attachment](/vpc/docs/about-network-attachments) through Private Service Connect.”
• BigQuery Data Transfer Service works with network attachment From the official documentation: “2. [Set up a network attachment](/vpc/docs/create-manage-network-attachments) within the same VPC network. This resource is used by the BigQuery Data Transfer Service to access private services.”
• Cloud Data Fusion depends on network attachment From the official documentation: “To configure Private Service Connect in Cloud Data Fusion, you must first create a network attachment and then create a Cloud Data Fusion instance with Private Service Connect.”
• Cloud SQL depends on network attachment From the official documentation: “You can configure your Private Service Connect-enabled Cloud SQL instance to have outbound connectivity with your network using a Private Service Connect interface and a [network attachment](/vpc/docs/about-network-attachments).”
• Eventarc trigger depends on network attachment From the official documentation: “Before creating an Eventarc trigger to route events to an internal HTTP endpoint in a VPC network, you must create a network attachment that accepts connections in the same network and region containing the HTTP destination service.”
• Managed Service for Apache Airflow depends on network attachment From the official documentation: “Managed Airflow uses a [network attachment](/vpc/docs/about-network-attachments) to connect your environment to a VPC network:”
• BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
• BigQuery works with Cloud Storage From the official documentation: “Sample to load Avro data from Cloud Storage into a new BigQuery table”
• BigQuery works with Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
• BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• Cloud SQL works with Cloud Storage From the official documentation: “Exports data from a Cloud SQL instance to a Cloud Storage bucket as a SQL dump or CSV file.”
• Customer-Managed Encryption Keys secures Cloud Storage From the official documentation: “CMEKs encrypt data at rest in Cloud SQL, Cloud Storage, and within GKE clusters.”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• BigQuery works with BigQuery Data Transfer Service From the official documentation: “The BigQuery Data Transfer Service uses load jobs to load Amazon S3 data into BigQuery.”
• Cloud Logging works with GKE From the official documentation: “Enable Cloud Logging on GKE Clusters”
• Cloud Monitoring works with GKE From the official documentation: “Enable Cloud Monitoring on GKE Clusters”
• Customer-Managed Encryption Keys secures Cloud SQL From the official documentation: “Enable CMEK for Cloud SQL Databases”
• Cloud SQL works with GKE From the official documentation: “The app uses Cloud SQL, Vertex AI, and either Google Kubernetes Engine (GKE) or Cloud Run.”
• Cloud Storage works with Customer-Managed Encryption Keys From the official documentation: “Cloud Storage supports CMEK for routing logs.”
• Cloud Storage works with Eventarc From the official documentation: “Trigger functions from Cloud Storage using Eventarc”
• Cloud Logging works with Cloud Monitoring From the official documentation: “You can store and view query-response activity logs in Cloud Logging and set up logs-based monitoring by using Cloud Monitoring.”
• Cloud Logging works with Cloud SQL From the official documentation: “Database Migration Service and Cloud SQL use Cloud Logging.”
• Cloud Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
• Cloud Storage works with Eventarc trigger From the official documentation: “# Create an Eventarc trigger, routing Cloud Storage events to Workflows”
• Customer-Managed Encryption Keys secures BigQuery From the official documentation: “You can either create CMEKs manually to protect your BigQuery resources or use Cloud KMS Autokey.”
• Eventarc trigger works with GKE From the official documentation: “You can create a trigger for a GKE destination using Terraform.”
• BigQuery works with Managed Service for Apache Airflow From the official documentation: “You can use Managed Airflow to orchestrate services in your data pipelines, such as triggering a job in BigQuery or starting a Dataflow pipeline.”
• BigQuery Data Transfer Service works with Cloud Storage From the official documentation: “- [Cloud Storage](/bigquery/docs/cloud-storage-transfer)”
• Customer-Managed Encryption Keys secures Managed Service for Apache Airflow From the official documentation: “This page describes how to use [Customer Managed Encryption Keys (CMEK)](/kms/docs/cmek) to protect Managed Airflow environments.”
• BigQuery works with Cloud Data Fusion From the official documentation: “Cloud Data Fusion pulls data from the storage bucket and writes it to BigQuery.”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery Data Transfer Service works with Cloud Logging From the official documentation: “The BigQuery Data Transfer Service exports logs and metrics to Cloud Monitoring and Cloud Logging that provide observability into your transfers.”
• Cloud Data Fusion works with Cloud Logging From the official documentation: “To use Cloud Logging with your Cloud Data Fusion pipeline, create a Cloud Data Fusion instance with Cloud Logging enabled:”
• Cloud Data Fusion works with Managed Service for Apache Airflow From the official documentation: “Recommended: You can also use Composer to orchestrate pipelines in Cloud Data Fusion.”
• Cloud Logging is an alternative to Cloud Storage From the official documentation: “Instead, they are routed to either Cloud Storage (recommended) or Cloud Logging, depending on your organization's configuration.”
• Cloud Logging works with Customer-Managed Encryption Keys From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
• Cloud Logging works with Eventarc From the official documentation: “Eventarc automatically sends audit logs to Cloud Logging for troubleshooting and streams metrics to Cloud Monitoring for trend analysis and alerting.”
• 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 Managed Service for Apache Airflow From the official documentation: “To learn about Cloud Logging and Cloud Monitoring for your Managed Airflow environment, see [Monitor environments](/composer/docs/composer-2/monitor-environments).”
• Cloud Storage works with Managed Service for Apache Airflow From the official documentation: “When you upload your DAG file to the `dags/` folder in Cloud Storage, Managed Airflow parses the file.”
• Customer-Managed Encryption Keys depends on Cloud Storage From the official documentation: “If used for storing Customer-managed Encryption Keys (CMEK): Cloud Storage (See [Cloud Storage pricing](/storage/pricing).)”
• Customer-Managed Encryption Keys secures GKE From the official documentation: “CMEKs encrypt data at rest in Cloud SQL, Cloud Storage, and within GKE clusters.”
• Eventarc works with GKE From the official documentation: “Before creating the service account, enable Eventarc to manage GKE clusters:”
• GKE works with Managed Service for Apache Airflow From the official documentation: “Managed Airflow runs your workloads on GKE.”
• Managed Service for Apache Airflow depends on Cloud SQL From the official documentation: “Managed Airflow uses Cloud SQL to run Airflow database.”
• BigQuery depends on Cloud Storage From the official documentation: “BigQuery relies on Cloud Storage for staging file data and supports reading from and writing to several other sources and Google Cloud services.”
• 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 Data Transfer Service works with Cloud Monitoring From the official documentation: “The BigQuery Data Transfer Service exports logs and metrics to Cloud Monitoring and Cloud Logging that provide observability into your transfers.”
• BigQuery Data Transfer Service works with Cloud SQL From the official documentation: “BigQuery Data Transfer Service lets you transfer data from a private Cloud SQL instance across different Google Cloud projects over an internal IP address.”
• BigQuery Data Transfer Service works with Customer-Managed Encryption Keys From the official documentation: “When you specify a CMEK with a transfer, the BigQuery Data Transfer Service applies the CMEK to any intermediate on-disk cache of ingested data so that the entire data transfer workflow is CMEK compliant.”
• BigQuery Data Transfer Service works with Managed Service for Apache Airflow From the official documentation: “**Managed Service for Apache Airflow jobs**: you can schedule [Managed Service for Apache Airflow](/composer) jobs to issue ETL jobs that create regional subsets before triggering the BigQuery Data Transfer Service through its [client API](/bigquery/docs/reference/libraries).”
• Cloud Data Fusion works with Cloud Monitoring From the official documentation: “Filter and aggregate Cloud Data Fusion pipeline and instance metrics in Monitoring using [*metric* and *monitored-resource* labels](/monitoring/api/v3/metric-model#generic-label-info).”
• Cloud Data Fusion works with Cloud SQL From the official documentation: “This page describes how to connect a private Cloud Data Fusion instance to a private Cloud SQL instance that hosts a MySQL database.”
• Cloud Data Fusion works with Eventarc trigger From the official documentation: “These instructions show you how to configure event routing to your Cloud Run service that is triggered by a direct Cloud Data Fusion event.”
• Cloud Logging is an alternative to Cloud Monitoring From the official documentation: “To see the status of your invalidation request or find a definitive list of recently submitted requests, you can use Cloud Logging or Cloud Monitoring.”
• Cloud Logging depends on Customer-Managed Encryption Keys From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
• Cloud Logging works with Managed Service for Apache Airflow From the official documentation: “To learn about Cloud Logging and Cloud Monitoring for your Managed Airflow environment, see [Monitor environments](/composer/docs/composer-2/monitor-environments).”
• Cloud Monitoring works with Eventarc From the official documentation: “Eventarc automatically sends audit logs to Cloud Logging for troubleshooting and streams metrics to Cloud Monitoring for trend analysis and alerting.”
• Cloud SQL depends on Cloud Storage From the official documentation: “When ingesting data from Cloud SQL, data is first staged to a Cloud Storage bucket.”