Advanced GCP Interview Questions

23. How do you optimize the cost of running workloads in GCP?

Take the advantage of sustain to use the discount to decrease the cost of running workloads in the google cloud platform and application committed to use agreements for expected load. To significantly preserve the costs, use discovering virtual machines (VMs) for useless tasks. Use resource autoscaling to reach the demand while prevent the overprovisioning. Frequently review your instances and change the size according to nee of usage patterns. Use Google’s cost-management resources, include the Cost Explorer and Budget Alerts, to maintain an eye on and regulate billing.

24. Explain the concept of Infrastructure as Code (IaC) in GCP and tools you can use.

Configuration files are employed in Google Cloud Platform (GCP) Infrastructure as Code (IaC) to manage and provision cloud resources. This makes it practical to create repeatable and consistent setups utilize the code as opposed to people processes. Ansible for cloud resource automation and orchestration, Terraform for declarative resource management, and Google Cloud Deployment Manager for native templated deployments are essential to the instruments for Infrastructure as a Cloud (IaC) in GCP. These tools enable increase scalability, dependability, and automate the infrastructure procedures.

25. How would you design a highly available and scalable architecture in GCP?

Developing a scalable and highly available architecture in GCP includes:

• Use a global load balancer to distribute traffic between multi region.
• Deploy virtual machine instances across multiple location’s and regions with auto scale enabled on.
• Utilize the managed services like Cloud SQL database, BigQuery, and Firebase for backend operations.
• Combine cloud storage and cloud content delivery network for scaling, deploy content delivery globally.
• Combine cloud login and monitor for the routine upkeep and improve the performance.

26. Describe a multi-cloud strategy and how you can implement it using GCP.

A multi-cloud look at involves making use using different cloud services from the different providers to improve repetition, decrease expenses, and prevent vendor lock-in. This works with google cloud via BigQuery Omni for data analytics, Apigee to handle APIs across different environments, and Google Cloud’s Anthos for consistent management across clouds. Kubernetes Engine for orchestration, Virtual private cloud peering, and interconnects can all to be used to controlee integration with different cloud service providers. This approach to ensures uninterrupted communication and a combine management interface.

27. How do you ensure data security and compliance in GCP?

To ensure the data security and compliance in the Google Cloud Platform (GCP), it is an important to use identity and access management (IAM) to controls freedoms, allow audit logging to track and monitor the action, and encrypt the data when it is in transit and at rest. It is important to frequently install security patches and updates in addition to use the GCP’s integrated safety solutions, such Security Command Center, for threat detection and compliance checks. In addition, periodic security inspections and compliance to compliance regulations (like GDPR and HIPAA) ensure continuous compliance and security.

28. Explain the steps to migrate an existing on-premises application to GCP.

• Assessment and Planning: Analyze the application architecture as exists, the performance specifications, and the dependencies. Plan the migration strategy considering into consideration replatforming, rehosting, and refactoring.
• Provisioning GCP Resources: Building the necessary infrastructure on Google Cloud Platform (GCP) employing Virtual Machines (Compute Engine), Google Kubernetes Engine (GKE), or App Engine. This involves network, storage, and database architecture.
• Data Migration: To transfer data from the on-premises storage to google cloud platform, use the services like database migration or Google Cloud Storage Transfers Services.
• Application Deployment: After ensuring that each part has been set up and optimize the cloud, we can launch the application within the GCP environment.
• Testing and Optimization: Thoroughly test the application in the google cloud environment, maintain a close eye on performance, and implement any required changes to optimize for security, scalability, and cost-effectiveness.

29. How do you implement CI/CD pipelines in GCP?

To implement continuous integrations and continuous deployments CI/CD pipelines in usage under GCP:

• Source Code Management: Make advantage of Google Cloud Source Repositories or GitHub/Bitbucket connectivity.
• Continuous Integration: Automate the code packaging, testing, and deployment using the Google Cloud Build.
• Artifact Storage: Build artifacts may be kept in Google Cloud Storage, Artifact Registry or the Container Registry.
• Continuous Deployment: Use the Google Cloud Deploy or Cloud Run for automatic deployment to GKE, the App Engine, or Cloud Runs.
• Monitoring: Using Google Cloud Monitor and Logging to keep tabs on the performance and health of your cloud deployment.

30. What are Managed Instance Groups (MIGs), and how do you use them?

Controlled Instance Groups, or MIGs for simple terms, are groups of virtual instances in Google Cloud that are managed as a single entity. The next one is an autonomous instance that may grow and cure self. Managed instance group (MIGs) may ensure high availability by distribute the instances across multiple zones. By develop a group, establish its template, establishing scaling the instructions, and carry out it, they are used. It is easier to increase the capacity of MIGs while handling significant workloads effectively.

31. How do you design and manage data pipelines using GCP services?

Determining your data flow requirements is the first stage in develop and handle data pipelines on Google Cloud Platform. Employ the Cloud Storage for data storage, BigQuery for analytics, and Google Cloud Dataflow for batch and stream processing. Using the Cloud Composer to set up and track workflows. Use best practices for the data governance, security, and scalability throughout the pipeline. Sustain performance monitoring and improvement for the most important data processing.

32. Explain how you would handle disaster recovery and backup strategies in GCP.

I would start disaster recovery by transferring very important data to multiple regions using services like Cloud Storage and Cloud SQL. Putting up automated backups using applications like Cloud Snapshot for virtual machines or Cloud SQL automate the backups will be the next step. In addition, a multi-region load balancing and failover process was set up using Traffic Director to guarantee uninterrupted service availability. To be sure backups and recovery plans work correctly, they must be tested on a regularly. Last but not the least, moving virtual machines using Cloud Endure, one of Google’s managed services, helps improves the recovery efforts following an crucial time.

33. What are some common use cases for SSH tunneling in GCP?

• Secure Remote Access: Secure remote access to resources like virtual machines and databases can be achieved with Google Cloud Platform (GCP) via secure shell (SSH) tunneling.
• Proxying Traffic: It is frequently employed for secure proxy traffic between a local computer and google cloud-deployed resources, such as Kubernetes clusters.
• Database Connection: Secure connections to databases such as Cloud SQL can be created from local development environments via SSH tunneling.
• Bypassing Firewalls: It can be utilized for securely access internal GCP resources from external networks without avoiding firewalls.
• Secure File Transfer: Using SCP or SFTP, SSH tunneling allows safe file transfers between local machines and the Google Cloud Platform instances.

34. Explain the role of Cloud Armor in protecting applications deployed on Google Cloud Platform.

A safety precaution on the Google Cloud Platform called Cloud Armor protects the web apps from Distributed Denial-of-Service (DDoS) assaults and other online risks. By enable the users to set up and enforce security policies at the outer limits of the Google Cloud network, it acts as a means of defense. Applications’ availability and integrity are ensured by Cloud Armor’s features, that also assist reduce the risks. These capabilities includes geo-based access controls, IP whitelisting, and blacklisting.

35. What is the difference between Cloud Router and VPN tunnels in GCP?

The Cloud Router enable the dynamic routing between the networks within your Virtual Private Cloud (VPC) and other networks. Routes to your VPC networks are automatically offered by that fully managed a solution. Virtual private network tunnels, on the other hand, use encrypted communication over the open internet to offer safe connections between your VPC network and your on-premises network. VPN tunnels securely increase your network into on-premises environments, while Cloud Router handles routing within Google Cloud Platform.

36. What is the difference between GCP and AWS?

Amongst the most prominent cloud service providers, Google Cloud Platform (GCP) has grown rapidly through offering an extensive selection of solutions and services tailored to various business needs. It can be hard to get ready for a GCP interview if you are a beginner who only recently started out with cloud technology, a seasoned professional hoping to expand your expertise, or an intermediate level applicant looking to hone your skills.