Google Associate-Cloud-Engineer Actual Questions

In Google compute engine, if predefined machine types don’t meet your needs, you can create an instance with custom virtualized hardware settings. Specifically, you can create an instance with a custom number of vCPUs and custom memory, effectively using a custom machine type. Custom machine types are ideal for the following scenarios:

   1. Workloads that aren’t a good fit for the predefined machine types that are available to you.

   2. Workloads that require more processing power or more memory but don’t need all of the upgrades that are provided by the next machine type level.

In our scenario, we only need a memory upgrade. Moving to a bigger instance would also bump up the CPU which we don’t need so we have to use a custom machine type. It is not possible to change memory while the instance is running so you need to first stop the instance, change the memory and then start it again. See below a screenshot that shows how CPU/Memory can be customized for an instance that has been stopped.

An external data source is a data source that you can query directly from BigQuery, even though the data is not stored in BigQuery storage.

BigQuery supports the following external data sources:

Amazon S3

Azure Storage

Cloud Bigtable

Cloud Spanner

Cloud SQL

Cloud Storage

Drive

A managed instance group (MIG) is a group of identical virtual machines (VMs) that you can manage as a single entity. You can use a MIG to deploy and maintain a stateless application that runs directly on VMs. A MIG can automatically scale the number of VMs based on the load or a schedule. A MIG can also automatically heal the VMs if they become unhealthy or unavailable. A MIG is suitable for applications that need to run on VMs rather than containers or serverless platforms.

B is incorrect because Kubernetes Engine is a managed service for running containerized applications on a cluster of nodes. It is not necessary to use Kubernetes Engine if the application does not use containers and can run directly on VMs.

C is incorrect because Cloud Functions is a serverless platform for running event-driven code in response to triggers. It is not suitable for applications that need to run continuously and handle HTTP requests.

D is incorrect because Cloud Run is a serverless platform for running stateless containerized applications. It is not suitable for applications that do not use containers and can run directly on VMs.

Managed instance groups documentation

Choosing a compute option for Google Cloud

Comprehensive and Detailed In Depth Explanation:

The problem states that a subnet is nearing its IP address capacity, and the requirement is to expand it without downtime and with minimal operational cost, following Google-recommended practices.

A. Creating a second VPC with the same subnet IP range and peering: While VPC Network Peering allows communication between VPCs, having overlapping IP ranges is generally not recommended and can lead to routing complexities if not managed carefully. It also adds operational overhead of managing two VPCs. This is not the most straightforward or cost-effective solution for simply expanding IP capacity within the same logical network.

B. Deleting and recreating the subnet: Deleting a subnet that contains active VM instances will cause downtime for those instances, violating a key requirement.

C. Using the Google Cloud CLI tool to expand the primary IP range of your subnet: Google Cloud allows you to expand the primary IP range of an existing subnet after it ' s created, as long as there are no conflicting subnets in the VPC. This operation does not require deleting the subnet or restarting the existing VMs within it, thus avoiding downtime. It ' s a direct and cost-effective way to increase the available IP address space within the existing subnet. This is a Google-recommended practice for handling subnet capacity issues.

D. Permitting additional traffic with firewall rules: Firewall rules control network traffic based on IP ranges, protocols, and ports. They do not increase the number of available private IP addresses within the subnet. This option does not address the core issue of IP address exhaustion.

Therefore, expanding the primary IP range of the existing subnet using the Google Cloud CLI is the recommended solution that meets all the requirements: addressing IP capacity, minimizing operational costs, and avoiding downtime.

Google Cloud Documentation References:

Expanding Subnet IP Ranges: - This documentation explicitly describes how to expand the IP range of an existing subnet without downtime. It outlines the prerequisites and steps involved using the gcloud CLI or the Google Cloud Console.

VPC Network Overview: - Provides context on subnet IP ranges and their management.

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