Table of Contents
Google Cloud Platform (GCP) is a leading cloud computing service offering a comprehensive suite of infrastructure and application services. Whether you’re considering migration to GCP or looking to optimize your existing cloud deployment, these FAQs provide essential information. At CloudRank, we’ve compiled this extensive resource to help you navigate the Google Cloud ecosystem effectively.
GCP Basics
1. What is Google Cloud Platform (GCP)?
Google Cloud Platform is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search, Gmail, and YouTube. It offers a range of services including computing, data storage, data analytics, and machine learning.
2. How does GCP differ from other cloud providers like AWS and Azure?
While all three major cloud providers offer similar core services, GCP differentiates itself with:
- Superior networking performance and global infrastructure
- Cutting-edge AI and machine learning capabilities
- Innovative pricing models including sustained use discounts
- Deep integration with Google’s ecosystem
- Strong data analytics offerings
- Leading container technologies (Kubernetes originated at Google)
3. What types of services does GCP offer?
GCP offers 200+ services across categories including:
- Compute (VMs, containers, serverless)
- Storage and databases
- Networking
- Big data and analytics
- Machine learning and AI
- Identity and security
- Management tools
- Developer tools
- IoT, media, and gaming solutions
4. Is GCP suitable for businesses of all sizes?
Yes, GCP scales to meet the needs of organizations of all sizes:
- Startups benefit from GCP’s free tier and startup credits
- Small and medium businesses can leverage pay-as-you-go pricing
- Enterprises can utilize GCP’s global infrastructure and advanced services
- GCP works for both cloud-native applications and traditional workloads
5. What is a GCP project?
A GCP project is the main organizing entity for Google Cloud resources. It contains your Google Cloud resources, enables you to manage API access, set permissions, and manage billing. Each project is identified by a unique project ID and project number.
Getting Started with GCP
6. How do I create a GCP account?
To create a GCP account:
- Go to cloud.google.com
- Click “Get started for free” or “Console”
- Sign in with your Google account or create a new one
- Complete the sign-up process, including entering payment details (required for verification but you won’t be charged until you upgrade)
- Set up your first project
7. What is included in the GCP free tier?
The GCP free tier includes:
- $300 credit for new users to spend on Google Cloud during the first 90 days
- “Always Free” resources that provide limited access to many common Google Cloud resources free of charge, including:
- Compute Engine: 1 e2-micro VM instance per month
- Cloud Storage: 5 GB per month of regional storage
- Cloud Functions: 2 million invocations per month
- BigQuery: 1 TB of queries per month and 10 GB of storage
8. How can I manage GCP costs effectively?
To manage GCP costs:
- Set budgets and alerts in the GCP Billing console
- Use committed use discounts for predictable workloads
- Take advantage of sustained use discounts
- Rightsize your resources based on actual usage
- Use preemptible VMs for fault-tolerant workloads
- Implement lifecycle policies for storage
- Consider a cloud cost optimization service for comprehensive savings
9. What tools do I need to start working with GCP?
Essential GCP tools include:
- Google Cloud Console (web interface)
- Google Cloud SDK and gcloud CLI (command-line tools)
- Cloud Shell (browser-based shell environment)
- Cloud APIs and client libraries
- IDE plugins for VS Code, IntelliJ, etc.
- Terraform for infrastructure as code
10. What certifications are available for GCP professionals?
Google Cloud offers several certification paths:
- Foundational: Cloud Digital Leader
- Associate: Cloud Engineer
- Professional roles: Cloud Architect, Data Engineer, Cloud Developer, Cloud DevOps Engineer, Cloud Security Engineer, Cloud Network Engineer, Machine Learning Engineer
- Specialty: G Suite, Workspace
Compute Services
11. What is Google Compute Engine?
Google Compute Engine (GCE) is an infrastructure-as-a-service (IaaS) offering that provides virtual machines running in Google’s data centers. It offers a wide range of machine types, disks, and networking options for workloads of all sizes.
12. What machine types are available in Compute Engine?
Compute Engine offers several machine series:
- General-purpose (E2, N2, N2D, N1)
- Compute-optimized (C2, C2D)
- Memory-optimized (M2, M1)
- Accelerator-optimized (A2 with GPUs)
- Custom machine types with user-defined CPU and memory
Each series offers multiple machine types with varying vCPU and memory configurations.
13. What are preemptible and spot VMs in GCP?
Preemptible VMs and Spot VMs are significantly discounted Compute Engine instances that can be terminated by Google at any time. Preemptible VMs have a maximum runtime of 24 hours, while Spot VMs can run indefinitely until resources are needed elsewhere. They’re ideal for batch processing jobs, fault-tolerant applications, and workloads that can handle interruptions.
14. What is Google Kubernetes Engine (GKE)?
Google Kubernetes Engine (GKE) is a managed Kubernetes service for deploying, managing, and scaling containerized applications using Google infrastructure. GKE automates the scaling, upgrading, and maintenance of Kubernetes clusters, enabling easier container orchestration.
15. What is Cloud Run?
Cloud Run is a managed compute platform that enables you to run stateless containers directly on top of Google’s scalable infrastructure. It automatically scales up or down from zero to N depending on traffic, so you pay only for the resources you use.
16. What is App Engine?
App Engine is a fully managed, serverless platform for developing and hosting web applications at scale. It provides automatic scaling, high availability, and security while allowing developers to focus on code rather than infrastructure management.
17. How does Cloud Functions work?
Cloud Functions is Google Cloud’s serverless, event-driven compute service. It allows you to run code in response to events like HTTP requests, Cloud Storage changes, Pub/Sub messages, or Firebase events without managing servers. You pay only for the compute time used to run your function.
18. What is Anthos?
Anthos is Google’s modern application management platform that extends GKE capabilities to multiple clouds and on-premises environments. It provides a consistent development and operations experience for hybrid and multi-cloud environments, allowing you to build and manage applications anywhere.
19. How do I choose between GCP’s compute services?
Choose based on your requirements:
- Compute Engine: For maximum control over infrastructure
- GKE: For containerized applications requiring orchestration
- Cloud Run: For containerized applications that scale to zero
- App Engine: For web and mobile applications
- Cloud Functions: For event-driven microservices
- Consult with cloud architecture experts for personalized guidance
20. What are Compute Engine sole-tenant nodes?
Sole-tenant nodes are physical Compute Engine servers dedicated to hosting VM instances only for your specific project. They provide physical isolation from other workloads/tenants and are ideal for workloads with strict compliance requirements, licensing constraints, or performance needs.
Storage and Databases
21. What storage options does GCP offer?
GCP provides several storage services:
- Cloud Storage: Object storage for unstructured data
- Persistent Disk: Block storage for Compute Engine VMs
- Filestore: Managed file storage (NFS)
- Cloud Storage for Firebase: Storage for app developers
- Transfer Service: Large-scale data transfer to GCP
22. What is Google Cloud Storage?
Google Cloud Storage is an object storage service for storing and accessing data on Google Cloud Platform. It offers unlimited storage with high durability (99.999999999%), different storage classes for different needs, and global accessibility.
23. What storage classes are available in Cloud Storage?
Cloud Storage offers four storage classes:
- Standard Storage: Frequently accessed data
- Nearline Storage: Data accessed less than once a month
- Coldline Storage: Data accessed less than once a quarter
- Archive Storage: Data accessed less than once a year
Each class has different pricing for storage, retrieval, and operations.
24. What database services does GCP provide?
GCP offers a range of database services:
- Cloud SQL: Managed MySQL, PostgreSQL, and SQL Server
- Cloud Spanner: Globally distributed relational database
- Firestore: NoSQL document database
- Bigtable: NoSQL wide-column database for large analytical and operational workloads
- Memorystore: In-memory data store service
- Firebase Realtime Database: Real-time NoSQL database for mobile app development
- Cloud Datastore: NoSQL document database
25. What is Cloud SQL?
Cloud SQL is a fully managed relational database service that makes it easy to set up, maintain, manage, and administer your relational databases on Google Cloud Platform. It supports MySQL, PostgreSQL, and SQL Server engines while handling patching, updates, backups, and high availability.
26. What is Cloud Spanner?
Cloud Spanner is a globally distributed, horizontally scalable, and strongly consistent relational database service. It combines the benefits of relational database structure with non-relational horizontal scale, offering up to 99.999% availability, automatic sharding, and synchronous replication.
27. What is Firestore?
Firestore is a flexible, scalable NoSQL cloud database for mobile, web, and server development. It keeps your data in sync across client apps through realtime listeners and offers offline support for mobile and web, helping you build responsive applications regardless of network latency or internet connectivity.
28. What is Cloud Bigtable?
Cloud Bigtable is Google’s fully managed, scalable NoSQL database service for large analytical and operational workloads. It’s the same database that powers many Google services like Search, Analytics, Maps, and Gmail, offering high throughput and low latency for large-scale, single-keyed data.
29. How does GCP handle data backup and recovery?
GCP offers several backup and recovery options:
- Automated and on-demand backups for managed databases
- Snapshot capabilities for Persistent Disks
- Object versioning and retention policies in Cloud Storage
- Cross-region replication for disaster recovery
- Database-specific features like point-in-time recovery
- Backup for GKE for Kubernetes applications
30. What is Memorystore?
Memorystore is Google Cloud’s fully managed in-memory data store service. It offers Redis and Memcached-compatible instances that provide sub-millisecond data access, allowing you to build application caches that provide high performance with minimal management overhead.
Networking
31. What is Google Cloud VPC?
Google Cloud Virtual Private Cloud (VPC) provides networking functionality for your Google Cloud resources, enabling you to provision your Google Cloud resources, connect them to each other, and isolate them from one another in a secure manner. It offers global, scalable, and flexible networking for your cloud-based services.
32. How can I connect my on-premises network to GCP?
You can connect on-premises networks to GCP using:
- Cloud VPN: Secure connection over the public internet
- Cloud Interconnect: Direct physical connection to Google’s network
- Partner Interconnect: Connection through a service provider
- Cloud Router: Dynamic routing between networks using BGP
33. What is Cloud Interconnect?
Cloud Interconnect provides direct physical connections and Layer 3 connectivity between your on-premises network and Google’s network. It comes in two varieties:
- Dedicated Interconnect: Direct connections to Google
- Partner Interconnect: Connections through a service provider
Both provide higher availability and lower latency compared to internet-based connections.
34. What is Cloud CDN?
Cloud CDN (Content Delivery Network) uses Google’s globally distributed edge points of presence to cache content close to users. It accelerates websites and applications by lowering network latency, reducing serving costs, and decreasing the load on your backend systems.
35. How does GCP handle load balancing?
GCP offers several load balancing options:
- Global external application load balancer (HTTP/HTTPS)
- Regional external application load balancer
- Global external proxy network load balancer (TCP/SSL)
- Regional external passthrough network load balancer
- Regional internal application load balancer
- Regional internal passthrough network load balancer
These load balancers distribute traffic across instances in multiple regions, automatically rerouting traffic in case of failures.
36. What is Cloud DNS?
Cloud DNS is a scalable, reliable, and managed authoritative Domain Name System (DNS) service running on the same infrastructure as Google. It translates domain names into IP addresses and offers features like DNSSEC, Cloud IAM for access control, and a 100% uptime SLA.
37. What are VPC firewall rules?
VPC firewall rules allow you to restrict or allow traffic to and from your VM instances based on a configuration you specify. You can define allow or deny rules based on IP addresses, port numbers, protocols, and instance tags or service accounts, helping secure your cloud environment.
38. How can I monitor network traffic in GCP?
GCP offers several tools for network monitoring:
- VPC Flow Logs: For detailed network telemetry
- Network Intelligence Center: For visibility and monitoring
- Cloud Monitoring: For metrics and alerts
- Network Topology: For visualizing network connections
- Performance Dashboard: For network performance insights
- Cloud monitoring services for comprehensive network visibility
39. What is Identity-Aware Proxy (IAP)?
Identity-Aware Proxy (IAP) controls access to cloud applications and VMs running on Google Cloud. It verifies user identity and context to determine if a user should be granted access to a protected resource, eliminating the need for a VPN to secure your applications.
40. What is Cloud NAT?
Cloud NAT (Network Address Translation) is a managed service that lets instances without external IP addresses access the internet. It provides source network address translation for VMs, allowing outbound connections to the internet while preventing inbound connections from the internet.
Security and Compliance
41. How does GCP approach security?
Google Cloud follows a shared responsibility model where Google secures the underlying cloud infrastructure while customers are responsible for securing their data, applications, and access management. GCP provides a suite of security tools, encryption options, identity management, network security, and compliance certifications.
42. What is Cloud Identity and Access Management (IAM)?
Cloud IAM is GCP’s unified system for managing access to resources. It provides fine-grained access control and visibility for centrally managing resources through a “who can do what on which resource” model. IAM enables you to implement the principle of least privilege and segregation of duties.
43. What is Google Cloud Armor?
Google Cloud Armor is Google’s DDoS protection and web application firewall (WAF) service. It protects your applications and websites from denial-of-service and web attacks, offering pre-configured rules to protect against common vulnerabilities like SQL injection and cross-site scripting.
44. How does GCP handle encryption?
GCP provides encryption at multiple levels:
- Data at rest: Automatic encryption for all storage services
- Data in transit: TLS encryption between clients and Google
- Cloud KMS: For managing encryption keys
- Customer-managed encryption keys (CMEK)
- Customer-supplied encryption keys (CSEK)
- Confidential Computing for encrypting data in use
45. What compliance certifications does GCP have?
Google Cloud maintains a comprehensive compliance portfolio including:
- ISO 27001, 27017, 27018
- SOC 1, SOC 2, SOC 3
- PCI DSS
- HIPAA
- FedRAMP
- GDPR
- And 40+ other regional and industry-specific certifications
46. What is Cloud Key Management Service (KMS)?
Cloud KMS is a cloud-hosted key management service that allows you to manage cryptographic keys for your cloud services. It integrates with IAM and Cloud Audit Logs so you can manage permissions on keys and track how they are used. It supports symmetric and asymmetric keys.
47. How does GCP help with regulatory compliance?
GCP helps with regulatory compliance through:
- Comprehensive compliance certifications
- Assured Workloads for sensitive workloads
- Security Command Center for compliance monitoring
- Data residency options
- Access Transparency and Access Approval
- Detailed compliance documentation
- Shared fate model with customers
48. What is VPC Service Controls?
VPC Service Controls helps mitigate data exfiltration risks by creating security perimeters around Google Cloud resources such as Cloud Storage buckets, Bigtable instances, and BigQuery datasets. These perimeters prevent data from being moved outside of a defined network boundary.
49. What is Security Command Center?
Security Command Center is Google Cloud’s security and risk management platform. It provides security and data risk insights to help identify vulnerabilities and threats across your GCP resources, including misconfigurations, vulnerabilities, and threats to your environment.
50. What security best practices should I follow in GCP?
Key security best practices include:
- Implement least privilege with IAM
- Enable MFA for all users
- Use organization policy constraints
- Configure VPC Service Controls for sensitive data
- Enable audit logging and monitoring
- Implement network security controls
- Use secure default configurations
- Regularly update and patch systems
- Encrypt sensitive data
- Conduct regular security assessments with security experts
Big Data and Analytics
51. What big data services does GCP offer?
GCP provides a comprehensive suite of big data services:
- BigQuery: Serverless data warehouse
- Dataflow: Stream and batch data processing
- Dataproc: Managed Hadoop and Spark service
- Pub/Sub: Messaging and ingestion for event-driven systems
- Data Fusion: Fully managed data integration service
- Dataprep: Data preparation service
- Composer: Managed Apache Airflow service for workflows
52. What is BigQuery?
BigQuery is Google’s fully managed, serverless data warehouse that enables super-fast SQL queries using the processing power of Google’s infrastructure. It allows you to analyze terabytes to petabytes of data without managing infrastructure or database administration, with built-in machine learning capabilities.
53. What is Dataflow?
Dataflow is a fully managed service for transforming and enriching data in stream (real-time) and batch modes. It’s based on Apache Beam and provides a simplified pipeline development experience, freeing you from operational tasks like resource management and performance optimization.
54. What is Dataproc?
Dataproc is a managed Apache Hadoop and Apache Spark service that lets you take advantage of open source data tools for batch processing, querying, streaming, and machine learning. It automates cluster creation, scaling, and deletion, reducing the overhead of managing the infrastructure.
55. What is Pub/Sub?
Pub/Sub is an asynchronous messaging service that decouples services that produce events from services that process events. It provides “at least once” delivery with no provisioning required and automatic scaling, making it ideal for event ingestion and delivery in real-time analytics pipelines.
56. What is Data Fusion?
Data Fusion is a fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT data pipelines. It provides a graphical interface to build scalable data integration solutions without having to write code, simplifying the development process.
57. What is Dataprep?
Dataprep is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis, reporting, and machine learning. It’s serverless and works at any scale without infrastructure management.
58. How does BigQuery compare to traditional data warehouses?
Compared to traditional data warehouses, BigQuery:
- Is serverless with no infrastructure to manage
- Separates storage and compute for independent scaling
- Offers pay-per-query pricing model
- Provides automatic high availability and disaster recovery
- Scales to petabytes without performance tuning
- Includes built-in ML capabilities
- Requires no indexing or partitioning for performance (though these options exist)
59. What is Looker and Looker Studio?
Looker is Google Cloud’s enterprise business intelligence platform that helps you explore, share, and visualize data. Looker Studio (formerly Data Studio) is Google’s free data visualization tool for creating interactive dashboards and reports. Together, they form Google Cloud’s comprehensive analytics and BI solution.
60. How can I build real-time data analytics pipelines in GCP?
To build real-time analytics pipelines in GCP, you can use:
- Pub/Sub for ingesting streaming data
- Dataflow for processing streams in real time
- BigQuery for analyzing streaming data
- Bigtable for high-throughput, low-latency storage
- Looker or Looker Studio for visualization
- Data analytics experts can help design optimal pipelines
AI and Machine Learning
61. What AI and machine learning services does GCP offer?
GCP provides a wide range of AI and ML services:
- Vertex AI: Unified ML platform
- AutoML: Automated machine learning for various data types
- Vision AI: Image analysis and recognition
- Natural Language API: Text analysis and understanding
- Translation & Speech: Language and speech services
- Document AI: Document processing and understanding
- Contact Center AI: Virtual agent and conversation analytics
62. What is Vertex AI?
Vertex AI is Google Cloud’s unified platform for building, deploying, and scaling ML models. It brings AutoML and custom ML together into a unified API, client libraries, and user interface. Vertex AI requires nearly 80% fewer lines of code to train a model compared to competitive platforms.
63. What is AutoML?
AutoML is a suite of machine learning products that enables developers with limited ML expertise to train high-quality models specific to their needs. It automates the process of selecting machine learning models, hyperparameter tuning, and deploying models, making ML accessible to more organizations.
64. What is Vision AI?
Vision AI is a set of pre-trained vision models that allow you to detect objects, understand text, and analyze images. It includes pre-built APIs for common use cases as well as AutoML Vision for custom image recognition models.
65. What natural language processing capabilities does GCP provide?
GCP’s natural language capabilities include:
- Natural Language API: For sentiment analysis, entity recognition, and syntax analysis
- AutoML Natural Language: For custom text classification and entity extraction
- Document AI: For document parsing and understanding
- Speech-to-Text and Text-to-Speech: For voice applications
- Translation: For real-time language translation
66. How does Google’s TensorFlow relate to GCP?
TensorFlow is an open-source machine learning framework created by Google. While it can be used anywhere, GCP provides optimized infrastructure for running TensorFlow workloads, including specialized hardware like TPUs (Tensor Processing Units) and integration with services like Vertex AI.
67. What are Cloud TPUs?
Cloud TPUs (Tensor Processing Units) are Google’s custom-developed application-specific integrated circuits (ASICs) used to accelerate machine learning workloads. They’re designed specifically to accelerate TensorFlow operations and provide significantly faster training and inference for ML models compared to CPUs and GPUs.
68. What is Document AI?
Document AI is a document understanding platform that uses machine learning to extract structured data from unstructured documents. It can process documents like invoices, receipts, tax forms, and contracts, helping automate document-based workflows.
69. How can I deploy ML models in GCP?
You can deploy ML models in GCP through:
- Vertex AI: For managed model deployment and serving
- Cloud Run: For containerized model serving
- GKE: For custom deployment environments
- Cloud Functions: For lightweight inference
- AI Platform Prediction (legacy): For model serving
- BigQuery ML: For in-database predictions
70. What is Responsible AI in Google Cloud?
Responsible AI in Google Cloud refers to Google’s commitment to developing AI systems and practices that are fair, interpretable, privacy-preserving, and secure. Google provides tools for explainable AI, fairness indicators, and AI principles guidance, allowing organizations to build ethical AI systems.
DevOps and Development
71. What DevOps tools does GCP provide?
GCP offers a comprehensive suite of DevOps tools:
- Cloud Build: Continuous integration and delivery platform
- Cloud Deploy: Continuous delivery to GKE
- Container Registry/Artifact Registry: For storing container images
- Cloud Source Repositories: Git repositories
- Cloud Monitoring and Cloud Logging: For observability
- Cloud Trace and Cloud Profiler: For performance analysis
- Cloud Debugger: For debugging production code
72. What is Cloud Build?
Cloud Build is a service that executes your builds on Google Cloud infrastructure. It can import source code from Google Cloud Storage, Cloud Source Repositories, GitHub, or Bitbucket, execute a build according to your specifications, and produce artifacts such as Docker containers or Java archives.
73. What is Artifact Registry?
Artifact Registry is a universal package manager for all your build artifacts and dependencies. It supports multiple formats (Docker, Maven, npm, Python packages) and integrates with Google Cloud’s build systems, providing a single place to manage artifacts.
74. What is Infrastructure as Code (IaC) in GCP?
Infrastructure as Code in GCP involves managing and provisioning infrastructure through code rather than manual processes. GCP supports multiple IaC approaches:
- Terraform with Google provider
- Google Cloud Deployment Manager
- Pulumi with GCP provider
- Configuration management tools (Ansible, Chef, Puppet)
75. What is Cloud Deployment Manager?
Cloud Deployment Manager is Google Cloud’s infrastructure deployment service that automates the creation and management of Google Cloud resources. It uses declarative YAML or Python templates to describe your environment, enabling reproducible deployments.
76. How can I implement CI/CD pipelines in GCP?
To implement CI/CD pipelines in GCP:
- Use Cloud Source Repositories or integrate with GitHub/Bitbucket
- Set up Cloud Build triggers for continuous integration
- Store artifacts in Artifact Registry
- Deploy to various targets (App Engine, GKE, Cloud Run) using Cloud Deploy
- Implement testing in your pipeline
- Use Infrastructure as Code for environment consistency
- Monitor with Cloud Monitoring and Cloud Logging
77. What is Cloud Monitoring?
Cloud Monitoring provides visibility into the performance, uptime, and overall health of cloud-powered applications. It collects metrics, events, and metadata from Google Cloud, hosted uptime probes, application instrumentation, and various common application components.
78. What is Cloud Logging?
Cloud Logging is a fully managed service that performs at scale and can ingest application and system log data from Google Cloud and AWS. It allows you to store, search, analyze, monitor, and alert on log data and events from Google Cloud and other sources.
79. What development languages and frameworks does GCP support?
GCP supports a wide range of languages and frameworks including:
- Python, Java, Go, Node.js, PHP, Ruby, .NET
- Web frameworks like Django, Flask, Spring, Express, Rails
- Mobile app development with Firebase
- Container orchestration with Kubernetes
- Serverless with Cloud Functions and Cloud Run
- Data processing frameworks like Apache Beam, Spark, and Hadoop
80. What is Cloud Code?
Cloud Code is a set of IDE plugins that helps developers write, run, and debug cloud-native applications quickly and easily. It provides extensions for popular IDEs like Visual Studio Code and IntelliJ, offering tools for developing applications that run on Google Cloud.
Serverless and Microservices
81. What serverless options does GCP offer?
GCP provides several serverless computing options:
- Cloud Functions: Event-driven compute service
- Cloud Run: Container-based serverless platform
- App Engine: Platform-as-a-Service for applications
- BigQuery: Serverless data warehouse
- Firestore: Serverless document database
- Workflows: Serverless orchestration of services
82. How do Cloud Functions, Cloud Run, and App Engine differ?
- Cloud Functions: Event-driven, single-purpose functions with automatic scaling to zero; suitable for small, independent pieces of logic
- Cloud Run: Runs containers that can be built with any language/framework; more flexible than Functions but still scales to zero
- App Engine: Full application platform with standard and flexible environments; designed for complete applications with less granular scaling
83. What event sources can trigger Cloud Functions?
Cloud Functions can be triggered by:
- HTTP requests
- Cloud Storage events (object creation, deletion, etc.)
- Pub/Sub messages
- Firestore document changes
- Firebase events (Auth, Realtime Database, etc.)
- Cloud Scheduler (time-based)
- Log sinks
- Various third-party services via webhooks
84. What is Cloud Workflows?
Cloud Workflows is a fully managed service that allows you to orchestrate and automate Google Cloud and HTTP-based API services. It enables you to create serverless workflows that link a series of tasks together in an order you define, without using a separate compute service.
85. What is API Gateway?
API Gateway is a fully managed service that enables you to create, secure, and monitor APIs for Google Cloud serverless backends like Cloud Functions, Cloud Run, App Engine, and GKE. It provides an API console, authentication, monitoring, quotas, and other features for managing APIs.
86. How can I implement microservices architecture in GCP?
To implement microservices in GCP:
- Use GKE for container orchestration
- Deploy containerized microservices on Cloud Run
- Implement serverless microservices with Cloud Functions
- Use Pub/Sub or Eventarc for event-driven communication
- Manage APIs with API Gateway or Apigee
- Implement service mesh with Istio on GKE
- Consult with microservices architecture experts for optimal design
87. What is Eventarc?
Eventarc is a service that enables you to build event-driven architectures by asynchronously delivering events from Google services, SaaS, and your own apps. It routes events from various sources to different destinations while managing delivery, security, authorization, and observability.
88. How does GCP support event-driven architectures?
GCP supports event-driven architectures through:
- Pub/Sub for reliable messaging
- Eventarc for event delivery
- Cloud Functions for event handling
- Cloud Run for container-based event processing
- Cloud Scheduler for time-based events
- Workflows for orchestrating event-driven processes
- Various triggers and connectors for different event sources
89. What is Cloud Tasks?
Cloud Tasks is a fully managed service that allows you to manage the execution, dispatch, and delivery of a large number of distributed tasks. You can schedule tasks to run at specific times or rates, retry tasks on failure, and distribute task execution across multiple regions.
90. How can I manage API lifecycle in GCP?
For API lifecycle management, GCP offers:
- Apigee: Full API management platform
- API Gateway: Lightweight API management
- Cloud Endpoints: API management for backend services
- Service Infrastructure: Google-scale API management
These solutions help with API creation, security, monitoring, analytics, and developer onboarding.
Migration and Hybrid Cloud
91. What tools does GCP provide for cloud migration?
GCP offers several migration tools:
- Migrate for Compute Engine: For VM migration
- Database Migration Service: For database migrations
- Transfer Service: For large-scale data transfer
- Storage Transfer Service: For online data transfer
- Transfer Appliance: For offline data transfer
- BigQuery Data Transfer Service: For analytics data
- Cloud migration services for complex migrations
92. What is Google Cloud’s Database Migration Service?
Database Migration Service is a serverless, easy-to-use migration tool that helps you migrate MySQL, PostgreSQL, SQL Server, and Oracle databases to Google Cloud with minimal downtime. It supports both one-time migrations and continuous replication.
93. What is Migrate for Compute Engine?
Migrate for Compute Engine (formerly Velostrata) is a service that helps you migrate VM-based workloads from on-premises or other clouds to Google Compute Engine. It automates the migration process, including testing, adaptations for Google Cloud, and cutover, reducing risk and downtime.
94. What is Anthos for hybrid and multi-cloud deployments?
Anthos is Google’s modern application management platform that extends GKE’s capabilities to multiple clouds and on-premises environments. It provides a consistent platform for deploying and managing applications across hybrid and multi-cloud environments, with centralized policy and security control.
95. How can I implement a hybrid cloud strategy with GCP?
To implement a hybrid cloud strategy with GCP:
- Connect on-premises and cloud environments using Cloud VPN or Cloud Interconnect
- Use Anthos for consistent Kubernetes experience across environments
- Implement hybrid storage solutions with Cloud Storage or Filestore
- Extend your identity management with Cloud Identity
- Use Google Cloud’s operations suite for monitoring across environments
- Deploy databases that span environments
Specialized Services
96. What IoT services does GCP offer?
GCP’s IoT offerings include:
- Cloud IoT Core: Fully managed service for connecting and managing IoT devices
- Pub/Sub: For ingesting device telemetry data
- Dataflow: For processing IoT data streams
- BigQuery: For analyzing IoT data
- Looker: For visualizing insights
- Edge TPU: For running ML inference on edge devices
97. What media services does GCP provide?
GCP’s media and entertainment services include:
- Transcoder API: For file-based video transcoding
- Video Intelligence API: For video content analysis
- Live Stream API: For live video processing
- Media CDN: For content delivery
- Speech-to-Text and Text-to-Speech: For audio processing
- Vision AI: For image and video analysis
98. What gaming-focused services does GCP offer?
GCP provides gaming infrastructure and services:
- Game Servers: Managed service for orchestrating game server deployments
- Open Match: Open-source matchmaking framework
- Global network infrastructure for low-latency gaming
- Firebase for game backends
- BigQuery for game analytics
- Spanner for global player databases
- AutoML Vision for game moderation
99. What healthcare-specific services does GCP offer?
For healthcare, GCP provides:
- Cloud Healthcare API: For healthcare data integration
- Healthcare Natural Language API: For medical text processing
- HIPAA-compliant infrastructure and services
- Medical imaging solutions with AutoML Vision
- Healthcare interoperability solutions
- AI-powered healthcare insights
100. What sustainability initiatives does Google Cloud have?
Google Cloud’s sustainability initiatives include:
- Carbon-free energy for cloud regions by 2030
- Already carbon-neutral cloud operations
- Carbon footprint dashboard for customers
- Region picker showing lowest carbon regions
- Active assistance in helping customers reduce their carbon footprint
- Sustainability commitments and transparency reporting
- Cloud sustainability advisory services for carbon reduction
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