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Google · Cloud Basics
Practice Cloud Basics questions specifically asked in Google interviews – ideal for online test preparation, technical rounds and final HR discussions.
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Go through each question and its explanation. Use this page for targeted revision just before your Google Cloud Basics round.
A Distributed Denial-of-Service (DDoS) attack overwhelms a server with excessive requests. Cloud providers offer built-in DDoS protection and rate limiting to defend against it.
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A multi-cloud strategy uses services from more than one cloud vendor. It helps improve resilience, avoid vendor lock-in, and optimize performance by picking the best tools from each provider.
Tools like Terraform, Anthos, and Azure Arc provide unified management. They allow consistent policy enforcement, deployment, and monitoring across environments.
Active-active setups run workloads simultaneously in multiple regions. They provide near-zero downtime during outages but cost more to operate.
Choose regions close to your customers for lower latency. Consider data residency laws, available services, and cost differences before deciding.
Start with discovery to map dependencies, then move non-critical workloads first. Use hybrid connectivity like VPN or Direct Connect, test performance, and validate backups before full migration.
First, restore service using rollback or backup. Then conduct a post-mortem to identify the root cause, update runbooks, and improve monitoring to prevent recurrence.
AWS offers VPC Flow Logs, Azure has Network Watcher, and GCP uses Cloud Armor for traffic analysis and DDoS protection. These tools track traffic patterns and detect suspicious activities automatically.
Zero Trust means never trust by default — always verify every request. It enforces strict identity checks and segmentation, assuming that both internal and external networks can be compromised.
IaC allows you to provision and manage cloud resources using declarative code. This ensures repeatable, version-controlled, and auditable infrastructure management.
BigQuery is GCP’s serverless data warehouse designed for large-scale analytics using SQL. It is optimized for high-speed query performance on petabytes of data.
Automating backups ensures data protection even if an entire region fails. Cross-region replication adds extra durability and disaster recovery coverage.
Monitor CPU, memory, disk I/O, and network utilization to ensure healthy performance. Also track latency, error rates, and request counts to detect bottlenecks early.
Storage classes allow data to be placed in cost-effective tiers. Frequently accessed data stays in hot storage, while infrequent data moves to cold or archive storage.
Automation tools eliminate repetitive manual steps and ensure consistency. This leads to faster provisioning, predictable outcomes, and reduced operational costs.
GCP provides infrastructure, platform, and software services for compute, storage, networking, and AI. It powers products like YouTube and Gmail, and supports enterprise workloads.
The Shared Responsibility Model defines who manages which part of security. The provider secures the infrastructure (data centers, hardware), while users secure their data, identities, and configurations.
Serverless computing automatically handles scaling and billing per execution. This reduces costs for infrequent or unpredictable workloads.
Cloud SQL offers managed MySQL, PostgreSQL, and SQL Server databases. It handles backups, replication, and automatic failover for high availability.
Alerts notify teams when metrics exceed defined limits. They help respond quickly to downtime or resource overuse.
Monitoring can trigger automated rollbacks or alerts when deployment errors occur. Integrating tools like Prometheus or CloudWatch ensures continuous visibility throughout the release cycle.
Lifecycle policies automatically move or delete data based on age or access patterns. They help save costs and manage long-term data retention efficiently.
Multi-region storage replicates data across geographically distant data centers. This improves availability, reduces latency for global users, and provides disaster recovery protection.
Managed databases handle routine operations like patching, scaling, backups, and failover. This saves time for DevOps teams and ensures consistent performance and security.
Implement unified IAM policies, encrypt data at rest and in transit, and use secure VPN or private links. Continuous monitoring and centralized logging keep visibility across all environments.
Terraform by HashiCorp lets you manage infrastructure across AWS, Azure, and GCP. It uses declarative configuration files and tracks resource state for repeatable deployments.
Terraform is a multi-cloud open-source tool that uses HCL syntax. CloudFormation is AWS-native and uses JSON or YAML. Terraform is more flexible across providers, while CloudFormation offers deeper AWS integration.
Cloud platforms provide scalability, API-based provisioning, and managed services. This allows DevOps teams to deploy, test, and scale applications rapidly with minimal infrastructure overhead.
Global load balancers manage incoming requests across multiple cloud regions or vendors. This improves fault tolerance and reduces latency for global applications.
Google Anthos allows consistent Kubernetes cluster management across on-prem and cloud providers. It standardizes policies and deployment pipelines across environments.
A multi-cloud setup avoids vendor lock-in and improves redundancy. It also lets organizations pick specialized services from each provider for performance or cost advantages.
StackDriver Monitoring (now Cloud Monitoring) provides visibility into GCP, AWS, and hybrid workloads. It offers dashboards, uptime checks, and alerting policies.
Centralized logging aggregates logs from multiple services into one location. It simplifies troubleshooting, security analysis, and compliance auditing by providing a single source of truth.
Cloud providers handle the security *of* the cloud — like data centers and networks. Users manage security *in* the cloud — like access control and data protection.
Elasticity means automatically adjusting computing resources based on demand. For example, a web app can scale up during high traffic and scale down when idle — saving cost while maintaining performance.
Compute Engine is GCP’s Infrastructure-as-a-Service offering that provides customizable virtual machines. It supports both Linux and Windows instances with flexible machine types.
Cloud Functions is GCP’s serverless compute service. You can run short pieces of code triggered by HTTP requests, storage changes, or Pub/Sub messages.
A Project is the primary organizational unit in GCP that contains resources like VMs, storage, and APIs. Each project has its own billing, IAM policies, and unique project ID for tracking and permissions.
A Service Account is a special Google account used by applications or services instead of users. It enables secure server-to-server communication and resource access through keys or tokens.
A VPC is a logically isolated section of a cloud provider’s network. It lets you define subnets, routing tables, and firewalls to control communication between resources.
Encryption protects data from unauthorized access by converting it into unreadable text. Most cloud providers support encryption both at rest and in transit.