1

Deploying and implementing Compute Engine resources. Tasks include:
Launching a compute instance using Cloud Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)

Creating an autoscaled managed instance group using an instance template

Generating/uploading a custom SSH key for instances

Configuring a VM for Stackdriver monitoring and logging

Assessing compute quotas and requesting increases

Installing the Stackdriver Agent for monitoring and logging

2

Deploying and implementing Google Kubernetes Engine resources. Tasks include:
Deploying a Google Kubernetes Engine cluster

Deploying a container application to Google Kubernetes Engine using pods

Configuring Google Kubernetes Engine application monitoring and logging

3

Deploying and implementing App Engine, Cloud Run, and Cloud Functions resources. Tasks include, where applicable:
Deploying an application, updating scaling configuration, versions, and traffic splitting

Deploying an application that receives Google Cloud events (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)

4

Deploying and implementing data solutions. Tasks include:
Initializing data systems with products (e.g., Cloud SQL, Cloud Datastore, BigQuery, Cloud Spanner, Cloud Pub/Sub, Cloud Bigtable, Cloud Dataproc, Cloud Dataflow, Cloud Storage)

Loading data (e.g., command line upload, API transfer, import/export, load data from Cloud Storage, streaming data to Cloud Pub/Sub)

4

Deploying and implementing networking resources. Tasks include:
Creating a VPC with subnets (e.g., custom-mode VPC, shared VPC)

Launching a Compute Engine instance with custom network configuration (e.g., internal-only IP address, Google private access, static external and private IP address, network tags)

Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, tags, service accounts)

Creating a VPN between a Google VPC and an external network using Cloud VPN

Creating a load balancer to distribute application network traffic to an application (e.g., Global HTTP(S) load balancer, Global SSL Proxy load balancer, Global TCP Proxy load balancer, regional network load balancer, regional internal load balancer)

5

Deploying a solution using Cloud Marketplace. Tasks include:
Browsing Cloud Marketplace catalog and viewing solution details

Deploying a Cloud Marketplace solution

6

Deploying application infrastructure using Cloud Deployment Manager. Tasks include:
Developing Deployment Manager templates

Launching a Deployment Manager template

1

What are the various components of the Google Cloud Platform?
Google Cloud Platform (GCP) is composed of a set of elements that helps people in different ways. The various GCP elements are

- Google Compute Engine

- Google Cloud Container Engine

- Google Cloud App Engine

- Google Cloud Storage

- Google Cloud Dataflow

- Google BigQuery Service

- Google Cloud Job Discovery

- Google Cloud Endpoints

- Google Cloud Test Lab

- Google Cloud Machine Learning Engine

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2

What are the main advantages of using Google Cloud Platform?
Google Cloud Platform is a medium that provides its users access to the best cloud services and features. It is gaining popularity among the cloud professionals as well as users for the advantages if offer. Here are the main advantages of using Google Cloud Platform over others –

- GCP offers much better pricing deals as compared to the other cloud service providers

- Google Cloud servers allow you to work from anywhere to have access to your information and data.

- Considering hosting cloud services, GCP has an overall increased performance and service

- Google Cloud is very fast in providing updates about server and security in a better and more efficient manner

- The security level of Google Cloud Platform is exemplary; the cloud platform and networks are secured and encrypted with various security measures.

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3

Why should you opt for Google Cloud Hosting?
The reason for opting Google Cloud Hosting is the advantages it offers. Here are the advantages of choosing Google Cloud Hosting:

- Availability of better pricing plans

- Benefits of live migration of the machines

- Enhanced performance and execution

- Commitment to Constant development and expansion

- The private network provides efficiency and maximum time

- Strong control and security of the cloud platform

- Inbuilt redundant backups ensure data integrity and reliability

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4

What are the libraries and tools for cloud storage on GCP?
At the core level, XML API and JSON API are there for the cloud storage on Google Cloud Platform. But along with these, there are following options provided by Google to interact with the cloud storage.

- Google Cloud Platform Console, which performs basic operations on objects and buckets

- Cloud Storage Client Libraries, which provide programming support for various languages including Java, Ruby, and Python

- GustilCommand-line Tool, which provides a command line interface for the cloud storage

- There are many third party libraries and tools such as Boto Library.

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5

What do you know about Google Compute Engine?
Google Cloud Engine is the basic component of the Google Cloud Platform. Google Compute Engine is an IaaS product that offers self-managed and flexible virtual machines that are hosted on the infrastructure of Google. It includes Windows and Linux based virtual machines that may run on local, KVM, and durable storage options. It also includes REST-based API for the control and configuration purposes. Google Compute Engine integrates with GCP technologies such as Google App Engine, Google Cloud Storage, and Google BigQuery in order to extend its computational ability and thus creates more sophisticated and complex applications.

6

How are the Google Compute Engine and Google App Engine related?
Google Compute Engine and Google App Engine are complementary to each other. Google Compute Engine is the IaaS product whereas Google App Engine is a PaaS product of Google. Google App Engine is generally used to run web-based applications, mobile backends, and line of business. If you want to keep the underlying infrastructure in more of your control, then Compute Engine is a perfect choice. For instance, you can use Compute Engine for the implementation of customized business logic or in case, you need to run your own storage system.

7

Explain Auto-scaling in Google cloud computing
Without human intervention, you can mechanically provision and initiate new instances in AWS. Depending on various metrics and load, Auto-scaling is triggered.

8

Describe Hypervisor in Google Cloud Platform
Hypervisor is otherwise called as VMM (Virtual Machine Monitor). Hypervisor is said to be a computer hardware/software used to create and run virtual machines (virtual machines is also called as Guest machine). Hypervisor is the one that runs on a host machine.

9

Define VPC in the Google cloud platform
VPC is Google cloud platform is helpful is providing connectivity from the premise and to any of the region without internet. VPC Connectivity is for computing App Engine Flex instances, Kubernetes Engine clusters, virtual machine instance and few other resources depending on the projects. Multiple VPC can also be used in numerous projects.

10

Explain Google BigQuery in Google Cloud Platform
For traditional data warehouse, hardware setup replacement is required. In such case, Google BigQuery serves to be the replacement. In addition, BigQuery helps in organizing the table data into unit called as datasets.

11

You want to deploy an application on Cloud Run that processes messages from a Cloud Pub/Sub topic. You want to follow Google-recommended practices. What should you do?

1. Deploy your application on Cloud Run on GKE with the connectivity set to Internal.
2. Create a Cloud Pub/Sub subscription for that topic.
3. In the same Google Kubernetes Engine cluster as your application, deploy a container that takes the messages and sends them to your application.

12

You need to deploy an application, which is packaged in a container image, in a new project. The application exposes an HTTP endpoint and receives very few requests per day. You want to minimize costs. What should you do?
- Deploy the container on Cloud Run on GKE.

13

You are using Deployment Manager to create a Google Kubernetes Engine cluster. Using the same Deployment Manager deployment, you also want to create a DaemonSet in the kube-system namespace of the cluster. You want a solution that uses the fewest possible services. What should you do?

- With Deployment Manager, create a Compute Engine instance with a startup script that uses kubectl to create the DaemonSet.
Reference: K8 engine

14

You need a dynamic way of provisioning VMs on Compute Engine. The exact specifications will be in a dedicated configuration file. You want to follow Google's recommended practices. Which method should you use?

- Managed Instance Group

15

You have a Dockerfile that you need to deploy on Kubernetes Engine. What should you do?

- Create a docker image from the Dockerfile and upload it to Container Registry. Create a Deployment YAML file to point to that image. Use kubectl to create the deployment with that file.
- Reference: Kubernetes Engne

16

Your development team needs a new Jenkins server for their project. You need to deploy the server using the fewest steps possible. What should you do?

- Use GCP Marketplace to launch the Jenkins solution.
Reference: Jenkins

17

You need to update a deployment in Deployment Manager without any resource downtime in the deployment. Which command should you use?

- gcloud deployment-manager deployments update --config
- Reference: Deployment Manager

18

You need to run an important query in BigQuery but expect it to return a lot of records. You want to find out how much it will cost to run the query. You are using on-demand pricing. What should you do?

- Use the command line to run a dry run query to estimate the number of bytes read. Then convert that bytes estimate to dollars using the Pricing Calculator.
- Reference: BigQuery Costs

19

You have a single binary application that you want to run on Google Cloud Platform. You decided to automatically scale the application based on underlying infrastructure CPU usage. Your organizational policies require you to use virtual machines directly. You need to ensure that the application scaling is operationally efficient and completed as quickly as possible. What should you do?

- Create an instance template, and use the template in a managed instance group with autoscaling configured.

20

You significantly changed a complex Deployment Manager template and want to confirm that the dependencies of all defined resources are properly met before committing it to the project. You want the most rapid feedback on your changes. What should you do?

- Execute the Deployment Manager template using the ג€"-preview option in the same project, and observe the state of interdependent resources.