Google Cloud Training in Kolkata

Carrer Elements 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.
• This is far from a complete list of Google Cloud Platform services, though it does introduce you to the major entries. In fact, some of the company's many services (all of which may be found in a list on this page) are applications or reconfigurations of other services -- ways to use a service that would perform a broad function, for a more specific purpose.
• Yes, G Suite (Google's suite of applications) is a kind of software-as-a-service (SaaS) that's delivered to you through Google's Cloud. But like Gmail, it isn't really part of Google Cloud Platform.
• We use the word "service" a lot to refer to what Google is bartering here, but think of GCP for a moment as more of a product. Productivity applications are a different department from hosted applications and interfaced functions.
• More importantly, when you become a GCP customer, you enter into a very different agreement than the one that applies to G Suite. GCP addresses an expectation that you will be using its cloud-based resources to create your own services and applications that will most likely be used by other people besides yourself.
• So Google has service-level commitments it pledges to meet, which it spells out in very explicit detail for each of its services.

What does using Google Cloud Platform cost?

• 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.)
• The formulas for determining the actual prices for resource consumption are actually somewhat complex. Google does offer a pricing calculator using formulas that are updated up-to-the-minute. But to use that calculator, your ballpark estimates of what resources you plan to consume, need to be within a surprisingly narrow ballpark.
• For example, to obtain a price estimate for Google Kubernetes Engine, you'd need to know the maximum number of compute nodes you'd be scaling out to, how much persistent disk storage your application will require (as opposed to ephemeral storage), and which availability zone you feel would be most efficient for load balancing, among other factors.
• GCP then applies discounts for certain usage patterns of GCE and other services. Google claims these discounts can reduce average expenditures for its cloud services.
• Google Compute Engine allows customers to preempt virtual machine instances when they're not in active use.
• So unlike a pricing scenario where you pay for the instance plus the resources it uses, a GCE customer pays for the perceptibility, but is then discounted when that preemption is put into play. The company often claims customers have saved as much as 80% over competitors' services, and 8% on average over AWS.
• Google claims that GCE customers can save significantly when they tailor their own custom instance types, as opposed to choosing an over-provisioned, pre-configured instance type.
• Enterprise customers anticipating heavy data consumption can sign up for a program called Storage Growth Plan, which entitles them to discounts if they commit to a minimum price per month for 12 months.
• This is for very heavy data consumers -- not small businesses, but enterprises that plan to have Google host massive data stores.All this being said, Google's specialty is not the classic virtual machine.
• Although you could conceivably save money over AWS deploying a VM in Google's cloud, especially on a custom instance, GCP is gearing itself more and more to be a host for containerized applications -- a modernized deployment and management system for applications that were designed during, and for, the cloud era.