Free Practice Questions for Google Associate-Cloud-Engineer Exam

Adding an API as a type provider

This page describes how to add an API to Google Cloud Deployment Manager as a type provider. To learn more about types and type providers, read the Types overview documentation.

A type provider exposes all of the resources of a third-party API to Deployment Manager as base types that you can use in your configurations. These types must be directly served by a RESTful API that supports Create, Read, Update, and Delete (CRUD).

If you want to use an API that is not automatically provided by Google with Deployment Manager, you must add the API as a type provider.

https://cloud.google.com/deployment-manager/docs/configuration/type-providers/creating-type-provider

"The Cloud Spanner to Cloud Storage Text template is a batch pipeline that reads in data from a Cloud Spanner table, optionally transforms the data via a JavaScript User Defined Function (UDF) that you provide, and writes it to Cloud Storage as CSV text files."

https://cloud.google.com/dataflow/docs/guides/templates/provided-batch#cloudspannertogcstext

"The Dataflow connector for Cloud Spanner lets you read data from and write data to Cloud Spanner in a Dataflow pipeline"

https://cloud.google.com/spanner/docs/dataflow-connector

https://cloud.google.com/bigquery/external-data-sources

auto-provisioning = Attaches and deletes node pools to cluster based on the requirements. Hence creating a GPU node pool, and auto-scaling would be betterhttps://cloud.google.com/kubernetes-engine/docs/how-to/node-auto-provisioning

Predefined roles

The following table describes Identity and Access Management (IAM) roles that are associated with Cloud Storage and lists the permissions that are contained in each role. Unless otherwise noted, these roles can be applied either to entire projects or specific buckets.

Storage Object Creator (roles/storage.objectCreator) Allows users to create objects. Does not give permission to view, delete, or overwrite objects.

https://cloud.google.com/storage/docs/access-control/iam-roles#standard-roles

Cloud Billing export to BigQuery enables you to export detailed Google Cloud billing data (such as usage, cost estimates, and pricing data) automatically throughout the day to a BigQuery dataset that you specify. Then you can access your Cloud Billing data from BigQuery for detailed analysis, or use a tool like Looker Studio to visualize your data.

Quickstart: using the Google Cloud Console

This page shows you how to perform basic tasks in Pub/Sub using the Google Cloud Console.

Note: If you are new to Pub/Sub, we recommend that you start with the interactive tutorial.

Before you begin

Set up a Cloud Console project.

Set up a project

Click to:

Create or select a project.

Enable the Pub/Sub API for that project.

You can view and manage these resources at any time in the Cloud Console.

Install and initialize the Cloud SDK.

Note: You can run the gcloud tool in the Cloud Console without installing the Cloud SDK. To run the gcloud tool in the Cloud Console, use Cloud Shell .

https://cloud.google.com/pubsub/docs/quickstart-console

This is the most optimal solution. Rather than recreating all nodes, you create a new node pool with GPU enabled. You then modify the pod specification to target particular GPU types by adding node selector to your workloads Pod specification. YOu still have a single cluster so you pay Kubernetes cluster management fee for just one cluster thus minimizing the cost.

Ref: https://cloud.google.com/kubernetes-engine/docs/how-to/gpus

Ref: https://cloud.google.com/kubernetes-engine/pricing

Example:

apiVersion: v1

kind: Pod

metadata:

name:my-gpu-pod

spec:

containers:

name:my-gpu-container

image: nvidia/cuda:10.0-runtime-ubuntu18.04

command: [/bin/bash]

resources:

limits:

nvidia.com/gpu: 2

nodeSelector:

cloud.google.com/gke-accelerator: nvidia-tesla-k80# or nvidia-tesla-p100 or nvidia-tesla-p4 or nvidia-tesla-v100 or nvidia-tesla-t4

The goal is to create a landing zone facilitating private IP communication across production projects and apply organization-wide firewall rules, following best practices and minimizing operational costs.

Network Structure:Individual VPCs with Peering (A, B): While VPC Peering allows private connectivity, managing a full mesh or complex peering topology across many projects becomes operationally complex and can hit peering limits. It's not the recommended pattern for centralized connectivity in a landing zone.

Shared VPC (C, D): This is the Google-recommended practice for scenarios where resources from multiple projects need to communicate privately within a common VPC network. A central host project owns the network, and service projects use it. This simplifies network administration and connectivity.

Firewall Rules:Organization Policies (A, C): These enforce organizational constraints (e.g., disable external IPs, restrict locations) but do not define specific network firewall rules (like allowing TCP ports).

Hierarchical Firewall Policies (B, D): These allow defining firewall rules at the Organization or Folder level, which are inherited by resources in descendant projects/folders. This is the mechanism to apply consistent firewall rules (like allowing specific TCP ports) across all VMs in the organization (or a specific folder) efficiently, without managing rules in each individual VPC or project.

Combining Shared VPC for the network structure (best practice for cross-project private communication and central management) with Hierarchical Firewall Policies (for applying organization-wide firewall rules) meets all requirements efficiently and follows Google recommendations.  

Keywords: - continually -> Standard - mission-critical analytics -> dual-regional

Signed URLs are used to give time-limited resource access to anyone in possession of the URL, regardless of whether they have a Google account.https://cloud.google.com/storage/docs/access-control/signed-urls