Google Cloud Platform

Google Cloud Platform




Google, a leader in AI and data analytics, is on a massive AI acquisition binge, having acquired myriad AI startups in the last several years. Google is deeply invested in furthering artificial intelligence capabilities. In addition to using AI to improve its services, Google Cloud sells a number of AI and machine learning services to business. It has an industry-leading software project in TensorFlow as well as its own Tensor AI chip project.

Google Cloud Platform Services

Google Cloud Platform's portfolio of cloud services isn't as extensive as Amazon's or Microsoft Azure's, but it offers some specialized tools for developers that are hard to find elsewhere. It organizes its cloud services into the following nine categories:

 

Compute — includes Google's original cloud service, the App Engine PaaS, as well as Compute Engine, Container Engine, Container Registry and the Cloud Functions serverless computing offering

Storage and Database — includes Cloud Storage object storage, Cloud SQL with MySQL or PostgreSQL database options, Cloud Bigtable NoSQL database, Cloud Spanner relational database, Cloud Datastore NoSQL database and Persistent Disk block storage

Networking — includes Virtual Private Cloud (VPC), Cloud Load Balancing, Cloud CDN content delivery, Cloud Interconnect for enterprise-grade connections to Google's Cloud and Cloud DNS for Web domain serving

Big Data — includes the BigQuery large-scale data warehouse, Cloud Dataflow for batch and stream data processing, Cloud DataProc with Spark and Hadoop capabilities, Cloud Datalab for analytics and visualizations, Cloud Dataprep for data preparation, Cloud Pub/Sub messaging, Genomics for genetic scientists and Google Data Studio for business reporting

Internet of Things — includes Google's Cloud IoT Core for secure device connection and management

Machine Learning — includes Google's Cloud Machine Learning Engine, as well as its APIs for job search, natural language, speech, translation, vision and video intelligence

Identity and Security — includes Cloud IAM identity and access management, Cloud Identity-Aware Proxy, Cloud Data Loss Prevention API, Security Key Enforcement, Cloud Key Management Service, Cloud Resource Manager and the Cloud Security Scanner

Management Tools — includes Stackdriver Overview, Monitoring and Logging, all of which support both Google Cloud Platform and AWS. This category also includes app optimization and deployment tools like Trace, Debugger, Cloud Deployment Manager, Cloud Endpoints, Cloud Console, Cloud Shell, Cloud Mobile App, Cloud Billing API and other Cloud APIs

Developer Tools — Includes the Cloud SDK with its command line interface for Google Cloud Platform services, container tools, Cloud Source Repositories, Cloud Tools for Android Studio, Cloud Tools for IntelliJ, Cloud Tools for Powershell, Cloud Tools for Visual Studio, Cloud Tools for Eclipse, Gradle App Engine Plugin, Maven App Engine Plugin and the Cloud Test Lab for On-Demand Testing

Google boasts that its cloud services have customer-friendly pricing, and it claims that its prices are "on average 60% less for many compute workloads compared to other cloud providers." The chart below, while far from exhaustive, offers an overview of the pricing and features for some of Google's most popular cloud services. Please note, however, that pricing can and does change frequently.

Popular Features of  google Cloud  Service:


Service

Features

APP Engine

• PaaS with support for most language runtimes, frameworkds and third-party libraries.
• Free tier
• Highly scalable
• Open and flexible
• Powerful monitoring and management tools

 

Compute Engine

• Highly scalable
• Custom machine types available
• Industry leadIng pricing • Fast boots • Minute-level incremental billing with automatic dlscounting • Envlronmentally friendly data centers

 

Container Engine

• Built on Docker and Kubernetes
• Fast deployment
• Fully managed
• Integrateswith identity and access management services

 

Cloud Storage

• Best-In-class performance and reliability.
• Low prices
• Seamless data lifecycle for active, nearline and colddata
• Built-in security

 

BigQuery

• Petabyte-scale
• Low cost
• Serverless architecture
• Designed for analytics
• Fast performance

 

Cloud Machine Learning Engine

• Built on Google's TensoFlow framework
• Support for thousands of users and TBs of data
• Deep learning and predictive analytics capabilities

 






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