Google Certified Professional Cloud Architect Interview Questions

Preparing for the exam interview is just as crucial as studying for the exam because it is the final stage in accomplishing your goals. When it comes to the GCP Cloud Architect exam interview, you should be aware that you will need not only technical experience in the field, but also confidence and the ability to present your answers effectively. As a result, we’ve compiled a list of the most common and excellent GCP Cloud Architect interview questions and answers that will help you understand how to respond to questions and prepare for the interview. Let’s start with a quick overview of the tasks and responsibilities of a cloud architect.

About the exam:

A Professional Cloud Architect enables corporations to leverage Google Cloud technologies. A Professional Cloud Architect can design, produce, and manage robust, defend, scalable, highly available, and effective solutions to stimulate business objectives. This certification validates the expertise of candidates and their ability to convert businesses with Google Cloud technology. The exam is meant for the following groups of people.

People who want to enhance skills with Cloud Architecture Certifications.
Anyone who is preparing for the Cloud Architect Exam from Google.
People who want to understand Public Cloud, Private Cloud, Hybrid Cloud Deployment.
AWS Solution Architect or Microsoft Azure Architects wants to understand Google Cloud Platform.
Anyone who wants to understand the Services offering from Google Cloud Platform.
Customers of Google Cloud Platform and want to understand services offered.
The customers of Amazon, Azure or any other public cloud wants to understand GCP Services.
Candidates who want to get an understanding of Google Cloud Platform – GCP.
Developers, Lead Developers who are using Google Cloud Platform Services, or any other public cloud services.

Let’s review the interview questions now.

Advanced Interview Questions

What experience do you have in designing, deploying, and managing cloud solutions using GCP?

As a GCP Cloud Architect, I have extensive experience in designing, deploying, and managing cloud solutions using Google Cloud Platform (GCP). I have been working with GCP for over five years and have successfully implemented cloud solutions for various organizations in different industries.

I have hands-on experience in designing and deploying highly scalable, secure, and reliable GCP solutions. I have designed and deployed various solutions like Virtual Machines, Kubernetes Clusters, Load Balancers, Storage Solutions, and Database Solutions, to name a few. I have also implemented solutions for Data Analytics and Machine Learning using GCP tools like BigQuery, Dataflow, and AI Platform.

I have deep knowledge of GCP security features like Network Security, IAM, and Encryption, and I have implemented solutions for compliance with different security and data privacy standards like PCI DSS, ISO 27001, and GDPR. I have extensive experience in managing GCP environments, including monitoring, troubleshooting, and maintenance. I have used tools like Stackdriver, GCP Console, and Cloud Shell to manage GCP environments.

In conclusion, my experience with GCP makes me confident in designing, deploying, and managing cloud solutions that meet the business and technical requirements of organizations.

Can you explain how you would design a highly available and scalable GCP architecture for a web application?

I would design a highly available and scalable architecture for a web application by utilizing various GCP services.

First, I would create a Virtual Private Cloud (VPC) to isolate the web application from the public internet and provide a secure environment. I would then create multiple subnets, one for the web application and another for the database.

Next, I would use Google Compute Engine (GCE) instances to host the web application, and I would use autoscaling groups to automatically adjust the number of instances based on the demand. This would ensure that the web application is highly available, as GCE instances can be automatically replaced in case of a failure.

To store the database, I would use Google Cloud SQL, which is a fully managed relational database service. I would also configure Cloud SQL to have automatic failover, ensuring high availability of the database. To balance the traffic to the web application, I would use Google Load Balancer, which distributes incoming traffic among multiple GCE instances. I would also configure Load Balancer to automatically route traffic to healthy instances, ensuring that the application is highly available.

To ensure data reliability, I would use Google Cloud Storage to store backups and backups would be scheduled regularly. Finally, I would monitor the application performance using Google Stackdriver, which would allow me to detect and resolve performance issues quickly.

In conclusion, by utilizing various GCP services, I would design a highly available and scalable architecture for the web application, ensuring that it is always available to users, even during high traffic periods.

Can you provide an example of a custom application deployment using GCP tools and services such as Compute Engine, Kubernetes, and Cloud Storage?

In this scenario, we have a custom application that needs to be deployed on a scalable infrastructure with high availability and resiliency. We will use the following GCP tools and services:

Compute Engine: This will be the main infrastructure provider where we will host our custom application.
Kubernetes: We will use Kubernetes as the orchestration engine to manage the deployment, scaling, and rollback of our application.
Cloud Storage: This will be used to store the Docker images of our custom application.

Here are the high-level steps for this deployment:

Create a Compute Engine instance with Kubernetes Engine pre-installed.
Create a Docker image of the custom application and upload it to Cloud Storage.
Create a Kubernetes deployment using the Docker image from Cloud Storage.
Create a Kubernetes service to expose the custom application to the public network.
Create a horizontal pod autoscaler to automatically scale the number of pods based on the application’s CPU utilization.
Monitor the deployment using GCP Stackdriver and take appropriate action based on the logs and metrics.

This is just a simple example of deploying a custom application using GCP tools and services. In a real-world scenario, there will be additional steps such as creating firewall rules, setting up load balancing, and securing the deployment with SSL certificates, etc. However, this example demonstrates the power of using GCP to deploy custom applications with ease and reliability.

How would you approach security and privacy considerations in a GCP deployment, such as ensuring data encryption, firewalls, and access control?

As a GCP Cloud Architect, I would approach security and privacy considerations in a GCP deployment in a multi-faceted and proactive manner.

Data encryption is a top priority for me, and I would ensure that all data stored in GCP is encrypted at rest and in transit. This can be achieved by enabling the appropriate encryption options in Google Cloud Storage, BigQuery, and other storage solutions. Additionally, I would explore using customer-managed encryption keys (CMEK) for added control and security.

Firewalls are a critical component of any cloud security strategy, and I would ensure that firewall rules are in place to restrict incoming and outgoing traffic. This includes configuring firewalls for specific projects, VPC networks, and individual instances to control access and reduce the attack surface.

Access control is another critical component of GCP security, and I would ensure that proper access control policies are in place for all projects, instances, and storage solutions. This would include implementing role-based access control (RBAC) to restrict access to sensitive data and resources, and using security groups and network policies to further restrict access.

In addition, I would also consider the use of security solutions such as Google Cloud Armor and Google Cloud Security Command Center to enhance the security of the GCP deployment.

Overall, security and privacy considerations are a top priority in any GCP deployment, and I would approach them with a comprehensive and proactive approach to ensure the confidentiality, integrity, and availability of customer data.

Can you discuss your experience with cloud migration and how you would approach migrating an on-premise application to GCP?

I have extensive experience in cloud migration and I would approach migrating an on-premise application to GCP in the following manner:

Assessment: The first step is to assess the current state of the on-premise application and the existing infrastructure. This includes reviewing the application architecture, identifying dependencies and constraints, and determining the cloud migration strategy.
Planning: Based on the assessment results, I would create a detailed migration plan, including a timeline and milestones, resource allocation, and risk mitigation strategies.
Preparation: I would then prepare the environment for migration, including setting up the necessary GCP infrastructure, creating virtual machines, and configuring the necessary networks, firewall rules, and security policies.
Migration: This involves moving the data and applications from the on-premise environment to GCP. I would use automated migration tools, such as the Google Cloud Storage Transfer Service, to minimize downtime and ensure that data is transferred securely.
Testing: Once the migration is complete, I would perform thorough testing to validate that the application is functioning correctly in the new environment.
Deployment: After successful testing, I would deploy the application to GCP and make any necessary configuration changes to ensure optimal performance and availability.
Monitoring: I would then monitor the application to ensure that it is running smoothly, identify any potential issues, and address them in a timely manner.

Overall, I would approach a cloud migration to GCP with a focus on minimizing downtime, ensuring data security, and optimizing the performance of the application in the new environment.

Can you explain how you would set up and manage disaster recovery and backup strategies in GCP?

As a GCP Cloud Architect, I would set up and manage disaster recovery and backup strategies in GCP by utilizing a combination of tools and services offered by Google Cloud Platform. First, I would implement a backup and disaster recovery plan for all critical data and systems. This would involve backing up data to multiple cloud storage services such as Google Cloud Storage, or utilizing snapshots for disks and virtual machine images.

I would also set up a multi-zone or multi-region configuration, so that if one region goes down, the data can be retrieved from another region. This can be achieved using services such as Google Cloud Load Balancer, Google Kubernetes Engine, or Google App Engine.

I would also ensure that disaster recovery procedures are in place, including regular testing and simulation of disaster scenarios to ensure that recovery processes work as expected. This would involve using Google Cloud Deployment Manager to automate the deployment of infrastructure and applications, as well as using Google Cloud Stackdriver to monitor and alert on any potential issues.

Additionally, I would set up and configure disaster recovery solutions such as Google Cloud DNS, Google Cloud VPN, and Google Cloud Interconnect to ensure seamless connectivity and data replication between different regions. Overall, my goal as a GCP Cloud Architect would be to design and implement a robust disaster recovery and backup strategy that ensures high availability, data protection, and seamless disaster recovery in case of any unforeseen events.

Can you discuss your experience with GCP cost optimization and how you would minimize GCP costs while maintaining application performance and reliability?

As a GCP Cloud Architect, I have extensive experience with GCP cost optimization. I understand the importance of maximizing the value of GCP investment while ensuring application performance and reliability. My approach to GCP cost optimization involves a combination of proactive cost monitoring and strategic resource utilization.

One of the first steps I take is to continuously monitor resource utilization and cost patterns. I use GCP’s cost optimization tools such as Cost Explorer, Budget and alerts, and usage reports to track cost trends and identify areas for improvement. This enables me to take proactive measures to minimize costs without sacrificing application performance and reliability.

I also ensure that the right resources are deployed for the right workloads. For example, using preemptible VMs for batch processing jobs that can tolerate temporary loss of resources, or using auto-scaling to adjust the number of instances based on actual demand. This helps to reduce idle resources and optimize the cost of resource utilization.

Another area of focus is optimizing storage costs. I make use of the right storage options based on the access patterns and data retention requirements of the application. For instance, using cheaper storage options like standard disk or cold line storage for infrequently accessed data, and more expensive options like SSD for high I/O workloads.

In conclusion, my experience with GCP cost optimization has taught me that a combination of cost monitoring, resource utilization optimization, and storage optimization can significantly minimize GCP costs while maintaining application performance and reliability.

How do you handle performance tuning and monitoring in GCP, and what tools and methodologies have you used in the past?

As a GCP Cloud Architect, I have extensive experience in performance tuning and monitoring in GCP. I handle performance tuning and monitoring in GCP by following a few key steps, including the following:

Identifying performance bottlenecks: The first step in performance tuning is to identify any bottlenecks or areas of concern in the system. This can be done using various tools such as Stackdriver, Monitoring, and Logging.
Load testing: Once I have identified the bottlenecks, I perform load testing to determine how the system behaves under various conditions and to see how it responds to different levels of stress.
Performance optimization: Based on the results of the load testing, I make recommendations for performance optimization. This may include making changes to the architecture, configuration, or resource allocation.
Continuous monitoring: Once the performance optimization steps have been taken, I monitor the system continuously to ensure that it is functioning as expected. This includes monitoring resource utilization, performance metrics, and other key indicators.

The tools and methodologies I have used in the past for performance tuning and monitoring in GCP include:

Stackdriver: Stackdriver is a comprehensive tool that allows me to monitor and manage all aspects of a GCP deployment. This includes monitoring performance, logs, and alerts.
Monitoring: Monitoring is another powerful tool in GCP that allows me to monitor the performance of resources in real-time.
Logging: Logging is an important aspect of performance tuning and monitoring. It allows me to track and analyze logs and events that are generated by the system.
Load testing: Load testing is a critical part of performance tuning and monitoring. I use tools such as Apache JMeter to simulate real-world traffic and stress test the system.
Performance optimization: I use various optimization techniques, such as auto-scaling, horizontal scaling, and resource allocation, to optimize the performance of a GCP deployment.

In conclusion, I use a combination of tools, methodologies, and best practices to handle performance tuning and monitoring in GCP. This includes identifying performance bottlenecks, load testing, performance optimization, and continuous monitoring.

Can you describe how you would integrate GCP services with other cloud platforms or on-premise infrastructure?

I have extensive experience in integrating GCP services with other cloud platforms and on-premise infrastructure. The first step in this process would be to identify the specific use case and requirements. Based on that, I would determine the best approach for the integration.

For example, if the client has an existing infrastructure on AWS, I would recommend using the Google Cloud Interconnect feature. This allows for a direct and secure connection between the two cloud platforms, enabling seamless data transfer between the two environments.

In the case of on-premise infrastructure, I would recommend using the Google Cloud VPN service. This allows for a secure and encrypted connection between the on-premise infrastructure and the GCP environment, enabling data transfer and communication between the two environments.

In addition to these methods, I would also recommend using services such as Google Cloud Storage, Google Pub/Sub, and Google Cloud Functions to enable communication and data transfer between the environments.

I would work closely with the client to understand their specific requirements and recommend the best approach for the integration. I would also ensure that the solution is scalable and secure, and that proper monitoring and logging are in place to detect and resolve any issues in real-time.

How do you stay current with GCP updates and changes, and how do you ensure your team stays informed and trained on the latest GCP technologies and best practices?

As a GCP Cloud Architect, staying current with GCP updates and changes is crucial to ensure that I can deliver the best solutions to my clients. I keep myself updated by regularly visiting the Google Cloud Platform website, subscribing to their newsletters and blogs, attending Google Cloud Next conference, and participating in online forums and discussion boards.

I also ensure that my team stays informed and trained on the latest GCP technologies and best practices by organizing regular training sessions and workshops. We also share updates and new information with each other, discuss new features and functionalities, and collaborate on projects to gain hands-on experience. Additionally, I encourage my team to pursue GCP certifications and attend relevant training programs and conferences.

Finally, I make sure that my team stays up to date with industry best practices and guidelines by conducting regular reviews of our processes and systems, and making any necessary updates or modifications. This helps us to continuously improve our skills and expertise and deliver the best results for our clients.

Basic Interview Questions

How would you describe an ideal cloud architect?

An ideal cloud architect would be the one who designs a cloud environment from a holistic viewpoint, meeting the company’s requirements and carrying out the deployment, monitoring, maintenance, and management tasks within the implemented cloud structure.

What is Google Cloud Platform?

Google Cloud Platform is a cloud platform that is managed by Google. It is a set of Compute, Storage, Virtual Machine, Networking, Big Data, Machine Learning, Databases, and Management services. These services run on the same infrastructure of Google that Google uses for its end-user products like YouTube, Gmail, and Google Search.

What are the layers of cloud computing?

The three layers of cloud computing are:

Infrastructure as a Service (IaaS)
Software as a Service (SaaS)
Platform as a Service (PaaS)

What is API? What are it’s uses?

API stands for Application Programming Interface. It has the following uses:

Eliminating the need to write fully-fledged programs.
Providing instructions to set up communication between one or more applications.
Allowing easy creation of applications and linking the cloud services with other systems.

What does Google Cloud Healthcare API do?

The Google Cloud Healthcare API makes data interchange between healthcare apps and Google Cloud solutions simple and standardised. With support for common healthcare data standards such as HL7® FHIR®, HL7® v2, and DICOM®, the Cloud Healthcare API delivers a fully managed, scalable, enterprise-grade development environment for building clinical and analytics solutions safely on Google Cloud.

What is a subnet?

A subnet is none other than a segmented piece of a larger network. Particularly, subnets are a logical partition of an IP network into multiple, smaller network segments. Various organizations use them to sub-divide larger networks into smaller and more efficient subnetworks.

Mention some services offered by GCP.

Some of the commonly used services of GCP are:

Computing and hosting
Databases
Storage
Networking
Machine learning
Big data

What do you mean by Google App engine?

Google App Engine (GCP App Engine) is a serverless platform that allows you to run your code directly while also ensuring that your app is available. Google will take care of all of your servers and other equipment. Furthermore, when your site’s traffic develops, GCP App Engine is responsible for delivering all built-in services and APIs, and you only pay for the resources you use.

What are the different models for deployment in cloud computing?

The deployment models in cloud computing are:

private
public
hybrid cloud

Explain the different layers of cloud architecture.

The different layers of cloud architecture are:

Physical layer: constitutes of the physical servers, network, and other aspects
Platform layer: Includes the operating system, apps, and other aspects
Infrastructure layer: Consists of storage, virtualized layers, and so on
Application layer: The layer that the end-user directly interacts with.

Mention the roles of IAM?

The types of roles in IAM are as follows:

Basic roles: Includes the Owner, Editor, and Viewer roles that existed prior to the introduction of IAM.
Predefined roles: Provides granular access for a specific service.
Custom roles: Provides granular access according to a user-specified list of permissions.

How is GCP beneficial?

The main advantages of using Google Cloud Platform are:

Google Cloud servers allow you to have access to your information and data anywhere.
GCP has an overall increased performance and service
It offers much better pricing deals in comparison to the other cloud service providers
Google Cloud is very fast in providing updates about server and security in an efficient manner
The Google Cloud platform and networks are secured and encrypted with various security measures.

How do you select database solution?

The best database for a system depends on the availability, consistency, durability, partition tolerance, latency, scalability, and query capability needs. For various subsystems, different systems employ different database solutions, which are then enabled to boost performance. Furthermore, choosing the improper database solution and features for a system can result in decreased performance.

What does VPC stand for?

VPC stands for Virtual Private Cloud.

What is the use of VPC?

A virtual private cloud (VPC) is one of the most efficient ways to connect to cloud resources from one’s own data centre. Each instance is assigned a private IP address that can be accessed from your data centre once you connect your data centre to the VPC where your instances are located. As a result, you can access resources in the public cloud as if they were on your own private network.

What is Google Cloud SDK?

The Google Cloud SDK, or Software Development Kit, is a suite of tools for managing Google Cloud Platform applications and resources. It includes the command-line utilities gsutil, gcloud, and bqcommand. Furthermore, the Cloud SDK downloads the gcloudtool automatically.

Mention some practices of cost-optimization.

Some prominent practices of cost optimization are:

Evaluate performance requirements: Determine the priority of applications and what minimum performance you require of them.
Use scalable design patterns: Improve performance and scalability with auto-scaling, compute choices, and storage configurations.
Identify and implement cost-saving approaches: Evaluate the cost for each running service while prioritizing the optimization for service availability and cost.

What is the full form of GKE?

GKE stands for Google Kubernetes Engine.

What are some of the features of GKE?

Some of the features of GKE are:

Autopilot mode of operation- Optimized cluster with pre-configured workload settings offers a nodeless experience. Maximizes operational efficiency and bolsters the security of your applications by restricting access only to Kubernetes API and safeguarding against node mutation. Payment to be made only for your running pods, not system components or operating system overhead.
Kubernetes applications-Enterprise-ready containerized solutions with prebuilt deployment templates, featuring portability, consolidated billing, and simplified licensing. These are not just container images, but open source, Google-built, and commercial applications that increase developer productivity, available now on Google Cloud Marketplace.
Pod and cluster auto-scaling-Horizontal pod autoscaling based on CPU utilization or custom metrics, cluster autoscaling that works on a per-node-pool basis, and vertical pod auto-scaling that continuously analyzes the CPU and memory usage of pods and dynamically adjusts their CPU and memory requests in response. Automatically scales the node pool and clusters across multiple node pools, based on changing workload requirements.

How can you achieve security, privacy, and compliance?

One can achieve security, privacy, and compliance by-

Managing risk with controls.
Implementing compute security controls.
Managing authentication and authorization.
Securing the network.
Building with application supply chain controls.
Implementing data security controls.
Auditing infrastructure with audit logs.

What are the types of migrations?

The three major types of migrations are:

Lift and shift
Rip and replace
Improve and move

What are Customer-managed encryption keys?

If you need more control over the keys used to encrypt data at rest within a Google Cloud project, certain Google Cloud services offer the option to safeguard data connected to those services using encryption keys owned by the client under Cloud KMS. Customer-managed encryption keys are the name for these keys. When you use CMEK to safeguard data in Google Cloud services, you have complete control over the CMEK.

What are the objectives of setting up a CI/CD pipeline for your data-processing workflow?

The objectives of setting up a CI/CD pipeline are:

Creating Cloud Storage buckets for your data.
Configuring the build trigger.
Forming the build, test, and production pipelines.
Configuring the Cloud Composer environment.

How do you plan Disaster Recovery?

RTO and RPO are the primary goals for restoring availability. The first step in a disaster recovery strategy is to set up backups and redundant workload components. These must be determined according to the business’s demands, and a strategy must be implemented to fulfil these goals, taking into account the locations and functions of workload data and resources.

Describe Google cloud deployment manager?

Google Cloud Deployment Manager is an infrastructure deployment service that automatically creates and manages Google Cloud resources. Moreover, creates deployments that have a variety of Google Cloud services, such as Cloud Storage, Compute Engine, and Cloud SQL configured to work together.

What is the role of cloud monitoring?

Cloud Monitoring gathers data from Google Cloud and application instrumentation in the form of metrics, events, and metadata. The BindPlane service may also collect data from over 150 typical application components, on-premise systems, and hybrid cloud systems. The Google cloud operations suite ingests the data and generates insights through dashboards, charts, and alarms. BindPlane is provided free of charge as part of the Google Cloud initiative.

What does IAM stand for?

Identity and Access Management

What is an Enterprise data warehouse?

An Enterprise data warehouse is one that consists not only of an analytical database but multiple critical analytical components and procedures. It, therefore, includes data pipelines, queries, and business applications required to fulfill the workloads of the organization.

What do you know about a data pipeline?

A data pipeline is an application that processes data via a series of linked processing steps. To move data between information systems, extract, transform, and load (ETL), data enrichment, and real-time data analysis, data pipelines can be used. As a result, data pipelines can be executed as a batch process, which executes and processes data when it is run, or as a streaming process, which executes constantly and processes data as it enters the pipeline.

What is the ETL procedure?

In data warehousing, data pipelines are frequently used to perform an extract, transform, and load (ETL) method. ETL solutions run outside of the data warehouse, allowing the data warehouse’s resources to be focused on concurrent querying rather than data preparation and transformation. One disadvantage of performing the transformation outside of the data warehouse is that it necessitates learning new tooling and languages to represent the transforms.