Google Cloud Platform Services

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Welcome to cloudaffaire.com and this is Debjeet.

In this blog post, we will try to list all the services currently available under GCP.

Compute Services:

Google Compute Engine:

Compute Engine lets you create and run virtual machines on Google infrastructure. Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google’s infrastructure.

Google App Engine:

App Engine is a fully managed, serverless platform for developing and hosting web applications at scale. You can choose from several popular languages, libraries, and frameworks to develop your apps, then let App Engine take care of provisioning servers and scaling your app instances based on demand.

Google Kubernetes Engine:

Google Kubernetes Engine provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The GKE environment consists of multiple machines (specifically, Google Compute Engine instances) grouped together to form a cluster.

Google Cloud Functions:

Google Cloud Functions is a serverless execution environment for building and connecting cloud services. With Cloud Functions you write simple, single-purpose functions that are attached to events emitted from your cloud infrastructure and services. Your function is triggered when an event being watched is fired. Your code executes in a fully managed environment. There is no need to provision any infrastructure or worry about managing any servers.

Google Cloud Run:

Cloud Run is a managed compute platform that enables you to run stateless containers that are invocable via web requests or Pub/Sub events. Cloud Run is serverless: it abstracts away all infrastructure management, so you can focus on what matters most — building great applications. It is built from Knative, letting you choose to run your containers either fully managed with Cloud Run, or in your Google Kubernetes Engine cluster with Cloud Run for Anthos on Google Cloud.

Networking Services:

Google Virtual Private Cloud:

Google Cloud Virtual Private Cloud (VPC) provides networking functionality to Compute Engine virtual machine (VM) instances, Google Kubernetes Engine (GKE) containers, and the App Engine flexible environment. VPC provides networking for your cloud-based services that is global, scalable, and flexible.

Google Virtual Private Network:

Cloud VPN securely connects your peer network to your Google Cloud (GCP) Virtual Private Cloud (VPC) network through an IPsecVPNconnection. Traffic traveling between the two networks is encrypted by one VPN gateway, then decrypted by the other VPN gateway. This protects your data as it travels over the internet. You can also connect two instances of Cloud VPN to each other.

Google Carrier Peering:

Carrier Peering enables you to access Google applications, such as G Suite, by using a service provider to obtain enterprise-grade network services that connect your infrastructure to Google.

Google Direct Peering:

Direct Peering allows you to establish a direct peering connection between your business network and Google’s edge network and exchange high-throughput cloud traffic. This capability is available at any of more than 100 locations in 33 countries around the world.

Google Dedicated Interconnect:

Dedicated Interconnect provides direct physical connections between your on-premises network and Google’s network. Dedicated Interconnect enables you to transfer large amounts of data between networks, which can be more cost-effective than purchasing additional bandwidth over the public Internet.

Google Partner Interconnect:

Partner Interconnect provides connectivity between your on-premises network and your VPC network through a supported service provider. A Partner Interconnect connection is useful if your data center is in a physical location that can’t reach a Dedicated Interconnect colocation facility or if your data needs don’t warrant an entire 10 Gbps connection.

Google Cloud DNS:

Using Cloud DNS, you can publish your domain names by using Google’s infrastructure for production-quality, high-volume DNS services. Google’s global network of anycast name servers provide reliable, low-latency, authoritative name lookups for your domains from anywhere in the world.

Google Cloud Armor:

Cloud Armor delivers defense at scale against infrastructure and application distributed denial of service (DDoS) attacks by using Google’s global infrastructure and security systems.

Google Cloud Load Balancing:

Cloud Load Balancing allows you to put your resources behind a single IP address that is externally accessible or internal to your Virtual Private Cloud (VPC) network.

Google Traffic Director:

Traffic Director is Google Cloud’s fully managed traffic control plane for service mesh. With Traffic Director, you can deploy global load balancing across clusters and virtual machine (VM) instances in multiple regions, offload health checking from service proxies, and configure sophisticated traffic control policies.

Storage Services:

Google Cloud Storage:

Cloud Storage allows world-wide storage and retrieval of any amount of data at any time. You can use Cloud Storage for a range of scenarios including serving website content, storing data for archival and disaster recovery, or distributing large data objects to users via direct download.

Google Nearline Storage:

Nearline Storage is a low-cost, highly durable storage service for storing infrequently accessed data. Nearline Storage is a better choice than Standard Storage in scenarios where slightly lower availability, a 30-day minimum storage duration, and costs for data access are acceptable trade-offs for lowered at-rest storage costs.

Google Coldline Storage:

Coldline Storage is a very-low-cost, highly durable storage service for data archiving, online backup, and disaster recovery. Unlike other “cold” storage services, your data is available within milliseconds, not hours or days. Coldline Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower availability, 90-day minimum storage duration, costs for data access, and higher per operation costs.

Google Persistent Disk:

Persistent Disk is a durable and high-performance block storage for Google Cloud Platform. Persistent Disk provides SSD and HDD storage which can be attached to instances running in either Compute Engine or Google Kubernetes Engine. Storage volumes can be transparently resized, quickly backed up, and offer the ability to support simultaneous readers.

Google Cloud Filestore:

Use Cloud Filestore to create fully managed NFS file servers on Google Cloud (GCP) for use with applications running on Compute Engine virtual machines (VMs) instances or Google Kubernetes Engine clusters.

Databases Services:

Google Cloud Bigtable:

Cloud Bigtable is Google’s NoSQL Big Data database service. It’s the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Google Cloud Datastore:

Cloud Firestore in Datastore mode is a NoSQL document database built for automatic scaling, high performance, and ease of application development.

Google Cloud Firestore:

Cloud Firestore is a NoSQL document database built for automatic scaling, high performance, and ease of application development. While the Cloud Firestore interface has many of the same features as traditional databases, as a NoSQL database it differs from them in the way it describes relationships between data objects.

Google Cloud Memorystore:

Cloud Memorystore for Redis is a fully managed Redis service for the Google Cloud. Applications running on Google Cloud can achieve extreme performance by leveraging the highly scalable, available, secure Redis service without the burden of managing complex Redis deployments.

Google Cloud Spanner:

Cloud Spanner is a fully managed, mission-critical, relational database service that offers transactional consistency at a global scale, schemas, SQL (ANSI 2011 with extensions), and automatic, synchronous replication for high availability.

Google Cloud SQL:

Cloud SQL is a fully-managed RDBMS database service that makes it easy to set up, maintain, manage, and administer your relational databases on Google Cloud Platform.

Security and identity Services:

Google Cloud Identity and Access Management (IAM):

Cloud Identity and Access Management (Cloud IAM) enables you to create and manage permissions for Google Cloud resources. Cloud IAM unifies access control for Google Cloud services into a single system and presents a consistent set of operations.

Google Cloud Identity Platform:

Identity Platform allows users to authenticate to your applications and services, like multi-tenant SaaS applications, mobile/web apps, games, APIs and more. Identity Platform provides secure, easy-to-use authentication if you’re building a service on Google Cloud, on your own backend or on another platform.

Google Resource Manager:

Google Cloud provides container resources such as organizations and projects that allow you to group and hierarchically organize other Google Cloud resources. This hierarchical organization helps you manage common aspects of your resources, such as access control and configuration settings.

Google Security Command Center:

Security Command Center is the canonical security and data risk database for Google Cloud. Security Command Center enables you to understand your security and data attack surface by providing asset inventory, discovery, search, and management.

Google Web Security Scanner:

Web Security Scanner identifies security vulnerabilities in your App Engine, Compute Engine, and Google Kubernetes Engine web applications. It crawls your application, following all links within the scope of your starting URLs, and attempts to exercise as many user inputs and event handlers as possible.

Google VPC Service Controls:

With VPC Service Controls, administrators can define a security perimeter around resources of Google-managed services to control communication to and between those services.

Google Access Context Manager:

Access Context Manager allows Google Cloud organization administrators to define fine-grained, attribute-based access control for projects and resources in Google Cloud. Administrators first define an access policy, which is an organization-wide container for access levels and service perimeters.

Google Access Transparency:

As part of Google’s long-term commitment to security and transparency, you can use Access Transparency, which provides you with logs of actions taken by Google staff when accessing your data.

Google Binary Authorization:

Binary Authorization is a service on Google Cloud Platform (GCP) that provides software supply-chain security for applications that run in the Cloud. Binary Authorization works with images that you deploy to Google Kubernetes Engine (GKE) from Container Registry or another container image registry. With Binary Authorization, you can ensure that internal processes that safeguard the quality and integrity of your software have successfully completed before an application is deployed to your production environment.

Google Cloud Data Loss Prevention (DLP):

Cloud DLP provides access to a powerful sensitive data inspection, classification, and de-identification platform.

Google Identity-Aware Proxy (IAP):

Identity-Aware Proxy (IAP) lets you manage access to applications running in App Engine standard environment, App Engine flexible environment, Compute Engine, and GKE. IAP establishes a central authorization layer for applications accessed by HTTPS, so you can adopt an application-level access control model instead of using network-level firewalls. When you turn on IAP, you must also use signed headers or the App Engine standard environment Users API to secure your app.

Management Services:

Google Stackdriver:

Stackdriver aggregates metrics, logs, and events from infrastructure, giving developers and operators a rich set of observable signals that speed root-cause analysis and reduce mean time to resolution (MTTR).

Google Cloud API:

Google Cloud APIs are a key part of Google Cloud Platform, allowing you to easily add the power of everything from storage access to machine-learning-based image analysis to your Cloud Platform applications.

Google Deployment Manager:

Deployment Manager is an infrastructure deployment service that automates the creation and management of Google Cloud resources. Write flexible template and configuration files and use them to create deployments that have a variety of Google Cloud services, such as Cloud Storage, Compute Engine, and Cloud SQL, configured to work together.

Google gcloud:

The gcloud command-line interface is a tool that provides the primary CLI to Google Cloud Platform. You can use this tool to perform many common platform tasks either from the command-line or in scripts and other automation.

Google Cloud Shell:

Cloud Shell is an interactive shell environment for Google Cloud Platform that makes it easy for you to learn and experiment with GCP and manage your projects and resources from your web browser.

Google Anthos:

Anthos is a modern application management platform that provides a consistent development and operations experience for cloud and on-prem environments. This page provides an overview of each layer of the Anthos infrastructure and shows how you can leverage its features.

Google Cloud Billing:

A Cloud Billing Account defines who pays for a given set of Google Cloud resources, and it can be linked to one or more Google Cloud projects. Your project usage is charged to the linked Cloud Billing Account.

Google Cloud Console:

Google Cloud Console is the frontend interface of your Google Cloud Platform which lets you build, deploy, and scale applications, websites, and services through a web browser.

Data and Analytics Services:

Google Cloud Composer:

Cloud Composer is a managed Apache Airflow service that helps you create, schedule, monitor and manage workflows. Cloud Composer automation helps you create Airflow environments quickly and use Airflow-native tools, such as the powerful Airflow web interface and command-line tools, so you can focus on your workflows and not your infrastructure.

Google Cloud Data Fusion:

Cloud Data Fusion is a fully managed, cloud-native, enterprise data integration service for quickly building and managing data pipelines. Cloud Data Fusion provides a graphical interface to increase time efficiency and reduce complexity. Now business users, developers, and data scientists can easily and reliably build scalable data integration solutions to cleanse, prepare, blend, transfer, and transform data— without having to wrestle with infrastructure.

Google Dataflow:

Dataflow is a managed service for executing a wide variety of data processing patterns. The documentation on this site shows you how to deploy your batch and streaming data processing pipelines using Dataflow, including directions for using service features.

Google Dataprep:

Use Cloud Dataprep to explore and transform raw data from disparate and/or large datasets into clean and structured data for further analysis and processing.

Google Dataproc:

Cloud Dataproc is a managed Apache Spark and Apache Hadoop service that lets you take advantage of open-source data tools for batch processing, querying, streaming, and machine learning. Cloud Dataproc automation helps you create clusters quickly, manage them easily, and save money by turning clusters off when you don’t need them. With less time and money spent on administration, you can focus on your jobs and your data.

Google Cloud Pub/Sub:

Pub/Sub is a fully-managed real-time messaging service that allows you to send and receive messages between independent applications.

Google BigQuery:

BigQuery is Google’s fully managed, petabyte-scale, low-cost analytics data warehouse. BigQuery is NoOps—there is no infrastructure to manage and you don’t need a database administrator—so you can focus on analyzing data to find meaningful insights, use familiar SQL, and take advantage of our pay-as-you-go model.

Google Cloud Life Science:

Cloud Life Sciences is a suite of services and tools for managing, processing, and transforming life sciences data. It also enables advanced insights and operational workflows using highly scalable and compliant infrastructure. Cloud Life Sciences includes features such as the Cloud Life Sciences API and extract-transform-load (ETL) tools, and more.

AI and ML Services:

Google Cloud AI Hub:

Google Cloud’s AI Hub is a hosted repository of plug-and-play AI components, including end-to-end AI pipelines and out-of-the-box algorithms. AI Hub provides enterprise-grade sharing capabilities that let organizations privately host their AI content to foster reuse and collaboration among machine learning developers and users internally. You can also easily deploy unique Google Cloud AI and Google AI technologies for experimentation and ultimately production on Google Cloud and hybrid infrastructures.

Google Tensor Processing Units (TPUs):

Tensor Processing Units (TPUs) are Google’s custom-developed application-specific integrated circuits (ASICs) used to accelerate machine learning workloads. TPUs are designed from the ground up with the benefit of Google’s deep experience and leadership in machine learning.

Google Deep Learning VM Images:

The AI Platform Deep Learning VM Images are a set of Debian 9-based Compute Engine virtual machine images optimized for data science and machine learning tasks. All images come with key ML frameworks and tools pre-installed, and can be used out of the box on instances with GPUs to accelerate your data processing tasks.

Google AI Platform:

AI Platform brings the power and flexibility of TensorFlow, scikit-learn and XGBoost to the cloud. You can use AI Platform to train your machine learning models using the resources of Google Cloud. In addition, you can host your trained models on AI Platform so that you can send them prediction requests and manage your models and jobs using the Google Cloud services.

Google AI Platform Deep Learning Containers:

AI Platform Deep Learning Containers provide you with performance-optimized, consistent environments to help you prototype and implement workflows quickly. Deep Learning Containers images come with the latest machine learning data science frameworks, libraries, and tools pre-installed.

Google AI Platform Data Labeling Service:

You use the AI Platform Data Labeling Service to request having human labelers label a collection of data that you plan to use to train a custom machine learning model.

Google AI Platform Notebooks:

AI Platform Notebooks makes it easy to manage JupyterLab instances through a protected, publicly available notebook instance URL. A JupyterLab instance is a Deep Learning virtual machine instance with the latest machine learning and data science libraries pre-installed.

Google BigQuery ML:

BigQuery ML enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data.

Google Cloud Talent Solution:

Transform your job search and candidate matching capabilities with Cloud Talent Solution, designed to support enterprise talent acquisition technology and evolve with your growing needs. This AI solution includes features such as Job Search and Profile Search (Beta) to provide candidates and employers with an enhanced talent acquisition experience.

Google Cloud AutoML:

Cloud AutoML makes the power of machine learning available to you even if you have limited knowledge of machine learning. You can use AutoML to build on Google’s machine learning capabilities to create your own custom machine learning models that are tailored to your business needs, and then integrate those models into your applications and web sites.

Google Cloud Vision:

Cloud Vision includes several options that you can use to integrate machine learning vision models into your applications and web sites.

Google Video Intelligence API:

Video Intelligence API allows developers to use Google video analysis technology as part of their applications. The REST API enables users to annotate videos stored locally or in Cloud Storage with contextual information at the level of the entire video, per segment, per shot, and per frame.

Google Natural Language:

Natural Language includes several options that you can use to integrate machine learning natural language models into your applications and web sites.

Google Cloud Translation:

Cloud Translation includes two options that you can use to integrate machine learning translation models into your applications and web sites.

Google Cloud Speech-to-Text:

Cloud Speech-to-Text enables easy integration of Google speech recognition technologies into developer applications. Send audio and receive a text transcription from the Speech-to-Text API service.

Google Cloud Text-to-Speech:

Text-to-Speech converts text or Speech Synthesis Markup Language (SSML) input into audio data of natural human speech.

Google Dialogflow:

Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product.

Google Recommendations AI:

Recommendations AI enables you to build an end-to-end personalized recommendation system based on state-of-the-art deep learning ML models, without a need for expertise in ML or recommendation systems.

Google Cloud Inference API:

The Cloud Inference API allows you to Index and load a dataset consisting of multiple data sources stored on Google Cloud Storage, Execute Inference queries over loaded datasets, computing relations across matched groups (see below for data organization), Unload or cancel the loading of a dataset and Get simple status updates for a dataset sent for processing.

Developer Oriented Services:

Google Cloud SDK:

Google Cloud SDK is a set of tools that you can use to manage resources and applications hosted on Google Cloud Platform. These include the gcloud, gsutil, and bq command-line tools.

Google Cloud Build:

Cloud Build is a service that executes your builds on Google Cloud Platform infrastructure. Cloud Build can import source code from Google Cloud Storage, Cloud Source Repositories, GitHub, or Bitbucket, execute a build to your specifications, and produce artifacts such as Docker containers or Java archives.

Google Cloud Source Repositories:

Cloud Source Repositories are fully-featured, private Git repositories hosted on Google Cloud.

Google Cloud Code for IntelliJ:

Google Cloud Code provides IDE support to help you develop and deploy Kubernetes and App Engine applications, manage your Google Cloud APIs and libraries, view your Cloud Storage content, add new projects to Cloud Source Repositories, and inspect live applications with Stackdriver Debugger, among a wealth of functionality, bringing speed, harmony, and efficiency to your development workflow.

Google Cloud Tools for PowerShell:

Cloud Tools for PowerShell is a set of cmdlets for PowerShell that lets you manage Google Cloud resources.

Google Cloud Tools for Visual Studio:

Cloud Tools for Visual Studio enables ASP.NET development in Visual Studio on Google Cloud.

Google Cloud Tools for Eclipse:

Cloud Tools for Eclipse is a Google-sponsored open-source plugin that supports Google Cloud Platform development inside the Eclipse IDE.

Google Container Registry:

Container Registry provides secure, private Docker image storage on Google Cloud Platform.

Other Services:

SAP:

Google Cloud has an ongoing partnership with SAP to provide SAP-certified infrastructure for all of your SAP systems. You can even choose Google Cloud to power SAP cloud offerings, like SAP S/4HANA Cloud, SAP Ariba, SAP HANA Enterprise Cloud, and the SAP Cloud Platform itself.

Google Transfer Appliance:

Transfer Appliance is a hardware appliance you can use to securely migrate large volumes of data (from hundreds of terabytes up to 1 petabyte) to Google Cloud Platform without disrupting business operations.

Google BigQuery Data Transfer:

The BigQuery Data Transfer Service automates data movement into BigQuery on a scheduled, managed basis. Your analytics team can lay the foundation for a BigQuery data warehouse without writing a single line of code.

Google Cloud Internet of Things (IoT):

Google Cloud Internet of Things (IoT) Core is a fully managed service for securely connecting and managing IoT devices, from a few to millions. Ingest data from connected devices and build rich applications that integrate with the other big data services of Google Cloud Platform.

GCP keeps adding new services in their arsenal to stay relevant in the cloud market and fulfill customer requirements. Hope you have enjoyed this blog post.