Google Cloud Platform is a suite of public cloud computing services offered by Google. The platform includes a range of hosted services for compute, storage and application development that run on Google hardware. Google Cloud Platform services can be accessed by software developers, cloud administrators and other enterprise IT professionals over the public internet or through a dedicated network connection.
Google Cloud Platform
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Google Cloud Platform
Google Cloud Platform Services
Google Cloud Platform offers services for compute, storage, networking, big data, machine learning and the internet of things (IoT), as well as cloud management, security and developer tools. The core cloud computing products in Google Cloud Platform include:
Google Compute Engine
which is an infrastructure-as-a-service (IaaS) offering that provides users with virtual machine instances for workload hosting.
Google App Engine
which is a platform-as-a-service (PaaS) offering that gives software developers access to Google’s scalable hosting. Developers can also use a software developer kit (SDK) to develop software products that run on App Engine.
Google Cloud Storage
which is a cloud storage platform designed to store large, unstructured data sets. Google also offers database storage options, including Cloud Datastore for NoSQL nonrelational storage, Cloud SQL for MySQL fully relational storage and Google’s native Cloud Bigtable database.
Google Container Engine
which is a management and orchestration system for Docker containers that runs within Google’s public cloud. Google Container Engine is based on the Google Kubernetes container orchestration engine.
Google continues to add higher-level services, such as those related to big data and machine learning, to its cloud platform. Google big data services include those for data processing and analytics, such as Google BigQuery for SQL-like queries made against multi-terabyte data sets. In addition, Google Cloud Dataflow is a data processing service intended for analytics; extract, transform and load (ETL); and real-time computational projects. The platform also includes Google Cloud Dataproc, which offers Apache Spark and Hadoop services for big data processing.
For artificial intelligence (AI), Google offers its Cloud Machine Learning Engine, a managed service that enables users to build and train machine learning models. Various APIs are also available for the translation and analysis of speech, text, images and videos.
Google also provides services for IoT, such as Google Cloud IoT Core, which is a series of managed services that enables users to consume and manage data from IoT devices.
The Google Cloud Platform suite of services is always evolving, and Google periodically introduces, changes or discontinues services based on user demand or competitive pressures. Google’s main competitors in the public cloud computing market include Amazon Web Services (AWS) and Microsoft Azure.
GOOGLE CLOUD STORAGE VS. AMAZON AWS
GCP began as a consumer business model around one of the core functions it originally created for its own purposes: distributed software orchestration. It doesn’t help you or your organization build software as much as it would help you deploy it. As the creator of Kubernetes, Google’s success is in getting software to the point where it can be distributed globally. It solved the problem of distributing updates to its search engine and e-mail service, and it then scaled down this solution to a form that’s usable by a small business.
Any business that knows what distributed software is, let alone what it wants to do with the stuff, is already pretty tech-savvy. But that’s not really the market Google would prefer to cater to. So it makes the effort to make this technology more approachable, which at one scale is not unlike instructing home gardeners in how to make better use of nuclear reactors.
This ends up being the key differentiator between Azure and GCP: To someone who may not be fully versed in the subject matter, Google has made further strides (so far) in adapting its services to people who may not understand them yet. You may be able to get a handle on BigQuery or Cloud Storage more readily.
GOOGLE CLOUD PLATFORM VS. MICROSOFT AZURE
Lately, Google has refrained from taking an adversarial stance against Microsoft. Indeed, the two companies are cooperating more than in years past, as indicated by the presence of Microsoft’s .NET language platform in Google App Engine.
Indeed, Google is training almost all of its marketing efforts on Amazon, the leader in the cloud services space. To that end, here is how it’s positioning itself:
- GCP is not about to topple AWS as the leading host of virtual machine instances. So it offers alternatives, most notably custom instances, and pricing models that can give certain customers an advantage. VMs may be the old deployment model for software, but no cloud service provider can relinquish a foothold in this service and expect to continue being considered a player.
- Amazon held out until the very last possible moment to produce its own Kubernetes engine. . . and then waited a bit longer, evidently reluctant to promote a deployment model that would cut into its own mainline business. As a result, Google has been taking a victory lap as the originator and still, in the public eye, the leader of Kubernetes. One more argument in Google’s favor that has yet to be disproven is that Amazon’s Kubernetes system is centered around Amazon, whereas GCP (more so today with Anthos) answers enterprise customers’ needs to avoid vendor lock-in.
- Recent analyst reports from multiple sources have shared the views of cloud computing customers that Amazon’s wealth of service options, in its enormity alone, can work to its disadvantage. No three sources can come to an agreement on where an AWS customer should want to begin. Google can use this to its advantage by focusing on successful services that customers actually demand, and not so much on experiments and beta tests that won’t sink the company if they fail.
Most major markets in any healthy economy loathe a tri-opoly. Usually it’s the safest bet an analyst can make that the #3 player will be shaken out of contention, and must make itself content with providing “alternative” products or services to niche markets.
But Google has the one luxury that no other #3 player in any market has: the role of the #1 player in a different, virtually one-player market: online advertising. Its cloud services can be allowed to mature and find their audiences, just as though the survival of the company didn’t rest upon them. A former Microsoft CEO once warned Google that his company made its mark for being tenacious, tenacious, tenacious. But he’s gone now. And Google Cloud Platform has every reason — including all the time it needs — to keep trying.
To capture the growing interest in web applications, Google App Engine was launched in April 2008 as a Platform as a Service (PaaS) resource allowing developers to build and host apps on Google’s infrastructure. App Engine came out of preview in September 2011, and the Google Cloud Platform name was formally adopted in 2013.
Since the introduction of Google App Engine, the company subsequently released a variety of complementary tools, such as its data storage layer, and its Infrastructure as a Service (IaaS) component known as the Google Compute Engine, which supports the use of virtual machines. After growing as an IaaS provider, Google added additional products including a load balancer, DNS, monitoring tools, and data analysis services, bringing GCP closer to feature parity with AWS and Azure, making it better able to compete in the cloud market.
Google Cloud Platform products span the following categories:
- Artificial intelligence & machine learning:AI Hub (beta), Cloud AutoML (beta), Cloud TPU, Cloud Machine Learning Engine, Diagflow Enterprise Edition, Cloud Natural Language, Cloud Speech-to-Text, Cloud Text-to-Speech, Cloud Translation, Cloud Vision, Cloud Video Intelligence, Cloud Inference API (alpha), and more
- API management:API Analytics, API Monetization, Cloud Endpoints, Developer Portal, Cloud Healthcare API
- Compute:Compute Engine, Shielded VMs, Container security, App Engine, Cloud Functions, GPU, and more
- Data analytics:BigQuery, Cloud Dataflow, Cloud Dataproc, Cloud Datalab, Cloud Dataprep, Cloud Composer, and more
- Databases:Cloud SQL, Cloud Bigtable, Cloud Spanner, Cloud Datastore, Cloud Memorystore
- Developer tools:Cloud SDK, Container Registry, Cloud Build, Cloud Source Repositories, Cloud Tasks, and more, as well as Cloud Tools for IntelliJ, PowerShell, Visual Studio, and Eclipse
- Internet of Things (IoT):Cloud IoT Core, Edge TPU (beta)
- Hybrid and multi-cloud:Google Kubernetes Engine, GKE On-Prem, Istio on GKE (beta), Anthos Config Management, Serverless, Stackdriver, and more
- Management Tools:Stackdriver, Monitoring, Trace, Logging, Debugger, Cloud Console, and more
- Media:Anvato, Zync Render
- Migration:Cloud Data Transfer, Transfer Appliance, BigQuery Data Transfer Service, Velostrata, VM Migration, and more
- Networking:Virtual Private Cloud (VPC), Cloud Load Balancing, Cloud Armor, Cloud CDN, Cloud NAT, Cloud Interconnect, Cloud VPN, Cloud DNS, Network Service Tiers, Network Telemetry
- Security:Access Transparency, Cloud Identity, Cloud Data Loss Prevention, Cloud Key Management Service, Cloud Security Scanner, and more
- Storage:Cloud Storage, Persistent Disk, Cloud Filestore, and more
Google Cloud Platform operates from redundant data centers in five regions, with several others set to open by 2017. The technology builds on the same infrastructure and data centers used for Google’s consumer services, such as search, Gmail, Maps and YouTube. Because of this, few companies match Google’s scale at building, optimizing and managing hyperscale infrastructure.
Like Amazon Web Services (AWS), Google Cloud Platform has connected, but geographically distributed, infrastructure deployed in regions and availability ; the former is a group of data centers in close proximity to enable automatic, site-level redundancy, while are widely separated regions that are isolated and independent. Google Cloud Platform reduces latency and improves performance through the synchronization of data between regions.