custom containers

Related topics

• Artifact Registry works with custom containers From the official documentation: “If your use case requires libraries that aren't included in the prebuilt containers, or maybe you have custom data transformations you want to perform as part of the inference request, you can use a custom container that you build and push to Artifact Registry.”
• custom containers is part of Dataflow From the official documentation: “Custom container images for Dataflow let you package third-party dependencies, private libraries, and runtime binaries directly into your worker environment.”
• custom containers works with Dataflow From the official documentation: “Running Dataflow jobs in custom containers lets you customize your worker runtime environment and pre-install third-party dependencies.”
• custom containers is part of Gemini Enterprise Agent Platform Workbench From the official documentation: “Agent Platform Workbench provides two types of mutually exclusive images: - **VM images**: Google-built boot images that install the operating system, frameworks, kernels, and JupyterLab directly on the instance host. - **Custom containers**: a Google-provided base container…”
• 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”
• Dataflow works with Pub/Sub From the official documentation: “Pub/Sub notifies Dataflow about the upload.”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
• Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• CMEK secures Pub/Sub From the official documentation: “Encrypt Pub/Sub topic with CMEK”
• BigQuery works with Pub/Sub From the official documentation: “createBigQuerySubscription creates a Pub/Sub subscription that exports messages to BigQuery.”
• Cloud Storage is an alternative to Pub/Sub From the official documentation: “To keep audit logs for a longer period of time or to use more powerful search capabilities, you can route copies of your audit logs to Cloud Storage, BigQuery, or Pub/Sub.”
• CMEK secures BigQuery From the official documentation: “Enable CMEK for BigQuery Tables”
• Cloud Storage works with Pub/Sub From the official documentation: “| **Google Cloud** | Cloud Storage | Pub/Sub |”
• CMEK secures Cloud Storage From the official documentation: “Enable CMEK for Cloud Storage Buckets”
• 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.”
• BigQuery is an alternative to Pub/Sub From the official documentation: “To keep audit logs for a longer period of time or to use more powerful search capabilities, you can route copies of your audit logs to Cloud Storage, BigQuery, or Pub/Sub.”
• VPC Service Controls secures Cloud Storage From the official documentation: “Storage Transfer Service supports transfers to Cloud Storage buckets protected by VPC Service Controls.”
• Cloud Monitoring works with Dataflow From the official documentation: “Dataflow is fully integrated with Cloud Monitoring.”
• Cloud Monitoring works with Pub/Sub From the official documentation: “Use Cloud Monitoring and Pub/Sub to set up custom monitoring and alerting policies for exported logs.”
• CMEK secures Artifact Registry From the official documentation: “You use the CMEK keys to help protect your data in Artifact Registry and in Cloud Run.”
• CMEK works with Dataflow From the official documentation: “The region for your CMEK and the [region](/dataflow/docs/resources/locations) for your Dataflow job must be the same.”
• Dataflow depends on Cloud Storage From the official documentation: “Begin by creating a Cloud Storage bucket using the Google Cloud console or Google Cloud CLI. The Dataflow pipeline uses this bucket as a temporary storage location.”
• 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 depends on Cloud Storage From the official documentation: “The registry service hosts your custom images in Cloud Storage under your Google Cloud project.”
• Artifact Registry works with Cloud Storage From the official documentation: “| Artifact Registry | Stored in Cloud Storage, for each data chunk | |”
• Artifact Registry works with Pub/Sub From the official documentation: “When you activate the Artifact Registry API in a Google Cloud project, Artifact Registry tries to automatically create a Pub/Sub topic with the topic ID `gcr` using Google-owned and Google-managed encryption keys.”
• 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 Gemini Enterprise Agent Platform Workbench From the official documentation: “Agent Platform Workbench instances also include a BigQuery integration that lets you browse and query data from within the JupyterLab interface.”
• 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 works with Gemini Enterprise Agent Platform Workbench From the official documentation: “Agent Platform Workbench instances let you collect system status and JupyterLab metrics and report them to Cloud Monitoring.”
• 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:”
• CMEK works with Pub/Sub From the official documentation: “By using Pub/Sub with CMEK, you are able to meet locality rules about encryption while still maintaining high availability.”
• Dataflow works with Gemini Enterprise Agent Platform Workbench From the official documentation: “Dataflow only supports Workbench instances that use the Apache Beam container.”
• Dataflow works with VPC Service Controls From the official documentation: “To customize DNS resolution when using Dataflow with VPC Service Controls, use Cloud DNS [private zones](/dns/docs/overview#dns-private-zones) instead of using custom BIND servers.”
• Gemini Enterprise Agent Platform Workbench depends on Artifact Registry From the official documentation: “To connect to the proxy service, your Agent Platform Workbench instance runs an agent that it downloads from Artifact Registry.”
• VPC Service Controls configures Artifact Registry From the official documentation: “Manage Artifact Registry VPC Service Controls configuration for remote repositories.”
• VPC Service Controls secures Cloud Monitoring From the official documentation: “VPC Service Controls provides additional security for Cloud Monitoring to help mitigate the risk of data exfiltration.”
• VPC Service Controls secures Dataflow From the official documentation: “Dataflow VPC Service Controls help protect against accidental or targeted action by external entities or by insider entities, which helps to minimize unwarranted data exfiltration risks.”
• VPC Service Controls secures Pub/Sub From the official documentation: “If you use [VPC Service Controls](/vpc-service-controls/docs/overview) and your Pub/Sub topic is part of a project inside a service perimeter, you must grant access to projects in order to create notifications.”