Google Cloud Platform,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, Gmail and YouTube. In this post we are going to discuss how much is Google cloud platform
What Google platform does?
Google Cloud Platform is a provider of computing resources for deploying and operating applications on the web. Its specialty is providing a place for individuals and enterprises to build and run software, and it uses the web to connect to the users of that software. Think of tens of thousands of websites operating on a network of “hyperscale” (very big, but also very divisible) data centers, and you’ll get the basic idea.
When you run a website, an application, or a service on Google Cloud Platform (GCP), Google keeps track of all of the resources it uses — specifically, how much processing power, data storage, database queries, and network connectivity it consumes. Rather than lease a server or a DNS address by the month (which is what you would do with an ordinary website provider), you pay for each of these resources on a per-second basis (competitors charge per-minute), with discounts that apply when your services are used heavily by your customers on the web.
Features of Google Cloud platform
- Automating the deployment of modern applications. An app is made of many moving parts, which is why some developers prefer to build their apps in the cloud to begin with (“cloud-native”). Google is the originator of Kubernetes, which is an orchestrator for applications comprised of many components. Early on, Google took a proactive approach to automating the deployment of these multifaceted apps to the cloud: for example, opening itself to Kubo, an automation platform originally created to help developers using Cloud Foundry to deploy their applications from dev platforms to the cloud.
- Creative cost control. As you’ll see later, rather than being the low-cost leader, Google’s strategy with GCP is to enable cost competitiveness in certain “sweet spot” scenarios. For example, Google offers a lifecycle manager for its object data storage, which enables the offloading or deletion of objects that haven’t been used in 30 days or more.
- Friendlier hand-holding for first-time users. A cloud services platform can be an overwhelming concept for a newcomer to digest. Just as it wasn’t obvious to many consumers what the purpose of a microcomputer actually was, a public cloud is a new and foreign beast for folks who are accustomed to seeing and touching the machine they’re using. GCP offers step-by-step examples of doing many of the most common tasks — for example, spinning up a Linux-based virtual machine, which is like claiming and setting up your own, brand new computer out of thin air.
Services of Google Cloud platform
- 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.
How much is Google cloud platform?
Each of these services consumes fundamental resources of cloud computing: processor power, memory, data storage, and connectivity. Like other cloud service providers, Google charges its GCP customers for the resources these services consume. So whatever you choose to do with GCP, you pay for the resources they consume. (As you can imagine, BigQuery and BigTable can incur some significant expenses in data storage consumption.)
Google Compute Engine has its own selection of VM instances, as its competitors do. It calls these instances pre-defined, with base prices (at the time of this writing) of just over $0.03 per virtual CPU per hour of processing, and $0.004 per gigabyte per hour for storage. However, Google then recalculates these figures on a per-second basis, with a minimum time interval of 60 seconds.
Also, if you are interested in specific services. You can visit this link where there is catalogue of all the services along with their pricing.