Google Cloud Platform

What is Google Cloud Platform?

Google Cloud Platform is a suite of cloud computing services provided by Google that runs on the same infrastructure that Google uses internally for its products, such as Google Search, Gmail, and YouTube. It offers a comprehensive range of services, including computing, storage, databases, networking, and machine learning, enabling businesses to build, deploy, and scale applications efficiently.

Key Features of GCP

GCP provides an array of powerful tools and services that cater to various needs, including:

1. Storage Solutions

• Cloud Storage: A globally scalable and secure object storage solution.

• Persistent Disk: High-performance block storage for virtual machines.

2. Compute Power

• Compute Engine: Provides scalable and flexible virtual machines.

• Cloud Functions: Enables server-less computing for event-driven applications.

• Kubernetes Engine: A managed environment for deploying, managing, and scaling containerized applications using Kubernetes.

3. Database Services

• Cloud SQL: A fully managed relational database service supporting MySQL, PostgreSQL, and SQL Server.

• Cloud Firestore: A NoSQL document database for mobile, web, and server development.

4. Machine Learning and AI

• Vertex AI: A unified platform for building and deploying ML models.

• TensorFlow Enterprise: Optimized for large-scale ML workloads with enterprise support.

5. Big Data and Analytics

• BigQuery: A powerful data warehouse that allows businesses to run fast queries on massive datasets.

• Dataflow: A server-less data processing tool for streaming and batch data processing.

Why GCP?

GCP stands out due to its commitment to security, reliability, and open-source innovation. Some key benefits include:

• Scalability: GCP allows businesses to scale their applications seamlessly with demand.

• Security: Google employs advanced security measures, including encryption and AI-driven threat detection.

• Open-Source and Hybrid Cloud Support: GCP integrates with popular open-source tools and supports multi-cloud and hybrid environments.

• Cost Efficiency: Pay-as-you-go pricing and sustained-use discounts help businesses optimize costs.

Google Cloud Platform provides a robust and future-ready cloud ecosystem for businesses of all sizes. Whether you’re a startup looking for cost-effective hosting or an enterprise in need of powerful AI and analytics capabilities, GCP offers the tools and infrastructure to drive innovation and efficiency.

Google Cloud Storage and Database Portfolio

STORAGE/DATABASE TYPE	GOOGLE CLOUD SERVICE	USE CASE EXAMPLES
Object	Cloud Storage A managed service for storing unstructured data. Store any amount of data and retrieve it as often as you like.	Websites Streaming videos Mobile apps
Relational	AlloyDB for PostgreSQL The PostgreSQL-compatible database.	Heterogenous migrations Legacy applications Enterprise workloads Hybrid cloud, multicloud, and edge
Relational	Cloud SQL Fully managed MySQL, PostgreSQL, and SQL Server.	CRM ERP Ecommerce and web SaaS application
Relational	Spanner Cloud-native with unlimited scale, global consistency, and up to 99.999% availability. Processes more than three billion requests per second at peak.	Gaming Retail Global financial ledger Supply chain/inventory management
Relational	Bare Metal Solution for Oracle Lift and shift Oracle workloads to Google Cloud.	Legacy applications Data center retirement
Relational	BigQuery Serverless, highly scalable, and cost-effective multicloud data warehouse designed for business agility and offers up to 99.99% availability. Enable near real-time insights on operational data with Datastream for BigQuery.	Multicloud analytics Real-time processing Built-in machine learning
Key-value	Bigtable Highly performant, fully managed NoSQL database service for large analytical and operational workloads. Offers up to 99.999% availability. Processes more than 7 billion requests per second at peak, and with more than 10 Exabytes of data under management. Learn how to migrate from HBase or Cassandra.	Personalization Adtech Recommendation engines Fraud detection
Document	Firestore Highly-scalable, massively popular document database service for mobile, web, and server development that offers richer, faster queries and high availability up to 99.999%. Has a thriving developer community of more than 250,000 monthly active developers.	Mobile/web/IoT applications Real-time sync Offline sync
Document	Firebase Realtime Database Store and sync data in real time.	Mobile sign-ins Personalized applications and ads In-app chat
In-memory	Memorystore Fully managed Redis and Memcached for sub-millisecond data access. Memorystore for Redis Cluster is a fully managed service that can easily scale to terabytes of keyspace and tens of millions of operations per second.	Caching Gaming Leaderboard Social chat or news feed
Additional NoSQL	MongoDB Atlas Global cloud database service for modern applications.	Mobile/web/IoT applications Gaming Content management Single view

Credit: https://www.linkedin.com/pulse/storage-options-google-coud-platform-cloud-ai-analytics/

GCP Compute Services

Google Cloud Platform (GCP) offers a suite of compute services designed to handle a wide range of workloads, from virtual machines to containerized applications and serverless computing. These services provide businesses with scalable, high-performance, and cost-efficient infrastructure to support their applications and development needs.

Key Compute Services in GCP

1. Compute Engine – A powerful Infrastructure-as-a-Service (IaaS) solution that provides scalable virtual machines (VMs) with customizable configurations, pre-configured machine images, and automatic scaling. It supports GPUs and TPUs for high-performance computing needs.

2. App Engine – A Platform-as-a-Service (PaaS) solution that allows developers to build and deploy applications quickly without worrying about infrastructure. It supports multiple programming languages and automatic scaling.

3. Cloud Functions – A serverless execution environment that allows developers to run event-driven functions without managing infrastructure. It is ideal for microservices, real-time processing, and automation tasks.

   • Sicroservices: A microservice is a small, independent service that performs a specific function and communicates via APIs.

4. Google Kubernetes Engine (GKE) – A fully managed Kubernetes, an open-source software for container orchestration, environment that simplifies the deployment, management, and scaling of containerized applications. GKE integrates with other GCP services, offering automated updates, security, and monitoring.

   • Containers: A package of an application and its dependencies, including libraries, code, data, and allows the app to run consistently across different computing environments.

5. Cloud Run – A fully managed platform that enables developers to deploy and run containerized applications with automatic scaling, eliminating the need for server management.

Server-based	Serverless	Containerized
Compute Engine - Customizable virtual machines	App Engine - Scalable and efficient app-development	Google Kubernetes Engine (GKE)
	Cloud Functions - Event-driven computation	Cloud Run

Analytics with GCP

Services mostly used for Analytics are:

• BigQuery

  • Fully managed server-less warehouse

  • Optimized for complex analytics

  • Scales up automatically

• Looker

  • Business Intelligence platform

  • Interactive visualizations and real-time analytics

  • Dashboards with BigQuery

• Data lakes: Centralized store for structured, semi-structured, and unstructured data :

  • Offer high flexibility

    • Central repository for diverse data types

  • Handle petabytes from sources like social media

  • Enable big data analytics and machine learning

  • GCP Data Lake service: scalable, cost- effective solution for data from various sources

  • GCP BigLake: integrates BigQuery to data lakes

AI and Machine Learning with GCP

Google Cloud Platform (GCP) offers a range of AI and machine learning services designed to help businesses build, train, and deploy ML models efficiently. Here are the key services:

Service	Description	Link
Vertex AI	Unified platform for building, training, and deploying ML models.	https://cloud.google.com/vertex-ai/
TensorFlow Enterprise	Optimized version of TensorFlow with enterprise-grade support.	https://cloud.google.com/tensorflow-enterprise/
AI Platform	Tools for developing, training, and managing ML models in the cloud.	https://cloud.google.com/ai-platform/
Cloud AutoML	No-code/low-code ML solution for training custom models.	https://cloud.google.com/automl/
BigQuery ML	Enables ML model training and deployment using SQL within BigQuery.	https://cloud.google.com/bigquery-ml/
Vision AI	Pre-trained and custom models for image and video analysis.	https://cloud.google.com/vision/
Video AI	Analyzes video content with object detection, label detection, and more.	https://cloud.google.com/video-intelligence/
Natural Language AI	Tools for sentiment analysis, entity recognition, and text processing.	https://cloud.google.com/natural-language/
Speech-to-Text	Converts spoken audio into written text.	https://cloud.google.com/speech-to-text/
Text-to-Speech	Synthesizes natural-sounding speech from text.	https://cloud.google.com/text-to-speech/
Translation AI	Neural machine translation for multilingual applications.	https://cloud.google.com/translate/
Dialogflow	Conversational AI for building chatbots and virtual assistants.	https://cloud.google.com/dialogflow/
Recommendation AI	AI-powered recommendations for personalized user experiences.	https://cloud.google.com/recommendations-ai/
Document AI	Extracts, classifies, and processes structured data from documents.	https://cloud.google.com/document-ai/