Google Cloud Platform All-In-One Guide: Get Familiar with a Portfolio of Cloud-based Services in GCP
- Length: 260 pages
- Edition: 1
- Language: English
- Publisher: BPB Publications
- Publication Date: 2023-01-16
- ISBN-10: 9355513321
- ISBN-13: 9789355513328
- Sales Rank: #0 (See Top 100 Books)
Explore the Essential Concepts, Tools, and Services in GCP
Key Features
- Build a solid foundation of the Google Cloud Platform.
- Work with different AI and Machine Learning services offered by Google Cloud.
- Learn how to use Google cloud services to build scalable apps.
Description
Google Cloud platform has a suite of cloud computing services for developing and maintaining software. It includes products like Google Compute Engine, Google App Engine, Google Cloud Storage, and Google Container Engine. With so much to offer, we will learn how to manage services running on Google Cloud.
‘Google Cloud Platform All-In-One Guide’ is primarily for everyone who wants to get familiar with the comprehensive list of services in GCP. You will work with various cloud-based services in computing, storage, database, and networking domains. You will understand how Big Data services can be used for developing end-to-end ETL/ELT pipelines. Lastly, you will explore various APIs available in Google cloud. The book ends with a chapter on best practices that will help you maximize resource utilization and cost optimization.
By the end of the book, you will be able to design, develop, and deploy apps in GCP.
What you will learn
- Explore and work with security and monitoring services in Google Cloud.
- Learn how to build an ETL Pipeline in the Google Cloud Platform.
- Build and deploy code-based custom models using Vertex AI and Jupyter notebook.
- Learn how to create workflows using GCP services.
- Get an overview of best practices for securely deploying your workloads on Google Cloud.
Who this book is for
This book is for everyone new to cloud computing or Google cloud. Cloud professionals who are looking to migrate their services to the Google cloud platform will find this book helpful.
Cover Page Title Page Copyright Page Dedication Page About the Author About the Reviewer Acknowledgement Preface Errata Table of Contents 1. Cloud Computing Fundamentals Introduction Structure Objectives What is cloud computing? Various service models in cloud computing Cloud models comparison Various deployment models in cloud computing Major cloud service providers in the industry OPEX versus CAPEX models Benefits of cloud computing Risks associated with cloud computing Introduction to Google Cloud Platform Google Cloud Project Different ways of accessing Google cloud platform Conclusion Key terms Questions Further reading 2. Compute in Google Cloud Introduction Structure Objectives Google Cloud Compute Engine Predefined machine types Custom machine types Google compute engine provisioning models Introduction to Kubernetes cluster Microservices Container POD Kubernetes cluster Master Node Worker Node Google Kubernetes Engine Modes in Google Kubernetes Engine: Difference between single zone, multi-zone, and regional cluster Cloud Run Google App Engine Types of App Engine environment App Engine standard environment App Engine flexible environment Cloud Functions Cost comparison between various compute options Choosing the correct compute option in GCP Lab exercises Creating an account in the Google Cloud Platform Creating a Compute Instance Creating a Standard Google Kubernetes Engine (GKE) Conclusion Key terms Questions Further reading 3. Storage in Google Cloud Introduction Structure Objectives Storage and its types Various storage options in Google Cloud Storage encryption in Google Cloud Choosing the right storage option Lab exercise Creating a Google Cloud Storage Bucket Conclusion Key terms Questions Further reading 4. Database Services in Google Cloud Introduction Structure Objectives Cloud SQL Features Cloud Spanner Cloud Bigtable Cloud Firestore Cloud Memorystore BigQuery Features Comparison between various database services Lab exercise Creating Cloud SQL MySQL instance and connecting it with a virtual machine Testing the connectivity between the VM instance and Cloud SQL instance Conclusion Key terms Questions Further reading 5. Networking in Google Cloud Introduction Structure Objectives Google’s global network Organization, projects, folders, and resources Virtual Private Cloud Connectivity options in VPC Shared VPC VPC Peering GCP Interconnect Dedicated Interconnect Partner Interconnect Connecting to Google Workspace and Google APIs Direct Peering Carrier Peering VPC creation best practices Cloud NAT Cloud Load Balancing Global load balancer HTTP/HTTPS load balancer SSL proxy load balancer TCP proxy load balancer Regional load balancer Internal TCP/UDP Load balancer Network load balancer Internal HTTPS load balancer Instance groups Managed instance group Unmanaged Instance Group GKE Ingress Controller Container native load balancing Hybrid cloud concepts Cloud CDN and edge locations Conclusion Key terms Questions Further reading 6. Security and Monitoring Services in Google Cloud Introduction Structure Objectives IAM roles, permissions, and policies Member Roles and permissions Primitive or basic roles Pre-defined roles Custom roles IAM policy Service account User-managed service accounts Google-managed service accounts Container security Cloud DNS Cloud DNS forwarding DNS Peering DNS Security Extension (DNSSEC) Cloud Armor Features Secret Manager Features Key management service (KMS) DevOps concepts Benefits of DevOps Some activities under DevOps practice Security in DevOps Implementing DevSecOps Google Cloud operations suite Cloud Logging Platform logs User-written logs Security logs Audit logs Access transparency logs Cloud Monitoring Application performance management (APM) Security-best practices Conclusion Key terms Questions Further reading 7. Big Data in Google Cloud Introduction Structure Objectives Big data Structured versus unstructured data Streaming data versus batch data Data processing tools ETL/ELT concepts Cloud Pub/Sub Important concepts in Cloud Pub/Sub Important use cases in Pub/Sub Dataflow Important features of Cloud Dataflow Dataproc Benefits of Cloud Dataproc Important features of Cloud Dataproc Cloud data fusion Important features of Cloud Data Fusion Benefits of using Cloud Data Fusion Important plug-ins used in Data Fusion Data analytics Data Warehouse OLAP versus OLTP BigQuery BigQuery architecture Storage management in BigQuery Partitioning and clustering in BigQuery Data visualization tools in GCP Looker Studio Google Cloud Cortex Framework Reference architecture showing Streaming and Batch data coming from different sources and utilizing various data services in GCP Conclusion Key terms Questions Further readings 8. AI/ML in Google Cloud Introduction Structure Objectives What is machine learning? Machine Learning approaches Supervised Machine Learning Unsupervised Machine Learning Reinforcement Machine Learning Machine Learning in Google Cloud Custom models in GCP Pre-trained models in GCP Various AI tools and services in Google Cloud Vertex AI AutoML Natural language API Speech-To-Text API Text-To-Speech API Dialogflow Translation AI Cloud Vision API Neural Network Types of neural networks TensorFlow Deploying and training ML model in GCP Conclusion Key terms Questions Further reading 9. Orchestration Services in GCP Introduction Structure Objectives Cloud Scheduler Features Workflows Features Cloud Composer Features Selecting the right orchestration service in GCP Use cases Cloud Scheduler use cases Workflows use cases Cloud Composer use cases Conclusion Key terms Questions Further readings 10. Migration Services in GCP Introduction Structure Objectives Migration concepts Discovery Assessment and planning Migration Testing, documentation, and knowledge transfer StratoZone StratoProbe StratoZone portal Migrate to Virtual Machine(V5.0) Pre-requisite for performing migration using migrate to the virtual machine Various phases in the migration lifecycle Transfer Appliance Use cases Storage Transfer Service Features of Storage Transfer Service Database Migration Service Features of Database Migration Service Elements in Database Migration Service Use cases BigQuery Data Transfer Service Elements in BigQuery Data Transfer Service Use cases Lab exercises Migrating MySQL database instance to cloud SQL using database migration service Conclusion Key terms Questions Further readings 11. Best Practices Introduction Structure Objectives Landing Zone—best practices Best practices Infrastructure provisioning—best practices Cloud IAM—best practices DevOps and automation –best practices Migration—best practices Conclusion Questions Further readings 12. Bonus Chapter Introduction Structure Objectives Google Cloud VMware Engine Features Oracle—Bare Metal Solution Features Anthos Anthos components Anthos features Google Distributed Cloud Edge Introduction to Edge Computing Distributed Cloud Edge Google Cloud Backup and DR Key features Conclusion Key terms Questions Further readings 13. Use Cases Introduction Structure Objectives Ecommerce website deployment—XYZ limited Problem statement Solution considerations GCP services to be used Deployment approach Data transformation—ABC Energy Problem statement Data sources Solution considerations GCP services to be used Deployment approach Landing Zone—AlphaBeta Limited Problem statement Solution considerations Landing Zone modules Deployment approach Conclusion Further readings Index
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