Google Cloud Associate Cloud Engineer Practice Exam - 3:

These are top 50 GCP ACE(Google Cloud Platform Associate Cloud Engineer) certification practice questions/cheatsheet (GCP ACE exam dumps) for professionals who are aspired to be GCP ACE certified. You will find these GCP ACE questions and answers very helpful in your GCP-ACE certification and interviews. Prepare well and All the very best.

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You deployed a Python application to GCP App Engine Standard service in the us-central region. Most of your customers are based in Japan and are experiencing slowness due to the latency. You want to transfer the application from us-central region to asia-northeast1 region to minimize latency. What should you do?

a). Create a new GCP project. Create a new App Engine Application in the new GCP project and
    set its region to asia-northeast-1. Delete the old App Engine application.
b). Update the region property to asia-northeast1 on the App Engine application.
c). Update the default region property to asia-northeast1 on the App Engine Service.
d). Deploy a new app engine application in the same GCP project and set the region to asianortheast1.
    Delete the old App Engine application.

Correct: a

Explanation:
    App Engine is regional, and you cannot change an app's region after you set it. You can deploy
    additional services in the App Engine, but they will all be targeted to the same region.

Reference: https://cloud.google.com/appengine/docs/locations

You deployed a java application in a single Google Cloud Compute Engine VM. During peak usage, the application CPU is maxed out and results in stuck threads which ultimately make the system unresponsive, and requires a reboot. Your operations team want to receive an email alert when the CPU utilization is greater than 95% for more than 10 minutes so they can manually change the instance type to another instance that offers more CPU. What should you do?

a). In Cloud Logging, create logs based metric for CPU usage and store it as a custom metric in
    Cloud Monitoring. Create an Alerting policy based on CPU utilization in Cloud Monitoring
    and trigger an email notification when the utilization exceeds the threshold.
b). Link the GCP project to a Cloud Monitoring workspace. Configure an Alerting policy based
    on CPU utilization in Cloud Monitoring and trigger an email notification when the utilization
    exceeds the threshold.
c). Write a custom script to monitor CPU usage and send an email notification when the usage
    exceeds the threshold.
d). Link the project to a Cloud Monitoring workspace. Write a custom script that captures CPU
    utilization every minute and sends to Cloud Monitoring as a custom metric. Add an uptime
    check based on the CPU utilization

Correct: b

Explanation:
    A Workspace is a tool for monitoring resources contained in one or more Google Cloud projects
    or AWS accounts. In our case, we create a Stackdriver workspace and link our project to this workspace.

Reference: https://cloud.google.com/monitoring/workspaces

Your company installs and manages several types of IoT devices all over the world. Events range from 50,000 to 500,000 messages a second. You want to identify the best solution for ingesting, transforming, storing and analyzing this data in GCP platform. What GCP services should you use?

!image

a). Cloud Pub/Sub for ingesting, Cloud Dataflow for transforming, Cloud Datastore for storing
    and BigQuery for analyzing the time-series data.
b). Firebase Messages for ingesting, Cloud Pub/Sub for transforming, Cloud Spanner for storing
    and BigQuery for analyzing the time-series data.
c). Cloud Pub/Sub for ingesting, Cloud Dataflow for transforming, Cloud Bigtable for storing
    and BigQuery for analyzing the time-series data.
d). Cloud Pub/Sub for ingesting, Cloud Storage for transforming, BigQuery for storing and
    Cloud Bigtable for analyzing the time-series data.

Correct: c

Explanation:
    For ingesting time series data, your best bet is Cloud Pub/Sub. For processing the data in
    pipelines, your best bet is Cloud Dataflow.
    That leaves us with two remaining options; both have BigQuery for analyzing the data. For
    storage, it is a choice between Bigtable and Datastore. Bigtable provides out of the box support
    for time series data. So using Bigtable for Storage is the right answer.

!image

Reference: https://cloud.google.com/bigtable/docs/schema-design-time-series

You migrated an internal HR system from an on-premises database to Google Cloud Compute Engine Managed Instance Group (MIG). The networks team at your company has asked you to associate the internal DNS records of the VMs with a custom DNS zone. You want to follow Google recommended practices. What should you do?

a). 1. Provision the VMs with custom hostnames.
b). 1. Create a new Cloud DNS zone and set its visibility to private. 2. When provisioning the
    VMs, associate the DNS records with the new DNS zone.
c). 1. Install a new BIND DNS server on Google Compute Engine, using the BIND name server
    software (BIND9). 2. Configure a Cloud DNS forwarding zone to direct all requests to the
    Internal BIND DNS server. 3. When provisioning the VMs, associate the DNS records with
    the Internal BIND DNS server.
d). 1. Create a new Cloud DNS zone and a new VPC and associate the DNS zone with the VPC.
    2. When provisioning the VMs, associate the DNS records with the new DNS zone.
    3. Configure firewall rules to block all external (public) traffic. 4. Finally, configure
    the DNS zone associated with the default VPC to direct all requests to the new DNS zone.

Correct: b

Explanation: 
    Our requirements here are Internal and Custom Zone. 
    You should do when you want internal DNS records in a custom zone. Cloud DNS gives you the
    option of private zones and internal DNS names.

Reference: https://cloud.google.com/dns/docs/overview#concepts

An application that you are migrating to Google Cloud relies on overnight batch jobs that take between 2 to 3 hours to complete. You want to do this at a minimal cost. Where should you run these batch jobs?

a). Run the batch jobs in a GKE cluster on a node pool with four instances of type f1-micro.
b). Run the batch jobs in a GKE cluster on a node pool with a single instance of type e2-small.
c). Run the batch jobs in a preemptible compute engine instance of appropriate machine type.
d). Run the batch jobs in a non-preemptible shared core compute engine instance that supports
    short periods of bursting.

Correct: c

Explanation:
    Requirements - achieve end goal while minimizing service costs. 
    We minimize the cost by selecting a preemptible instance of the appropriate type. If the
    preemptible instance is terminated, the next nightly run picks up the unprocessed volume.

Your company produces documentary videos for a reputed television channel and stores its videos in Google Cloud Storage for long term archival. Videos older than 90 days are accessed only in exceptional circumstances and videos older than one year are no longer needed. How should you optimise the storage to reduce costs?

a). Configure a lifecycle rule to transition objects older than 90 days to Coldline Storage Class.
    Configure an other lifecycle rule to delete objects older than 365 days from Coldline Storage Class.
b). Use a Cloud Function to rewrite the storage class to Coldline for objects older than 90 days.
    Use another Cloud Function to delete objects older than 275 days from Coldline Storage Class.
c). Use a Cloud Function to rewrite the storage class to Coldline for objects older than 90 days.
    Use another Cloud Function to delete objects older than 365 days from Coldline Storage Class.
d). Configure a lifecycle rule to transition objects older than 90 days to Coldline Storage Class.
    Configure another lifecycle rule to delete objects older than 275 days from Coldline Storage Class.

Correct: a

Explanation:
    Object Lifecycle Management does not rewrite an object when changing its storage class. When
    an object is transitioned to Nearline Storage, Coldline Storage, or Archive Storage using the
    SetStorageClass feature, any subsequent early deletion and associated charges are based on the
    original creation time of the object, regardless of when the storage class changed.

Reference: https://cloud.google.com/storage/docs/lifecycle

Your company is migrating an application from its on-premises data centre to Google Cloud. One of the applications uses a custom Linux distribution that is not available on Google Cloud. Your solution architect has suggested using VMWare tools to exporting the image and store it in a Cloud Storage bucket. The VM Image is a single compressed 64 GB tar file. You started copying this file using gsutil over a dedicated 1Gbps network, but the transfer is taking a very long time to complete. Your solution architect has suggested using all of the 1Gbps Network to transfer the file quickly. What should you do?
```
a). Increase the transfer speed by decreasing the TCP window size.
b). Restart the transfer from GCP console.
c). Upload the file Multi-Regional instead and move the file to Nearline Storage Class.
d). Use parallel composite uploads to speed up the transfer.

Correct: d

Explanation: 
    With cloud storage, Object composition can be used for uploading an object in parallel: you can
    divide your data into multiple chunks, upload each chunk to a distinct object in parallel, compose
    your final object, and delete any temporary source objects. This option helps maximize your bandwidth
    usage and ensures the file is uploaded as fast as possible.
```
Reference: https://cloud.google.com/storage/docs/composite-objects#uploads

Your team is responsible for the migration of all legacy on-premises applications to Google Cloud. Your team is a big admirer of serverless and has chosen App Engine Standard as the preferred choice for compute workloads. Your manager asked you to migrate a legacy accounting application built in C++, but you realized App Engine Standard doesn’t support C++. What GCP compute services should you use instead to maintain the serverless aspect? (Choose two answers)

a). Deploy the containerized version of the application in Cloud Run.
b). Convert the application into a set of functions and deploy them in Google Cloud Functions.
c). Deploy the containerized version of the application in Google Kubernetes Engine (GKE).
d). Deploy the containerized version of the application in Cloud Run on GKE.
e). Deploy the containerized version of the application in App Engine Flex.

Correct: a, d

Explanation:
    App engine standard currently supports Python, Java, Node.js, PHP, Ruby and Go.
    The question already states App Engine doesn't support C#. We are required to ensure we
    maintain the serverless aspect of our application.

    Cloud Run is a fully managed compute platform that automatically scales your stateless
    containers. Cloud Run is serverless: it abstracts away all infrastructure management, so you can
    focus on what matters most—building great applications. Run your containers in fully managed
    Cloud Run or on Anthos, which supports both Google Cloud and on‐premises environments.
    Cloud Run is built upon an open standard, Knative, enabling the portability of your applications.

    Cloud Run implements the Knative serving API, an open-source project to run serverless
    workloads on top of Kubernetes. That means you can deploy Cloud Run services anywhere
    Kubernetes runs. And suppose you need more control over your services (like access to GPU or
    more memory). In that case, you can also deploy these serverless containers in your GKE cluster
    instead of using the fully managed environment. When using the fully managed environment,
    Cloud Run on GKE is serverless.

Reference: https://cloud.google.com/appengine/docs/standard/
Reference: https://cloud.google.com/run
Reference: https://github.com/knative/serving/blob/master/docs/spec/spec.md
Reference: https://cloud.google.com/blog/products/serverless/cloud-run-bringing-serverless-tocontainers

You've deployed a microservice that uses sha1 algorithm with a salt value to has usernames. You deployed this to GKE cluster using deployment file:

apiVersion: apps/v1
kind: Deployment
metadata:
    name: sha1_hash_app-deployment
spec:
selector:
    matchLabels:
    app: sha1_hash_app
    replicas: 3

    template:
    metadata:
        labels:
            app: sha1_hash_app
    spec:
        containers:
        - name: hash-me
        image: gcr.io/hash-repo/sha1_hash_app:2.17
        env:
        - name: SALT_VALUE
            value: "z0rtkty12$!"
        ports:
        - containerPort: 8080

You need to make changes to prevent the salt value from being stored in plain text. You want to follow Google-recommended practices. What should you do?

a). Save the salt value in a Kubernetes ConfigMap object. Modify the YAML configuration file
    to reference the ConfigMap object.
b). Bake the salt value into the container image.
c). Save the salt value in a Kubernetes Persistent Volume. Modify the YAML configuration file to
    include a Persistent Volume Claim to mount the volume and reference the password from the file.
d). Save the salt value in a Kubernetes secret object. Modify the YAML configuration file to
    reference the secret object.

Correct: d

Explanation:
    In GKE, you can create a secret to hold the password; and then use the secret as an environment
    variable in the YAML file.
    You can create a secret using:

    kubectl create secret generic passwords --from-literal sha1_hash_app_SALT_VALUE=z0rtkty12$!

    And you can then modify the YAML file to reference this secret as shown below.

    apiVersion: apps/v1
    kind: Deployment
    metadata:
    name: sha1_hash_app-deployment
    spec:
    selector:
        matchLabels:
        app: sha1_hash_app
        replicas: 3
        template:
        metadata:
            labels:
            app: sha1_hash_app
        spec:
            containers:
            - name: hash-me
            image: gcr.io/hash-repo/sha1_hash_app:2.17
            env:
            - name: SALT_VALUE
                valueFrom:
                    secretKeyRef:
                        name: passwords
                        key: sha1_hash_app_SALT_VALUE
            ports:
            - containerPort: 8080

Reference: https://cloud.google.com/kubernetes-engine/docs/concepts/secret

You developed an enhancement to a production application deployed in App Engine Standard service. Unit testing and user acceptance testing has succeeded, and you deployed the new version to production. Users have started complaining of slow performance after the recent update, and you need to revert to the previous version immediately. How can you do this?

a). Deploy the previous version as a new App Engine Application and use traffic splitting feature
    to send all traffic to the new application.
b). In the App Engine Console, identify the App Engine application versions and make the
    previous version the default to route all traffic to it.
c). In the App Engine Console, identify the App Engine application and select Revert.
d). Execute gcloud app restore to rollback to the previous version.

Correct: b

Explanation:
    You can roll back to a previous version in the app engine GCP console. Go back to the list of
    versions and check the box next to the version that you want to receive all traffic and click the
    MAKE DEFAULT button located above the list. Traffic immediately switches over to the selected version.

Reference: https://cloud.google.com/community/tutorials/how-to-roll-your-app-engine-managed-vms-app-back-to-a-previous-version-part-1

You want to migrate a public NodeJS application, which serves requests over HTTPS, from your on-premises data centre to Google Cloud Platform. You plan to host it on a fleet of instances behind Managed Instances Group (MIG) in Google Compute Engine. You need to configure a GCP load balancer to terminate SSL session before passing traffic to the VMs. Which GCP Load balancer should you use?

a). Use HTTP(S) load balancer.
b). Use External TCP proxy load balancer.
c). Use Internal TCP load balancer.
d). Use External SSL proxy load balancer.

Correct: a

Explanation:
    This option fits all requirements. It can serve public traffic, can terminate SSL at the load
    balancer and follows google recommended practices.

    "The backends of a backend service can be either instance groups or network endpoint groups
    (NEGs), but not a combination of both."

    "An external HTTP(S) load balancer distributes traffic from the internet."

    "The client SSL session terminates at the load balancer."

    "For HTTP traffic, use HTTP Load Balancing instead."

Reference: https://cloud.google.com/load-balancing/docs/https

The application development team at your company wants to use the biggest CIDR range possible for a VPC and has asked for your suggestion. Your operations team is averse to using any beta features. What should you suggest?

a). Use 10.0.0.0/8 CIDR range.
b). Use 0.0.0.0/0 CIDR range.
c). Use 172.16.0.0/12 CIDR range.
d). Use 192.168.0.0/16 CIDR range.

Correct: a

Explanation:
    The private network range is defined by IETF (Ref: https://tools.ietf.org/html/rfc1918) and
    adhered to by all cloud providers. The supported internal IP Address ranges are
    24-bit block 10.0.0.0/8 (16777216 IP Addresses)
    20-bit block 172.16.0.0/12 (1048576 IP Addresses)
    16-bit block 192.168.0.0/16 (65536 IP Addresses)
    10.0.0.0/8 gives you the most extensive range - 16777216 IP Addresses.

Your company is migrating a mission-critical application from the on-premises data centre to Google Cloud Platform. The application requires 12 Compute Engine VMs to handle traffic at peak usage times. Your operations team have asked you to ensure the VMs restart automatically (i.e. without manual intervention) if/when they crash, and the processing capacity of the application does not reduce down during system maintenance. What should you do?

a). Deploy the application on a Managed Instance Group (MIG) that disables the creation retry
    mode by setting the --nocreation-retries flag.
b). Create an instance template with availability policy that turns off the automatic restart
    behaviour and sets on-host maintenance to terminate instances during maintenance events.
    Deploy the application on a Managed Instance Group (MIG) based on this template.
c). Create an instance template with availability policy that turns on the automatic restart
    behaviour and sets on-host maintenance to live migrate instances during maintenance events.
    Deploy the application on a Managed Instance Group (MIG) based on this template.
d). Deploy the application on a Managed Instance Group (MIG) with autohealing health check
    set to healthy (HTTP).

Correct: c

Explanation:
    Requirements
    12 instances - indicates we need to look for MIG (Managed Instances Group) where we can
    configure healing/scaling settings.
    Highly available during system maintenance - indicates we need to look for Live Migration.
    Automatically restart on crash - indicates we need to look for options that enable automatic
    restarts.

    Enabling automatic restart ensures that compute engine instances are automatically restarted
    when they crash. And Enabling "Migrate VM Instance" enables live migrates, i.e. compute
    instances are migrated during system maintenance and remain running during the migration.
    Automatic Restart - If your instance is set to terminate when there is a maintenance event, or if
    your instance crashes because of an underlying hardware issue, you can set up Compute Engine
    to automatically restart the instance by setting the automaticRestart field to true. This setting
    does not apply if the instance is taken offline through a user action, such as calling sudo
    shutdown, or during a zone outage.

    Enabling the Migrate VM Instance option migrates your instance away from an infrastructure
    maintenance event, and your instance remains running during the migration. Your instance might
    experience a short period of decreased performance, although generally, most instances should
    not notice any difference. Live migration is ideal for instances that require constant uptime and
    can tolerate a short period of decreased performance.

Reference: https://cloud.google.com/compute/docs/instances/setting-instance-scheduling-options#autorestart
Reference: https://cloud.google.com/compute/docs/instances/setting-instance-scheduling-options#live_migrate

A recent reorganization in your company has seen the creation of a new data custodian team – responsible for managing data in all storage locations. Your production GCP project uses buckets in Cloud Storage, and you need to delegate control to the new team to manage objects and buckets in your GCP project. What role should you grant them?

a). Grant the data custodian team Storage Object Admin IAM role.
b). Grant the data custodian team Storage Object Creator IAM role.
c). Grant the data custodian team Storage Admin IAM role.
d). Grant the data custodian team Project Editor IAM role.

Correct: c

Explanation:
    This role grants full control of buckets and objects. When applied to an individual bucket, control
    applies only to the specified bucket and objects within the bucket.

Reference: https://cloud.google.com/iam/docs/understanding-roles#storage-roles

You are in the process of migrating a mission-critical application from your on-premises data centre to Google Kubernetes Engine (GKE). Your operations team do not want to take on the overhead for upgrading the GKE cluster and have asked you to ensure the Kubernetes version is always stable and supported. What should you do?

a). When provisioning the GKE cluster, ensure you use the latest stable and supported version.
b). Update your GKE cluster to turn on GKE’s node auto-upgrade feature.
c). Update your GKE cluster to turn on GKE’s node auto-repair feature.
d). When provisioning the GKE cluster, use Container Optimized OS node images.

Correct: b

Explanation:
    Node auto-upgrades help you keep the nodes in your cluster up to date with the cluster master
    version when your master is updated on your behalf. When you create a new cluster or node pool
    with Google Cloud Console or the gcloud command, node auto-upgrade is enabled by default.

Reference: https://cloud.google.com/kubernetes-engine/docs/how-to/node-auto-upgrades

Your company stores sensitive user information (PII) in three multi-regional buckets in US, Europe and Asia. All three buckets have data access logging enabled on them. The compliance team has received reports of fraudulent activity and has begun investigating a customer care representative. It believes the specific individual may have accessed some objects they are not authorized to and may have added labels to some files in the buckets to enable favourable discounts for their friends. The compliance team has asked you to provide them with a report of activities for this customer service representative on all three buckets. How can you do this efficiently?

a). Enable a Cloud Trace on the bucket and wait for the user to access objects/set metadata to
    capture their activities.
b). Retrieve this information from the Cloud Storage bucket page in GCP Console.
c). Apply the necessary filters in Cloud Logging Console to retrieve this information.
d). Retrieve this information from Activity logs in GCP Console.

Correct: c

Explanation:
    Our requirements are - sensitive data, verify access, fewest possible steps.

    Data access logs are already enabled, so we already record all API calls that read the
    configuration or metadata of resources, as well as user-driven API calls that create, modify, or
    read user-provided resource data. Data Access audit logs do not record the data-access operations
    on resources that are publicly shared (available to All Users or All Authenticated Users), or that
    can be accessed without logging into Google Cloud.

    Since we are dealing with sensitive data, it is safe to assume that these buckets are not publicly
    shared and therefore enabling Data access logging logs all data-access operations on resources.
    These logs are sent to Stackdriver where they can be viewed by applying a suitable filter.

    Unlike activity logs, retrieving the required information to verify is quicker through Stackdriver
    as you can apply filters such as:

    resource.type="gcs_bucket"
    (resource.labels.bucket_name="gcp-ace-lab-255520" OR resource.labels.bucket_name="gcp-ace-lab-255521"
    OR resource.labels.bucket_name="gcp-ace-lab-255522")
    (protoPayload.methodName="storage.objects.get" OR protoPayload.methodName="storage.objects.update")
    protoPayload.authenticationInfo.principalEmail="XXXXXXXXXXX@gXXXX.com"

    and query just the gets and updates, for specific buckets for a specific user. This option involves
    fewer steps and is more efficient. Data access logging is not enabled by default and needs to be
    enabled explicitly.

Your finance department wants you to create a new billing account and link all development and test Google Cloud Projects to the new billing account. What should you do?

a). Ask your security administrator to grant you the Billing Account Administrator role on the
    existing Billing Account. Link all development and test projects to the existing Billing Account.
b). Ask your security administrator to grant you the Billing Account Creator role on the GCP
    organization and Project Billing Manager role on all the development and test projects. Link
    all the development and test projects to an existing Billing Account.
c). Ask your security administrator to grant you the Billing Account Creator role on the GCP
    organization and Project Billing Manager role on all the development and test projects. Create a
    new Billing Account and link all the development and test projects to the new Billing Account.
d). Ask your security administrator to grant you the Billing Account Administrator role on the existing
    Billing Account. Create new development and test projects and link them to the existing Billing Account.

Correct: c

Explanation:
    We are required to link an existing google cloud project with a new billing account.

    The purpose of the Project Billing Manager is to Link/unlink the project to/from a billing
    account. It is granted at the organization or project level. Project Billing Manager role allows a
    user to attach the project to the billing account, but does not grant any rights over resources.
    Project Owners can use this role to allow someone else to manage the billing for the project
    without granting them resource access.

    Billing Account Creator - Use this role for initial billing setup or to allow the creation of
    additional billing accounts.

Reference: https://cloud.google.com/billing/docs/how-to/billing-access

You are migrating your on-premises workloads to GCP VPC, and you want to use Compute Engine virtual machines. You want to separate the Finance team VMs and the Procurement team VMs into separate subnets. You need all VMs to communicate with each other over their internal IP addresses without adding routes. What should you do?

a). Use Deployment Manager to create two VPCs, each with a subnet in the same region. Ensure
    the subnets use overlapping IP range.
b). Use Deployment Manager to create a new VPC with 2 subnets in the same region. Ensure the
    subnets use the same IP range.
c). Use Deployment Manager to create two VPCs, each with a subnet in a different region.
    Ensure the subnets use non-overlapping IP range.
d). Use Deployment Manager to create a new VPC with 2 subnets in 2 different regions. Ensure
    the subnets use non-overlapping IP range.

Correct: d

Explanation:
    When we create subnets in the same VPC with different CIDR ranges, they can communicate
    automatically within VPC. "Resources within a VPC network can communicate with one another
    by using internal (private) IPv4 addresses, subject to applicable network firewall rules."

Reference: https://cloud.google.com/vpc/docs/vpc

You deployed a Java application on four Google Cloud Compute Engine VMs in two zones behind a network load balancer. During peak usage, the application has stuck threads. This issue ultimately takes down the whole system and requires a reboot of all VMs. Your operations team have recently heard about self-healing mechanisms in Google Cloud and have asked you to identify if it is possible to automatically recreate the VMs if they remain unresponsive for 3 attempts 10 seconds apart. What should you do?

a). Use a global HTTP(s) Load Balancer instead and set the load balancer health check to healthy (HTTP).
b). Enable autohealing and set the autohealing health check to healthy (HTTP).
c). Use a global HTTP(s) Load Balancer instead and limit Requests Per Second (RPS) to 10.
d). Enable autoscaling on the Managed Instance Group (MIG).

Correct: b

Explanation:
    To enable auto-healing, you need to group the instances into a managed instance group.
    Managed instance groups (MIGs) maintain the high availability of your applications by
    proactively keeping your virtual machine (VM) instances available. An auto-healing policy on
    the MIG relies on an application-based health check to verify that an application is responding as
    expected. If the auto-healer determines that an application isn't responding, the managed instance
    group automatically recreates that instance.

    It is essential to use separate health checks for load balancing and auto-healing. Health checks
    for load balancing can and should be more aggressive because these health checks determine
    whether an instance receives user traffic. You want to catch non-responsive instances quickly, so
    you can redirect traffic if necessary. In contrast, health checking for auto-healing causes
    Compute Engine to replace failing instances proactively, so this health check should be more
    conservative than a load balancing health check.

You want to deploy a cost-sensitive application to Google Cloud Compute Engine. You want the application to be up at all times, but because of the cost-sensitive nature of the application, you only want to run the application in a single VM instance. How should you configure the managed instance group?

a). Enable autoscaling on the Managed Instance Group (MIG) and set minimum instances to 1
    and maximum instances to 2.
b). Enable autoscaling on the Managed Instance Group (MIG) and set minimum instances to 1
    and maximum instances to 1.
c). Disable autoscaling on the Managed Instance Group (MIG) and set mininum instances to 1
    and maximum instances to 2.
d). Disable autoscaling on the Managed Instance Group (MIG) and set mininum instances to 1
    and maximum instances to 1.

Correct: b

Explanation:
    Requirements:
        1. Since we need the application running at all times, we need a minimum 1 instance.
        2. Only a single instance of the VM should run, we need a maximum 1 instance.

    We want the application running at all times. If the VM crashes due to any underlying hardware
    failure, we want another instance to be added to MIG so that application can continue to serve
    requests. We can achieve this by enabling autoscaling.

    The only option that satisfies these three is Enable autoscaling on the Managed Instance
    Group (MIG) and set minimum instances to 1 and maximum instances to 1.

Reference: https://cloud.google.com/compute/docs/autoscaler

You are developing a simple application in App Engine Standard service. Unit testing and user acceptance testing has succeeded, and you want to build a new App Engine application to serve as your performance testing environment. What should you do?

a). Configure a Deployment Manager YAML template to copy the application from the development GCP
    project into the performance testing GCP project.
b). Create a new GCP project for the performance testing environment using gcloud and copy the application
    from the development GCP project into the performance testing GCP project.
c). Create a new GCP project for the performance testing environment using gcloud and deploy your App
    Engine application to the new GCP project.
d). Use gcloud to deploy the application to a new performance testing GCP project by specifying the 
    --project parameter. Select Yes when prompted for confirmation on creating a new project.

Correct: c

Explanation:
You can deploy to a different project by using --project flag. By default, the service is deployed
the current project configured via:

$ gcloud config set core/project PROJECT

To override this value for a single deployment, use the --project flag:

$ gcloud app deploy ~/my_app/app.yaml --project=PROJECT

Reference: https://cloud.google.com/sdk/gcloud/reference/app/deploy

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