What Are Google Cloud Services and Why Do You Need Them?
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.
DISTINGUISHING FEATURES OF GOOGLE CLOUD PLATFORM
So what do you actually do on a cloud platform, and why would you want to do it on Google’s? You use a cloud platform when you want the services you present to your users, your customers, or your fellow employees to be an application as opposed to a website. Maybe you want to help homebuilders estimate the size and structure of the cabinets they need to rebuild a kitchen. Maybe you’re analyzing the performance statistics of athletes trying out for a college sports club, and you need sophisticated analytics to tell the head coaches whose performance could improve. Or you could be scanning hundreds of thousands of pages of archived newspaper copy, and you need to build a scannable index dating back decades.
You use a cloud platform such as GCP when you want to build and run an application that can leverage the power of hyperscale data centers in some way: to reach users worldwide, or to borrow sophisticated analytics and AI functions, or to utilize massive data storage, or to take advantage of cost efficiencies. You pay not for the machine but for the resources the machine uses.
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.
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.
[NOTE: This segment was recently updated with the help of clarifications offered by Google Cloud.]
- Google Cloud Platform is essentially a public cloud-based machine whose services are delivered to customers on an as-you-go basis, by way of service components.
- A public cloud lets you leverage its resources to empower the applications you build, as well as to reach a broader base of customers.
- Although Google does offer a virtual machine hosting service similar to, and competitive with, Amazon Web Services, its primary service model is based around the development and deployment of more modern, containerized applications.
- GCP’s strategy for competing on price is to offer discounts for sustained use, for customized use, and for committed use.
- The targeted core user for GCP at present appears to be the business — small, medium, or large — that is well into its journey to modern application models, and needs a more cost-effective and efficient means of deploying them.
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