Google Associate-Cloud-Engineer - Google Cloud Certified - Associate Cloud Engineer

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Total 343 questions

(You are developing an internet of things (IoT) application that captures sensor data from multiple devices that have already been set up. You need to identify the global data storage product your company should use to store this data. You must ensure that the storage solution you choose meets your requirements of sub-millisecond latency. What should you do?)

Store the IoT data in Spanner. Use caches to speed up the process and avoid latencies.

Store the IoT data in Bigtable.

Capture IoT data in BigQuery datasets.

Store the IoT data in Cloud Storage. Implement caching by using Cloud CDN.

Explanation:

Let's evaluate each option based on the requirement of sub-millisecond latency for globally stored IoT data:

A. Spanner with Caching: While Spanner offers strong consistency and global scalability, the base latency might not consistently be sub-millisecond for all read/write operations globally. Introducing caching adds complexity and doesn't guarantee sub-millisecond latency for all initial reads or cache misses.

B. Bigtable: Bigtable is a highly scalable NoSQL database service designed for low-latency, high-throughput workloads. It excels at storing and retrieving large volumes of time-series data, which is typical for IoT sensor data. Its architecture is optimized for single-key lookups and scans, providing consistent sub-millisecond latency, making it a strong candidate for this use case.

C. BigQuery: BigQuery is a fully managed, serverless data warehouse designed for analytical queries on large datasets. While it's excellent for analyzing IoT data in batch, it's not optimized for the low-latency, high-throughput ingestion and retrieval required for real-time IoT applications with sub-millisecond latency needs.

D. Cloud Storage with Cloud CDN: Cloud Storage is object storage and is not designed for low-latency transactional workloads. Cloud CDN is a content delivery network that caches content closer to users for faster delivery, but it's not suitable for the primary storage of rapidly incoming IoT sensor data requiring sub-millisecond write latency.

Google Cloud Documentation References:

Cloud Bigtable Overview: https://cloud.google.com/bigtable/docs/overview - This document highlights Bigtable 's suitability for low-latency and high-throughput applications, including IoT. It mentions its ability to handle massive amounts of data with consistent performance.

Spanner Overview: https://cloud.google.com/spanner/docs/overview - While Spanner offers low latency, Bigtable is generally preferred for extremely high-throughput, low-latency use cases like raw sensor data ingestion due to its optimized architecture for such workloads.

BigQuery Overview: https://cloud.google.com/bigquery/docs/introduction - This emphasizes BigQuery 's analytical capabilities rather than low-latency operational workloads.

Cloud Storage Overview: https://cloud.google.com/storage/docs/overview - This describes Cloud Storage as object storage, not ideal for sub-millisecond latency reads and writes required for real-time IoT data.

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Question # 2

You need to grant access for three users so that they can view and edit table data on a Cloud Spanner instance. What should you do?

Run gcloud iam roles describe roles/spanner.databaseUser. Add the users to the role.

Run gcloud iam roles describe roles/spanner.databaseUser. Add the users to a new group. Add the group to the role.

Run gcloud iam roles describe roles/spanner.viewer --project my-project. Add the users to the role.

Run gcloud iam roles describe roles/spanner.viewer --project my-project. Add the users to a new group. Add the group to the role.

Question # 3

(You are managing an application deployed on Cloud Run. The development team has released a new version of the application. You want to deploy and redirect traffic to this new version of the application. To ensure traffic to the new version of the application is served with no startup time, you want to ensure that there are two idle instances available for incoming traffic before adjusting the traffic flow. You also want to minimize administrative overhead. What should you do?)

Ensure the checkbox "Serve this revision immediately" is unchecked when deploying the new revision. Before changing the traffic rules, use a traffic simulation tool to send load to the new revision.

Configure service autoscaling and set the minimum number of instances to 2.

Configure revision autoscaling for the new revision and set the minimum number of instances to 2.

Configure revision autoscaling for the existing revision and set the minimum number of instances to 2.

Explanation:

Let's analyze each option to find the one that meets the requirements of no startup time for new traffic, two idle instances, and minimal administrative overhead:

A. Unchecking "Serve this revision immediately" and using a traffic simulation tool: Unchecking "Serve this revision immediately" does prevent the new revision from receiving traffic immediately. However, manually using a traffic simulation tool adds administrative overhead. It also doesn't guarantee that two idle instances will be ready before traffic is shifted; you would need to monitor and adjust traffic manually based on the simulation.

B. Configuring service autoscaling and setting the minimum number of instances to 2: Service-level autoscaling applies to all revisions of the service. Setting the minimum instances at the service level would ensure at least two instances are running across all active revisions, not specifically for the new revision before traffic shift.

C. Configuring revision autoscaling for the new revision and setting the minimum number of instances to 2: This is the correct approach. By configuring revision autoscaling specifically for the new revision and setting the minimum number of instances to 2, Cloud Run will ensure that at least two instances of the new version are running and ready to serve traffic before you redirect any traffic to it. This eliminates startup latency when you do shift traffic. It also minimizes administrative overhead as Cloud Run manages the instance scaling based on this configuration.

D. Configuring revision autoscaling for the existing revision and setting the minimum number of instances to 2: This would ensure the existing version has at least two idle instances, which doesn't directly address the requirement of having idle instances ready for the new version before traffic redirection.

Google Cloud Documentation References:

Cloud Run Autoscaling: https://cloud.google.com/run/docs/configuring/min-instances - This document explains how to configure minimum and maximum instances for Cloud Run services and revisions. It clarifies that you can set minimum instances at the revision level to ensure instances are always ready.

Cloud Run Traffic Management: https://cloud.google.com/run/docs/managing/traffic - This describes how to deploy new revisions and gradually shift traffic between them. Combining minimum instances on the new revision with traffic splitting allows for zero-downtime deployments with pre-warmed instances.

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Question # 4

You have a developer laptop with the Cloud SDK installed on Ubuntu. The Cloud SDK was installed from the Google Cloud Ubuntu package repository. You want to test your application locally on your laptop with Cloud Datastore. What should you do?

Export Cloud Datastore data using gcloud datastore export.

Create a Cloud Datastore index using gcloud datastore indexes create.

Install the google-cloud-sdk-datastore-emulator component using the apt get install command.

Install the cloud-datastore-emulator component using the gcloud components install command.

Question # 5

You have one project called proj-sa where you manage all your service accounts. You want to be able to use a service account from this project to take snapshots of VMs running in another project called proj-vm. What should you do?

Download the private key from the service account, and add it to each VMs custom metadata.

Download the private key from the service account, and add the private key to each VMâ€™s SSH keys.

Grant the service account the IAM Role of Compute Storage Admin in the project called proj-vm.

When creating the VMs, set the service accountâ€™s API scope for Compute Engine to read/write.

Question # 6

You have created a new project in Google Cloud through the gcloud command line interface (CLI) and linked a billing account. You need to create a new Compute

Engine instance using the CLI. You need to perform the prerequisite steps. What should you do?

Create a Cloud Monitoring Workspace.

Create a VPC network in the project.

Enable the compute googleapis.com API.

Grant yourself the IAM role of Compute Admin.

Question # 7

(You are managing a stateful application deployed on Google Kubernetes Engine (GKE) that can only have one replica. You recently discovered that the application becomes unstable at peak times. You have identified that the application needs more CPU than what has been configured in the manifest at these peak times. You want Kubernetes to allocate the application sufficient CPU resources during these peak times, while ensuring cost efficiency during off-peak periods. What should you do?)

Enable cluster autoscaling on the GKE cluster.

Configure a Vertical Pod Autoscaler on the Deployment.

Configure a Horizontal Pod Autoscaler on the Deployment.

Enable node auto-provisioning on the GKE cluster.

Question # 8

You are migrating a business critical application from your local data center into Google Cloud. As part of your high-availability strategy, you want to ensure that any data used by the application will be immediately available if a zonal failure occurs. What should you do?

Store the application data on a zonal persistent disk. Create a snapshot schedule for the disk. If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.

Store the application data on a zonal persistent disk. If an outage occurs, create an instance in another zone with this disk attached.

Store the application data on a regional persistent disk. Create a snapshot schedule for the disk. If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.

Store the application data on a regional persistent disk If an outage occurs, create an instance in another zone with this disk attached.

Question # 9

You want to set up a Google Kubernetes Engine cluster Verifiable node identity and integrity are required for the cluster, and nodes cannot be accessed from the internet. You want to reduce the operational cost of managing your cluster, and you want to follow Google-recommended practices. What should you do?

Deploy a private autopilot cluster

Deploy a public autopilot cluster.

Deploy a standard public cluster and enable shielded nodes.

Deploy a standard private cluster and enable shielded nodes.

Question # 10

A colleague handed over a Google Cloud Platform project for you to maintain. As part of a security checkup, you want to review who has been granted the Project Owner role. What should you do?

In the console, validate which SSH keys have been stored as project-wide keys.

Navigate to Identity-Aware Proxy and check the permissions for these resources.

Enable Audit Logs on the IAM & admin page for all resources, and validate the results.

Use the command gcloud projects getâ€“iamâ€“policy to view the current role assignments.

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Google Associate-Cloud-Engineer - Google Cloud Certified - Associate Cloud Engineer

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