Google Cloud Platform (GCP)

What is Google Cloud Platform (GCP)?

Google Cloud Platform (GCP), offered by Google, 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 and YouTube.Alongside a set of management tools, it provides a series of modular cloud services including computing, data storage, data analytics and machine learning. Registration requires a credit card or bank account details.

Google Cloud Platform provides infrastructure as a service, platform as a service, and serverless computing environments.

In April 2008, Google announced App Engine, a platform for developing and hosting web applications in Google-managed data centers, which was the first cloud computing service from the company. The service became generally available in November 2011. Since the announcement of App Engine, Google added multiple cloud services to the platform.

Google Cloud Platform is a part of Google Cloud, which includes the Google Cloud Platform public cloud infrastructure, as well as G Suite, enterprise versions of Android and Chrome OS, and application programming interfaces (APIs) for machine learning and enterprise mapping services. 

Services of Google Cloud Platform

Cloud services are difficult to understand in the abstract. So to help you comprehend Google Cloud Platform more explicitly, here are the major services that GCP operates:

• Google Compute Engine (GCE) competes directly against the service that put Amazon Web Services on the map: hosting virtual machines (VMs, servers that exist entirely as software).
• Google Kubernetes Engine (GKE, formerly Google Container Engine) is a platform for a more modern form of containerized application (housed in what are often still called "Docker containers"), which is engineered for deployment on cloud platforms.
• Google App Engine provides software developers with tools and languages such as Python, PHP, and now even Microsoft's .NET languages, for building and deploying a web application directly on Google's cloud. This is different from building the application locally and deploying it remotely on the cloud; this is "cloud-native" development: building, deploying, and evolving the application all remotely.
• Google Cloud Storage is GCP's object data store, meaning it accepts any quantity of data and represents that data to its user in whatever manner is most useful -- for example, as files, a database, a data stream, an unordered list of data, or as multimedia.
• Nearline is a way to utilize Google Cloud Storage for backup and archival data -- the kind that you wouldn't necessarily consider a database, and that may only be accessed once, by one user, typically no more often than once per month. Google calls this model "cold storage," and adapts its pricing model to account for this low level of utilization, with the aim of making Nearline a more attractive option for such purposes as system backups.
• Anthos, announced last April, is GCP's system for organizing and maintaining applications that may be centered around Google, but may utilize resources from AWS or Azure ("multi-cloud services"). Think of an application whose code base is hosted by Google, but that borrows an AI function from AWS and that stores its logs in an object store on Azure.
• BigQuery is a data warehousing system using Google Cloud Storage designed for very large quantities of highly distributed data, enabling SQL queries to be executed across multiple databases of varying structure levels. Rather than a traditional, row-based, record-oriented SQL relational database index, BigQuery utilizes a columnar storage system in which components of records are stacked onto one another and streamed to a parallel storage system. Such an organization proves useful in analytics applications, which collect broad statistics on simple, often general, relationships between data elements.
• Cloud Bigtable (formerly BigTable) is a highly distributed data system that organizes related data into a multi-dimensional assembly of key/value pairs, based on the large-scale storage system Google created for its own use in storing search indexes. Such an assembly is easier for analytics applications to manage than a very large index for a colossal relational database with multiple tables whose records would have to be joined at query time.
• Cloud SQL (not yet ready for public consumption) hosts much more traditional, relational database tables and indexes, using a GCE instance that scales itself up to meet the database's performance demands.
• Cloud Translation, Text-to-Speech, and Speech-to-Text, as their names suggest, leverage Google's existing capability for spoken and written language management, for use in custom applications.
• Apigee is a modeling system for producing and managing APIs -- service calls to server-based functions, using the Web as the medium of communication. An Apigee user may model, test, and deploy mechanisms for their existing web apps to be discoverable using APIs, and monitor how web users make use of those API calls for their own purposes.
• Istio is an interesting kind of "phone book" for modern, scalable applications that are distributed as individual components called microservices. A conventional, contiguous application knows where all of its functions are; a microservices-based application needs to be informed, by way of a service mesh. Istio was originally developed as a service mesh by an open source partnership made up of Google, IBM, and ride-sharing service Lyft.
• Cloud Pub/Sub (publish-and-subscribe) is a mechanism that replaces the message queues used by middleware during the earlier era of client/server applications. For applications that are designed to cooperate without being explicitly connected to one another ("asynchronously"), Pub/Sub serves as a kind of post office for events, so one application can notify others of their progress or about requests they may have.
• Cloud AutoML is a suite of services geared to enable applications to leverage machine learning -- to detect perceptible patterns throughout large quantities of data, and utilize those patterns within a program.
• Cloud Run is a newly announced service enabling software developers to stage and deploy their applications to Google's cloud using the so-called serverless model -- building and running programs with the appearance of being hosted locally instead of in the cloud.