IAM policies

Related topics

• IAM policies configures principal From the official documentation: “IAM policies grant specific roles to principals, thereby giving them certain permissions.”
• IAM policies configures Bigtable From the official documentation: “Bigtable uses [IAM](/iam) for access control. To control who has access a resource, set IAM policies on the resource.”
• IAM policies configures Compute Engine From the official documentation: “You can [grant access to Compute Engine resources](/compute/docs/access/managing-access-to-resources) such as VM instances, images, and disks, by attaching IAM policies directly to those resources.”
• IAM policies is part of Identity and Access Management (IAM) From the official documentation: “To prevent test disruptions, ensure that your Identity and Access Management (IAM) roles, policies, and failover configurations are correctly set up.”
• IAM policies configures linked dataset From the official documentation: “You can't set [IAM roles](/bigquery/docs/access-control) or [IAM policies](/config-connector/docs/reference/resource-docs/iam/iampolicy) on individual tables within a linked dataset. Apply them at the linked dataset level instead.”
• IAM policies configures predefined roles From the official documentation: “Predefined roles, which you grant by using IAM policies, contain permissions that let principals perform specific actions.”
• Identity and Access Management configures IAM policies From the official documentation: “IAM lets you control **who** (identity) has **what access** (roles) to **which resource** by setting IAM policies.”
• 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.”
• 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.”
• Compute Engine works with service account From the official documentation: “A common method is to attach a service account to a resource like a Compute Engine instance.”
• BigQuery works with Bigtable From the official documentation: “BigQuery lets you query your Bigtable data from BigQuery.”
• Cloud SQL works with Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
• Compute Engine is an alternative to GKE From the official documentation: “You can also deploy a third-party model to either Vertex AI Model Garden or self-host on GKE or Compute Engine.”
• 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 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.”
• GKE depends on Compute Engine From the official documentation: “For example, GKE deploys clusters on Compute Engine VMs.”
• IAM roles is part of Identity and Access Management From the official documentation: “IAM roles give the principals permissions to perform tasks on your App Topology resources.”
• Identity and Access Management secures Cloud Storage From the official documentation: “Cloud Storage uses Identity and Access Management (IAM) for authorization.”
• service account is part of Identity and Access Management From the official documentation: “Service accounts function as both principals and resources within IAM.”
• BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
• Bigtable is an alternative to Cloud Storage From the official documentation: “If the joining data is in the gigabyte or terabyte range, use either Bigtable or Cloud Storage to merge the joining data to the driving data, depending on the nature of the data.”
• Cloud Storage works with service account From the official documentation: “The service account can manage objects in the Cloud Storage bucket.”
• IAM roles configures service account From the official documentation: “2. [Grant the necessary Identity and Access Management roles](#grant-iam-roles) to your service account.”
• 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 (IAM) secures BigQuery From the official documentation: “BigQuery uses IAM for fine-grained access control.”
• predefined roles is part of IAM roles From the official documentation: “This requirement applies to both [predefined roles](/iam/docs/roles-permissions) and [custom roles](/iam/docs/roles-overview#custom).”
• 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.”
• 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 service account From the official documentation: “The service account can be used by services, such as Cloud Run, to read and modify data in the BigQuery dataset.”
• Bigtable is an alternative to Cloud SQL From the official documentation: “If you're interested in evaluating how the performance of your on-premises databases compares to [Cloud SQL](/sql), [Spanner](/spanner), [Firestore](/firestore), or [Bigtable](/bigtable), you could implement a PoC where the same business logic uses different databases.”
• Bigtable works with Cloud Storage From the official documentation: “For example, if you frequently write data to Bigtable from a Cloud Storage bucket in the `us-central1` (Iowa) region, create your Bigtable cluster in a zone within `us-central1`.”
• Bigtable works with Compute Engine From the official documentation: “OAuth scopes let Google Cloud services such as Compute Engine and Dataflow authenticate and connect to Bigtable.”
• Bigtable works with GKE From the official documentation: “TVer built a high-throughput, zero-downtime ad infrastructure with Bigtable and GKE to process hundreds of millions of daily ad requests.”
• Bigtable works with Identity and Access Management (IAM) From the official documentation: “Bigtable uses [IAM](/iam) for access control.”
• 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.”
• Cloud SQL depends on Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
• Cloud SQL works with Identity and Access Management From the official documentation: “This page describes how Cloud SQL is integrated with IAM .”
• Cloud Storage works with GKE From the official documentation: “This example configures GKE to store Pod snapshots in the `FOLDER_PATH/` path inside the Cloud Storage bucket `BUCKET_NAME`:”
• Cloud Storage works with Identity and Access Management From the official documentation: “To learn how to use IAM with Cloud Storage, see [Using IAM Permissions](/storage/docs/access-control/using-iam-permissions).”
• Compute Engine depends on service account From the official documentation: “The Service Account is used by Compute Engine to access other Google APIs.”
• GKE depends on Identity and Access Management From the official documentation: “GKE relies on and can be used with many other Google Cloud services, from IAM for access control to Cloud Billing for managing your costs.”
• IAM roles secures Bigtable From the official documentation: “Access to your Bigtable tables is controlled by your Google Cloud project and the [Identity and Access Management (IAM) roles](/bigtable/docs/access-control#roles) that you assign to users.”
• IAM roles secures Cloud Storage From the official documentation: “**Fine-grained access control**: Control agent access to Cloud Storage precisely using [IAM roles](/storage/docs/access-control/iam-roles).”
• IAM roles is part of Identity and Access Management (IAM) From the official documentation: “To prevent test disruptions, ensure that your Identity and Access Management (IAM) roles, policies, and failover configurations are correctly set up.”
• IAM roles configures linked dataset From the official documentation: “You can't set [IAM roles](/bigquery/docs/access-control) or [IAM policies](/config-connector/docs/reference/resource-docs/iam/iampolicy) on individual tables within a linked dataset. Apply them at the linked dataset level instead.”
• IAM roles configures principal From the official documentation: “To control who can view, create, or update Security Command Center resources, you grant IAM roles to principals, such as users, groups, or service accounts.”
• IAM roles works with service account From the official documentation: “In this section, you designate the service account for the gateway proxies and assign them the correct IAM roles.”
• Identity and Access Management secures BigQuery From the official documentation: “Security in BigQuery is intrinsically linked to [Identity and Access Management (IAM)](/iam/docs/overview) in Google Cloud.”
• Identity and Access Management secures Bigtable From the official documentation: “Bigtable uses Identity and Access Management (IAM) for authorization.”
• Identity and Access Management configures GKE From the official documentation: “First, as you would with most services on Google Cloud, you need to configure [IAM](/iam) roles in order to set up authorization on GKE.”
• Identity and Access Management configures service account From the official documentation: “Learn more about using Identity and Access Management to [create a service account](/iam/docs/creating-managing-service-accounts) and [manage the access granted to a service account](/iam/docs/granting-changing-revoking-access).”
• Identity and Access Management (IAM) secures Cloud Storage From the official documentation: “Cloud Storage supports two methods for granting users access to your buckets and objects: Identity and Access Management (IAM) and access control lists (ACLs).”
• predefined roles is part of Identity and Access Management From the official documentation: “There are three types of roles in IAM: - **Predefined roles** provide granular access for a specific service and are managed by Google Cloud.”
• principal works with service account From the official documentation: “The previous query searches for audit logs that capture roles being granted to a principal on a service account.”
• service account depends on BigQuery From the official documentation: “Each feature view uses a service account to access the source data in BigQuery during sync.”
• service account secures Cloud SQL From the official documentation: “Cloud SQL uses service accounts for authentication between Cloud SQL and other Google Cloud products.”