runtime

Related topics

• Cloud Run is an alternative to runtime From the official documentation: “Run agents locally or scale them globally using Runtime, Cloud Run, or Google Kubernetes Engine.”
• Google Kubernetes Engine is an alternative to runtime From the official documentation: “Run agents locally or scale them globally using Runtime, Cloud Run, or Google Kubernetes Engine.”
• runtime is part of Colab Enterprise From the official documentation: “This page describes runtimes and runtime templates for Colab Enterprise.”
• 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”
• 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.”
• Artifact Registry works with Cloud Run From the official documentation: “Cloud Run recommends using Artifact Registry.”
• Cloud Storage works with customer-managed encryption keys From the official documentation: “Cloud Storage supports CMEK for routing logs.”
• Cloud Storage works with Compute Engine From the official documentation: “For example, you can create a service account that your Compute Engine instances use to access objects stored in Cloud Storage buckets.”
• 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.”
• Artifact Registry works with Google Kubernetes Engine From the official documentation: “You can identify frequently pulled images and copy them to Artifact Registry for deployments to Google Cloud environments such as Google Kubernetes Engine or Cloud Run.”
• BigQuery works with Vertex AI From the official documentation: “The page provides guidance for getting predictions from Vertex AI, based on retail [data exported into BigQuery](/retail/docs/export-data-into-bq).”
• Cloud Run works with Cloud Storage From the official documentation: “Receive events from Cloud Storage in a Cloud Run service”
• Cloud Run works with Google Kubernetes Engine From the official documentation: “Connecting Cloud Run services to Cloud Service Mesh lets you securely route traffic to workloads on GKE.”
• Colab Enterprise depends on Compute Engine From the official documentation: “Colab Enterprise uses Compute Engine quota for GPUs.”
• Compute Engine is an alternative to Google Kubernetes Engine From the official documentation: “You can install MongoDB on a Compute Engine instance or you can deploy MongoDB on Google Kubernetes Engine.”
• BigQuery works with Colab Enterprise From the official documentation: “You can use Colab Enterprise from within the Google Cloud console, with features built into both Agent Platform and BigQuery.”
• Cloud Storage works with Colab Enterprise From the official documentation: “Colab Enterprise stores the results in Cloud Storage for you to review and share with others.”
• customer-managed encryption keys secures Artifact Registry From the official documentation: “Artifact Registry also supports [organization policy constraints](/artifact-registry/docs/cmek#org-policy) that can require CMEK to protect resources.”
• 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 Compute Engine From the official documentation: “In IL5, CMEK is enabled by default for Compute Engine, Google Kubernetes Engine (GKE), Cloud Storage, and Cloud SQL.”
• Google Kubernetes Engine depends on BigQuery From the official documentation: “This happens because Google Kubernetes Engine depends on BigQuery and Managed Service for Apache Airflow inherits this dependency from the Kubernetes Engine API.”
• 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 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 Compute Engine From the official documentation: “Compute Engine can pull containers directly from Artifact Registry repositories so you can run containerized workloads on virtual machine (VM) instances.”
• Artifact Registry secures Google Kubernetes Engine 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…”
• 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 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 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.”
• Cloud Run depends on Artifact Registry From the official documentation: “The containerized function is stored in Artifact Registry and deployed to Cloud Run as a service.”
• 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 Google Kubernetes Engine From the official documentation: “**Agent and tool runtimes**: hosting and executing agents or MCP servers on runtimes such as Agent Runtime on Gemini Enterprise Agent Platform, Cloud Run, or Google Kubernetes Engine (GKE) incurs standard compute and runtime charges for those services.”
• Cloud Run works with Vertex AI From the official documentation: “The Cloud Run service can interact with Vertex AI services.”
• Cloud Storage works with Google Kubernetes Engine From the official documentation: “Often, media-related data residing in Cloud Storage is processed by applications running in Compute Engine or Google Kubernetes Engine, and the output of this process is written back to Cloud Storage.”
• Cloud Storage works with Vertex AI From the official documentation: “Access Cloud Storage content through your current project's Vertex AI service agent.”
• Colab Enterprise works with customer-managed encryption keys From the official documentation: “For more information about how to use CMEK for Colab Enterprise, see the [Colab Enterprise CMEK page](/colab/docs/cmek).”
• Colab Enterprise depends on Vertex AI From the official documentation: “Colab Enterprise provides a notebook-centric, zero-configuration experience, with compute resources managed by Vertex AI, and integrates with other Google Cloud services like BigQuery.”
• Compute Engine works with Google Kubernetes 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.”
• customer-managed encryption keys is part of BigQuery From the official documentation: “If you require more control over encryption keys, BigQuery supports [customer-managed encryption keys](/bigquery/docs/customer-managed-encryption) in the [Cloud Key Management Service](/kms/docs).”
• customer-managed encryption keys secures Cloud Run From the official documentation: “If you want to control your encryption keys, then you can use customer-managed encryption keys (CMEKs) in [Cloud KMS](/kms/docs) with CMEK-integrated services including Cloud Run.”
• customer-managed encryption keys is part of Cloud Storage From the official documentation: “[Cloud Storage](/storage/docs/introduction) provides features such as customer-managed encryption, lifecycle management, and aging and retention policies.”
• customer-managed encryption keys secures Colab Enterprise From the official documentation: “This guide describes how to use CMEK for Colab Enterprise.”
• customer-managed encryption keys secures Google Kubernetes Engine From the official documentation: “In IL5, CMEK is enabled by default for Compute Engine, Google Kubernetes Engine (GKE), Cloud Storage, and Cloud SQL.”
• Google Kubernetes Engine is an alternative to Vertex AI From the official documentation: “| **Small ML Models** | Requires specific hardware (e.g., GPU). | Vertex AI / Google Kubernetes Engine (GKE) | Specialized hardware; more complex setup. |”