Google Cloud Services is a set of Computing, Networking, Storage, Big Data, Machine Learning, and Management services offered by Google which runs on the same cloud infrastructure that Google uses internally for YouTube, Gmail, and other end-user products.
In this blog, we are going to give an overview of each of these services.
- Computing Service
- Storage and Database Service
- Networking Service
- Big Data Service
- Machine Learning Service
- Identity and Security Service
- Management and Developer Tools
1.) Computing Service ^
Google Cloud provides users with the facility of computing and hosting where you can choose to do the following:
- Work in a serverless environment
- Use a managed application platform
- Build a cloud-based infrastructure to have maximum control and flexibility
- Leverage container technologies to achieve maximum flexibility
1.1 Compute Engine (Virtual Machine)
Compute engine is an unmanaged compute service of Google Cloud. It is an IaaS (Infrastructure As A Service) service that provides virtual machines (VMs) hosted on Google’s infrastructure. Users can perform many tasks after building a compute engine like:
- Choose the regions and zones to deploy resources, giving users control over where the data is stored and used.
- Choose the required operating systems, development stacks, languages, frameworks, services, and other software technologies as per users’ preference.
- Make use of Google Cloud Storage or any third-party technologies.
- Use virtual machines (VMs), called instances, to build applications similar to that of as you build your own hardware infrastructure.
To know more about Compute Engine read our blog on Google Compute Engine.
1.2 Google App Engine
The App Engine is a PaaS (Platform As A Service) offering of Google Cloud used for building scalable web applications and IoT backends. It scales applications automatically depending upon the traffic received. It provides users with built-in services and APIs, such as Datastores, NoSQL, and a user authentication API.
Read more about it in our blog on App Engine.
1.3 Cloud Functions
It is a function as a service (FaaS) offering which provides a serverless execution environment for building and connecting cloud services. It is an event-based, asynchronous computing solution allowing users to create microservices (small, single-purpose functions) that respond to cloud events without the need for an explicitly managed server or a runtime environment. It can be written using JavaScript, Python 3, Go, or Java.
To create your first cloud Function, read our blog at Cloud Function
1.4 Google Kubernetes Engine/ Container Engine
It is a strong Cluster Manager and balanced system for running Docker containers. Kubernetes Engine schedules your containers into the cluster, keeps them healthy, and manages them automatically based on the requirements defined by the user.
Read more about Kubernetes Engine in our blog at Introduction to Kubernetes Engine.
1.5 Google Cloud Container Registry
The container registry is a private Docker repository to manage Docker Images and works with the popular continuous delivery systems. Customers can decide who can access what with fine-grained access control.
2.) Storage And Database Services ^
Google Cloud provides a variety of storage and database services. Some of them are:
2.1 Google Cloud Storage
Cloud Storage is a service for storing objects in Google Cloud. An object is an immutable piece of data consisting of a file of any format. These objects are stored in containers called buckets. All buckets are associated with a project, and you can group your projects under an organization. It is similar to the S3 bucket in AWS.
Read our blog on Google Cloud Storage to get a detailed overview.
2.2 Cloud SQL
It is a fully-managed database service which allows user to create, configure, use, and administer relational MySQL and PostgreSQL databases in the cloud.
Read more about Cloud SQL in our blog.
2.3 Cloud Bigtable
Cloud Bigtable is a high-performance NoSQL Big Data database service, designed to support very large workloads at consistent low latency and high throughput rates. It integrates conveniently with popular Big Data tools like Hadoop and Spark and supports the open-source, industry-standard HBase API. Google uses Bigtable internally to power services including Google Search and Gmail.
2.4 Cloud Datastore
It is a NoSQL database that stores data in JSON documents (similar to MongoDB) which are automatically indexed so you can query on individual attributes. It provides an elastic, highly available document-oriented database as a service. It can store terabytes of data.
2.5 Persistent Disk
It is a service that provides SSD and HDD storage that can be attached to instances running in either Compute Engine or Container Engine.
2.6 Cloud Spanner
Cloud Spanner is a managed globally distributed relational database with ACID transactions, strong consistency, SQL semantics, horizontal scaling, and high availability features.
To know more about these services in detail read our blog on Google Cloud Storage & Database Services for Beginners.
3.) Networking Services ^
Networking is one of the most important and basics of Google Cloud Platform Services. These services help users to load-balance traffic across resources, create DNS records, and connect their existing network to Google’s network. The types of networking services available are as follows:
3.1 Virtual Private Cloud (VPC)
It provides a set of networking services that are used by VM instances. It provides a private network with IP allocation, routing, and network firewall policies to create a secure environment for deployments. Every VPC project has a default network. Users can create additional networks in their projects, but networks cannot be shared between projects.
3.2 Cloud Load Balancing
It is a process of distributing workloads across many computing resources. Load balancing helps to scale applications according to user requirements, balance load of Compute machines resources in single or multiple regions. This reduces the cost of resources and maximizes availability.
It provides the following two options:
- Network Load Balancing
- HTTP (S) Load Balancing
Read more about Google Cloud Load Balancing.
3.3 Cloud DNS (Domain Naming System)
Cloud DNS is a scalable, reliable, and managed authoritative DNS service running on the same infrastructure as Google. It translates requests for domain names into IP addresses and offers a UI, command-line interface, and API for publishing and managing numerous DNS zones and resource records. It has low latency, high availability, and is cost-efficient.
3.4 Cloud CDN (Content Delivery Network)
CDN is a geographically distributed network that consists of proxy servers and their data centers. The network uses Google’s globally distributed edge caches to speed up content delivery for websites and applications served from Google Compute Engine.
3.5 Google Cloud Interconnect
Cloud Interconnect allows Cloud platform customers to connect to Google via enterprise-grade connections with higher availability and lower latency than their existing Internet connections.
4.) Big Data Services ^
Big data services enable users to process and query big data in the cloud to get fast solutions to complicated queries. Google Cloud platform offers various bigdata services like:
4.1 BigQuery
It is a fully managed data analysis service that enables users to:
- create custom schemas to organize data into tables and datasets.
- load data from different sources
- use SQL like commands to query large data
- make use of web UI, command-line interface, or API
- manage and protect data
4.2 Cloud Dataflow
Cloud Dataflow provides a set of managed services and a set of SDKs that can be used to perform batch and streaming data processing tasks. It works well for high-volume computation, especially when the processing tasks can easily be divided into parallel workloads. It is also great for extract-transform-load (ETL) tasks.
4.3 Google Cloud Pub/Sub
It is an asynchronous, serverless, large-scale, reliable real-time messaging service. Its usage is not just related to big data but could also be used to coordinate the App engine and Compute engine.
4.4 Cloud Dataproc
It is a managed Spark and Hadoop service used to process big datasets using the powerful and open tools in the Apache big data ecosystem.
4.5 Cloud Datalab
Cloud Datalab is an interactive Jupyter like notebook used to explore, collaborate, analyze, and visualize data. It is integrated with BigQuery and Google Cloud Machine Learning to provide easy access to key data processing services.
5.) Machine Learning Services ^
AI Platform offers a variety of machine learning (ML) services. Users can select APIs that provide pre-trained models optimized for specific applications, or build and train large-scale models using a managed TensorFlow framework. Google Cloud offers a variety of APIs that enable users to take advantage of Google’s ML without creating and training their own models.
5.1 Cloud Machine Learning
It is a managed service that enables users to build Machine Learning models based on mainstream frameworks like TensorFlow.
5.2 Cloud AutoML
Cloud AutoML is a Machine Learning product that enables developers who are not that experienced in this field to provide train their high-quality models by Google’s transfer learning and Neural Architecture Search.
5.3 Cloud Vision API
It is a REST API used for image recognition and classification. It allows users to integrate vision detection features, including image labeling, face and landmark detection, optical character recognition (OCR), etc.
5.4 Cloud Speech API
It is a REST API that can be used to convert audio to text recognizing over 110 languages and variants, to support customer’s global user base.
5.5 Cloud Natural Language API
It allows users to add sentiment analysis, entity analysis, entity-sentiment analysis, content classification, and syntax analysis.
5.6 Translate API
It allows the users to quickly translate source text into any of over a hundred supported languages. Language detection helps out in cases when the source language is unknown.
6.) Identity And Security Services ^
Identity and Security are one of the most important Google Cloud Services, knowing that data is safe and is encrypted.
6.1 Google Cloud IAM
Cloud Identity and Access Management (IAM) can be defined as a framework of policies and technologies for ensuring that authorized people in an enterprise have the appropriate access to technology and resources.
6.2 Cloud Resource Manager
This service is used for programmatically managing resource containers used for grouping and hierarchically organizing GCP resources.
6.3 Cloud Security Scanner
It is a web security scanner for common vulnerabilities in App Engine applications, like cross-site-scripting (XSS), Flash injection, mixed content, and outdated or insecure libraries.
Check Out: Google Cloud Run Pricing. Click here
7.) Management And Developer Tools ^
Management and developer tools are used by developers and development teams to be productive when writing, deploying, monitoring, and debugging applications hosted in Google Cloud.
Some of the tools are:
7.1 Stackdriver
Google Stackdriver delivers real-time monitoring, logging, and diagnostics across GCP. It provides metrics, dashboards, alerting, reporting, and tracing capabilities.
7.2 Console App
It is a native mobile application that enables customers to manage the key Google Cloud services and provides monitoring, altering, and the ability to take actions on resources.
7.3 Google Cloud SDK
It manages Google Cloud resources and applications with command-line tools and libraries. The Cloud SDK contains gcloud, gsutil, and bq command-line tools, which can be used to access Compute Engine, BigQuery, and more.
7.4 Cloud Deployment Manager
It is used for creating and managing cloud resources with simple templates. It Specifies all the resources needed for applications in a declarative format using YAML.
So this was all about the services and tools offered by Google Cloud Platform to build applications and perform tasks.
Create Google Cloud Free-Trial Account
Google Cloud Platform (GCP) is providing 90 days of Free Trial account with $300 credits to new subscribers to get hands-on experience with all the Google cloud services. So you can create your free trial account and get started with Google Cloud Learning.
You can check our blog for the steps to create your Google Cloud Account.
Frequently Asked Questions
What tools come with the Google Cloud SDK?
The Cloud SDK contains gcloud, gsutil, and bq command-line tools which can be used to access different services like BigQuery, Compute Engine, etc.
What database does Google Cloud use?
Google Cloud uses Cloud SQL which is a managed service that allows users to create, configure, use, and administer relational MySQL and PostgreSQL databases in the cloud.
What are serverless services in GCP?
Serverless services enables users to build, develop, deploy functions and applications as source code and removing the infrastructure management role.
What is the difference between Compute Engine and App Engine?
Compute Engine is an IaaS offering where the users have to create and configure their own virtual machine instances whereas App Engine is a PaaS offering where users have to deploy their code and everything else is handled by the platform.
Related References
- GCP Associate Cloud Engineer: All You Need To Know About
- GCP Professional Cloud Architect: Everything You Need To Know
- Introduction To Google Cloud Platform
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If you are also interested and want to know more about the Google Professional Cloud Architect certification then register for our Free Class.
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