Alicloud or Alibaba Cloud, Advantages and Speed

Alicloud or Alibaba Cloud, Advantages and Speed

Alicloud or Alibaba Cloud The biggest cloud provider in China

Alicloud or Alibaba Cloud (Mandarin: 阿里 云; pinyin: Ālǐyún; lit.: ‘Ali Cloud’), also known as Aliyun, is a Chinese cloud computing company, a subsidiary of Alibaba Group. Alibaba Cloud Computing was founded on September 10, 2009, with the mission of building an advanced data-centric cloud computing service company and an Internet data-sharing platform. The company attracts top technical talent both domestically and internationally and is committed to innovating in technology in the field of the Internet and e-commerce based on Alibaba Group’s experience in the e-business sector.

Alicloud Or Alibaba Cloud, Advantages And Speed
Alicloud Or Alibaba Cloud, Advantages And Speed

World-class technology will help Alibaba become the most influential Internet company and the largest e-commerce service provider in the world and will bring new experiences on the internet and e-commerce for the future.

Alibaba Cloud provides cloud computing services for online businesses and Alibaba’s e-commerce ecosystem. Alibaba Cloud’s international operations are registered and headquartered in Singapore. As in August 2019, the company announced to change the name of Alibaba Cloud to Alibaba Cloud Intelligence.

Alibaba Cloud offers cloud services. Services are available on a pay basis when you travel and include Elastic Calculation, Data Storage, Relational Database, Large Data Processing, Anti-DDoS protection, and Content Delivery Networks (CDN).

Beyond the status as the largest cloud computing company in China, Alibaba Cloud operates in 21 data center regions and 63 availability zones worldwide. In June 2017, Alibaba Cloud was placed in the Visionary quadrant of the Magic Quadrant Gartner for Cloud Infrastructure as a Service, Worldwide.

Jack Ma
CO-FOUNDER, ALIBABA GROUP

“Help young people. Help small guys. Because small guys will be big. Young people will have the seeds you bury in their minds, and when they grow up, they will change the world.”

History of Alicloud / Alibaba Cloud

1. September 2009 – Alibaba Cloud is established and R&D centers and subsequent operations centers are opened in Hangzhou, Beijing, and Silicon Valley.

2. November 2010 – Supporting the first Single Day (11.11) of the Taobao shopping festival, with 2.4 billion PV in 24 hours.

3. November 2012 – Becoming the first Chinese cloud service provider to pass ISO27001: 2005 (Information Security Management System).

4. January 2013 – Merged with HiChina for business www.net.cn.

5. August 2013 – ApsaraDB architecture supports 5000 physical machines in one cluster.

6. December 2014 – Defends DDoS attacks for 14 hours, peaking at 453.8Gbit / s.

7. May 2014 – Hong Kong data center online.

8. October 2015 – Two US data centers online.

9. July 2015 – The Alibaba Group is investing the further US $ 1 billion in Alibaba Cloud.

10. August 2015 – Singapore’s first Alibaba Cloud data center opens. Singapore was announced as Alibaba Cloud’s overseas headquarters.

11. October 2015 – MaxCompute leads the Sortch Benchmark, sorting 100TB of data in 377 compared to previous Apache Spark records of 1406s.

12. October 2015 – Alibaba Cloud Computing Conference was held in Hangzhou and attracted more than 20,000 developers.

13. November 2015 – Supports the 11.11 shopping festival with a record transaction of $ 14.2 billion in 24 hours.
April 2016 – Alibaba Cloud partners with SK Holdings C&C to provide cloud services for Korean and Chinese companies.

14. May 2016 – Alibaba Group and SoftBank formalize joint venture to launch cloud services in Japan that utilize technology and solutions from Alibaba Cloud.

15. June 2016 – Alibaba Cloud expands data center operations in Singapore with the establishment of a second availability zone. Alibaba Cloud also won two new overseas certifications: the Singapore Multi-Tier Cloud Security (MTCS) Level 3 standard, and the Payment Card Industry Data Security Standard (PCI-DSS).

16. November 2016 – Alibaba Cloud partners with Vodafone Germany for Data Center operations and to provide cloud services for German and European companies.

17. January 2017 – Alibaba becomes the official Olympic cloud service provider.

18. June 2017 – Alibaba Cloud is placed in the Visionary quadrant of the Gartner Magic Quadrant for Cloud Infrastructure as a Service, Worldwide.

19. July 2017 – The official website of Alibaba Cloud was changed from intl.aliyun.com to www.alibabacloud.com. September 2017 – Alibaba Cloud partners with Fusionex Malaysia to provide cloud solutions in Southeast Asia.

20. October 2017 – Alibaba Cloud partners with Elastic and launches a new service called Alibaba Cloud Elasticsearch.

21. October 2017 – Alibaba Cloud Malaysia data center begins operations.

22. December 2017 – Alibaba Cloud India data center begins operations.

23. December 2017 – Alibaba Cloud received C5 standard certification from the German Federal Office for Information Security (BSI) for data centers in Germany and Singapore.

24. February 2018 – Alibaba Cloud Indonesia’s data center begins operations.

Advantages of using Alibaba Cloud:

1. Cloud without restrictions

Reduce latency and apply globally on the Alibaba Cloud international network of 14 data centers and manage all regions through one global account.

2. The biggest cloud provider in China

The largest cloud network access in China, including 6 deployment areas and several Availability Zones in each region.

3. Protection of your data

As a company registered in Indonesia, Alibaba Cloud adheres to high-level international certification to ensure data security.

4. Performance record-breaker

Alibaba Cloud has broken records in data sorting technology, anti-DDoS protection, and transaction processing per second.

Google Compute Engine History And Pricing

Google Compute Engine History And Pricing

Get to know more about Google Compute Engine

Google Compute Engine (GCE) is an infrastructure component that is included as a Service from the Google Cloud Platform built on a Global infrastructure that runs Google Search, Gmail, YouTube, and other services. Google Compute Engine allows users to launch virtual machines on demand.

Virtual machines can be launched from standard images or special images created by users. Google Compute Engine users must be authenticated based on OAuth 2.0 before launching a Virtual Machine. Google Compute Engine can be accessed through the Developer Console, REST (Representational State Transfer), or command-line interface.

Google Compute Engine History And Pricing
Google Compute Engine History And Pricing

History Google Compute Engine

Google announced Compute Engine on June 28, 2012, on Google I / O in limited preview mode. In April 2013, Google Compute Engine was available to customers with a Gold Support Package. On February 25, 2013, Google announced that RightScale was its first retailer.

During Google, I / O input 2013, many features including sub-hour billing, shared core sample types, greater persistent storage, improved network-based software-determined network capabilities, and ISO / IEC 27001 certification were announced.

Google Compute Engine is available to everyone on May 15, 2013. Layer 3 balancing the computation load comes to Google Compute Engine on August 7, 2013. Finally, on December 2, 2013, Google announced that Google Compute Engine is generally available. This also extends system support operation, allows direct migration of Virtual Machines, for example, 16-core, faster storage, and lower standard prices.

At the Google Cloud Platform Live event on March 25, 2014. According to Urs Hölzle, Senior Vice President for technical infrastructure announced a continuous use discount, support for Microsoft Windows Server 2008, Cloud Design Naming System and Cloud Deployment Manager. On May 28, 2014, Google announced an optimization along with the dynamic scheduling of containers throughout the Virtual Engine.

Every Google Compute Engine process begins with a source storage called persistent disk. Persistent disks provide storage space for agencies that contain the root system file. Persistent storage can be used as a block of raw devices.

Google Compute Engine uses a small computer system interface to install persistent disks. Disk Persistent provides extensive, consistent, and reliable storage at a consistent and reliable price, eliminating the need for separate local disks. A persistent disk needs to be created before launching the example.

Once attached to an example, they can be formatted with the original submission system. One persistent disk can be attached to several instances in reading the only mode. Each persistent disk can reach 10TB. Google Compute Engine encrypts persistent disks with the Advanced Encryption Standard, and this encryption is implemented before the data leaves the virtual machine monitor and touches the disk. Encryption is always enabled and transparent for Google Compute Engine users. Persistent disk integrity is maintained through a message-based authentication code scheme.

On June 18, 2014, Google announced support for SSD persistent disks. This disk gives up to 30 IOPS per GB which is 20 times more IOPS writing and 100x more IOPS reading than a standard persistent disk.

All pricing Google Compute Engine

Google Compute Engine prices may change, always check the latest prices HERE

Machine Type Machine name Core Virtual Memory Hourly Fees (US hosted) Hourly Fee (Europe hosted)
Standard n1-standard-1 1 3.75GB $ 0.070 $ 0.077
Standard n1-standard-2 2 7.5GB $ 0.140 $ 0.154
Standard n1-standard-4 4 15GB $ 0.280 $ 0.308
Standard n1-standard-8 8 30GB $ 0.560 $ 0.616
Standard n1-standard-16 16 60GB $ 1.120 $ 1.232
High Memory n1-highmem-2 2 13GB $ 0.164 $ 0.180
High Memory n1-highmem-4 4 26GB $ 0.328 $ 0.360
High Memory n1-highmem-8 8 52GB $ 0.656 $ 0.720
High Memory n1-highmem-16 16 104GB $ 1.312 $ 1.440
High CPU n1-highcpu-2 2 1.80GB $ 0.088 $ 0.096
High CPU n1-highcpu-4 4 3.60GB $ 0.176 $ 0.192
High CPU n1-highcpu-8 8 7.20GB $ 0.352 $ 0.384
High CPU n1-highcpu-16 16 14.40GB $ 0.704 $ 0.768
Shared Core f1-micro 1 0.60GB $ 0.013 $ 0.014
Shared Core g1-small 1 1.70GB $ 0.035 $ 0.0385
Memory-optimized n1-ultramem-40 40 938GB $ 6.3039 $ 6.9389
Memory-optimized n1-ultramem-80 80 1922GB $ 12.6078 $ 13.8779
Memory-optimized n1-megamem-96 96 1433.6GB $ 10.6740 $ 11.7430
Memory-optimized n1-ultramem-160 160 3844GB $ 25.2156 $ 27.7557

Get To Know Google Pub-Sub And Its Message Queue

Get To Know Google Pub-Sub And Its Message Queue

Cloud Pub / Sub

Global messaging and easier absorption of events. Absorbing events on all scales Data absorption is the foundation for analysis and machine learning, whether you are creating integrated streams, batches, or pipelines. Google cloud Pub-Sub / Sub provides a simple and reliable staging location for your event data for processing, storage, and analysis purposes.

Get To Know Google Pub Sub And Its Message Queue
Get To Know Google Pub Sub And Its Message Queue

With Cloud Pub / Sub, data engineers can:

1. Scale by providing, creating partitions, or isolating loads without worry
2. Easily expand your application and pipeline to new regions with global topics
3. Enrich, delete duplicates, sort, merge, and place events using Cloud Dataflow
4. Combining real-time processing and batch processing through durable Cloud Pub / Sub storage

Simplify the development of event-controlled microservices

Whether you’re just starting an asynchronous event-driven microservice activity or migrating an existing system, making events accessible via messaging middleware is an important first step. Application developers at GCP rely on Cloud Pub / Sub to send each event reliably to all services that will respond to it.

After publishing events to Cloud Pub / Sub:

1. A push subscription sends events to applications without a server running on Cloud Functions, App Engine or Cloud Run
2. Pull subscriptions provide it to more complex stateful services that run on Google Kubernetes Engine or Cloud Dataflow
3. The multi-region environment operates smoothly thanks to the global Cloud Pub / Sub

Be ready for production from day one

Cloud Pub / Sub is designed as a premium service that allows Google Cloud users to focus on application logic, regardless of location or scale. This service is very minimal and easy to start, but it also eliminates operational, scaling, compliance, and security shocks that are revealed in the software project themselves.

That is why Cloud Pub / Sub includes the following active features:

1. Comprehensive encryption, IAM, and audit logging
2. Scaling and supplying fully automatic and without operation with almost unlimited throughput
3. Extreme data security and availability with synchronized cross-zone replication
4. The native client library in several major languages ​​and open service APIs

Cloud Pub Sub For Global Messaging And Event Absorption
Cloud Pub Sub For Global Messaging And Event Absorption

Cloud Pub / Sub features

1. Delivery of at least one time

Synchronous cross-zone message replication and receipt tracking per message ensure delivery at least once on all scales.

2. Open it

Open client APIs and libraries in seven languages ​​support cross-cloud and hybrid deployments.

3. Processing exactly once

Cloud Dataflow supports reliable, expressive, and one-time processing of Cloud Pub / Sub streams.

4. Global by default

Publish from anywhere in the world and use from anywhere, with consistent latency. No replication needed.

5. Without the provision, everything is done automatically

Cloud Pub / Sub has no shards or partitions. Just set your quota, publish, and use.

6. Compliance and safety

Cloud Pub / Sub is a service that complies with HIPAA provisions and offers very detailed access control and full encryption.

7. Integrated

Take advantage of integration with several services, such as cloud storage and Gmail update events, and Cloud Functions for event-controlled, server-free computing.

8. Search and replay

Rewind your backlog to any point in time or snapshot, giving it the ability to reprocess messages. Play fast forward to get rid of obsolete data.

Cloud Pub / Sub prices

The more you use Cloud Pub / Sub, the cheaper the price will be. No upfront costs and no fees for creating or managing topics or subscriptions.

Monthly data volume 1 Price per TB 2
First 10 GB $ 0.00
Next 50 TB $ 60
Next 100 TB $ 50
Above 150 TB $ 40

Google Cloud Pub / Sub is a message queue service that allows systems to share data with other systems in real-time. To do this, the following things are needed.

1. First is Topic, which is a feed where data will be published
2. Second is Publisher, the process of publishing data to a topic, and
3. Finally, a Subscriber is a system that will receive data from topics sent from the publisher.

Google Cloud Platform products used are Google Cloud Shell is a shell environment, Google Cloud Pub / Sub as a messaging service, and Python as a Programming language.

Google Pub Sub As A Messaging Service, And Python As A Programming Language
Google Pub Sub As A Messaging Service, And Python As A Programming Language

Next is the system architecture that will be created. To do the above, do the following:

1. install the google cloud pub subpackage on the google cloud shell.

sudo pip install – upgrade google-cloud-pubsub

2. set GOOGLE_CLOUD_PROJECT variable environment.

export GLOBAL_CLOUD_PROJECT = <GCP-Project-ID>

3. Make a publisher.py file that contains.

This file contains methods for creating topics, topic lists, and publishing messages

1. Create a Pub / Sub Topic with the name of the song.

python publisher.py $ GLOBAL_CLOUD_PROJECT create a song

2. List topics to ensure topics have been created.

python publisher.py $ GLOBAL_CLOUD_PROJECT list

3. Create a file called subscriber.py to receive messages from the publisher.

In this script, there are methods to create a subscriber from a topic, subscriber list on a topic, and receive messages from a topic

1. Create a subscriber with the name subs_lagu to retrieve messages from the song topic.

python subscriber.py $ GLOBAL_CLOUD_PROJECT create song subs_song

2. List subscriber that receives from the song topic.

python subscriber.py $ GLOBAL_CLOUD_PROJECT list_in_topic song

3. Listen to messages from song topics and subscriber subs_lagu.

python subscriber.py $ GLOBAL_CLOUD_PROJECT receive subs_song

4. Add a session to the cloud shell.

5. Push message to the song topic by the publisher using the new session so that it does not terminate the session that is listening to the topic.

python publisher.py $ GLOBAL_CLOUD_PROJECT publish the song “upset night of the week”

6. Look at the session that is listening to the message from the song topic. Then it will produce output like this.

Demo of a program that has been created.

Google Datalab Exploration, Analysis, Data Visualization, and Machine Learning

Google Datalab Exploration, Analysis, Data Visualization, and Machine Learning

Google Datalab Exploration

An interactive tool that is easy to use for exploration, analysis, data visualization, and machine learning.

Google today launched Cloud Datalab. Cloud Datalab is an interactive and reliable tool created to explore, analyze, transform, and visualize data and create machine learning models on the Google Cloud Platform. This tool can run on Compute Engine and easily connect to many cloud services so you can focus on your data science tasks.

Google Datalab Exploration, Analysis, Data Visualization, And Machine Learning
Google Datalab Exploration, Analysis, Data Visualization, And Machine Learning

This service uses a Jupyter notebook (formerly known as IPython), a format that allows you to create documents with direct code and visualization. Jupyter is quite famous in the world of data science, and a growing ecosystem has developed around it, which should make this new Google tool easier too.

To get started, you must first use Cloud Datalab as an App Engine application – and that’s where fees for using the service will enter after the free beta period (Google has not released pricing information). After completion, you can start a new project and prepare a new notebook; This service will come with several notebooks installed to help you get started.

What’s cool here is that Datalab is open source, and developers who want to extend it can only cut it and/or send pull requests on GitHub.

Integrated & open source

Cloud Datalab was built on Jupyter (formerly IPython), which has a thriving module ecosystem and a strong knowledge base. Cloud Datalab allows analysis of your data in BigQuery, Cloud Machine Learning Engine, Compute Engine, and Cloud Storage using Python, SQL, and JavaScript (for user-defined BigQuery functions).

Scalable

Whether you are analyzing data in megabytes or terabytes, Cloud Datalab can help you. Query terabytes of data in BigQuery, run a local analysis of sample data and run training tasks on terabytes of data in the Cloud Machine Learning Engine without problems.

Data management and visualization

Use Cloud Datalab to get information from your data. Explore, transform, analyze, and visualize your data interactively using BigQuery, Cloud Storage, and Python.

Machine learning with process cycle support

Departing from data to machine learning (ML) models that are deployed and ready for prediction. Explore data, create, evaluate, and optimize machine learning models using TensorFlow or Cloud Machine Learning Engine.

8 Google Datalab features that you should know about

Integrated

Cloud Datalab simplifies data processing with BigQuery Cloud, Cloud Machine Learning Engine, Cloud Storage, and Stackdriver Monitoring. Authentication, cloud computing, and source control have been handled since the initial use.

Multilingual support

Cloud Datalab currently supports Python, SQL, and JavaScript (for user-defined BigQuery functions).

Format the notebook

Cloud Datalab combines code, documentation, results, and visualizations into one in an intuitive notebook format.

Price per use

Simply pay for the cloud resources you use: VM Compute Engine, BigQuery, and other additional resources used, such as Cloud Storage.

Interactive data visualization

Use Google Charting or matplotlib to facilitate visualization.

Machine learning

Supports TensorFlow-based deep ML models in addition to sci-kit-learn. Scale training and predictions through a special library for the Cloud Machine Learning Engine.

IPython support

Datalab is based on Jupyter (formerly called IPython) so you can use many existing packages for statistics, machine learning, etc. Learn from published notebooks and exchange tips with the busy IPython community.

Open Source

Developers who want to expand Datalab can copy and / or submit pull requests to projects hosted on GitHub.

Cloud Datalab Pricing

There are no fees to use Google Cloud Datalab. However, you pay for any Google Cloud Platform resources you use with Datalab Cloud, for example:

Calculate resources:
You are charged from the time of creation until the removal of the Cloud Datalab VM virtual machine. The default Cloud Datalab VM machine type is n1-standard-1, but you can choose a different machine type. You are also charged for the 20GB Standard Persistent Disk, which is used as a Boot Disk, and the 200GB Standard Persistent Disk, where the user’s notebook is stored (see Storage resources). The 20GB boot disk is deleted when the VM instance is deleted, but the 200GB disk remains after the VM deletion until you delete it. The following command removes VM instances and 20GB boot disks and 200GB user notebook disks.

Storage resources: Notebooks are saved to Persistent Disk and are backed up to Google Cloud Storage (see Determination of persistent disk prices and Cloud Storage prices).

Data Analysis Services: You are charged with Google BigQuery fees when issuing SQL questions in the Cloud Datalab notebook (see BigQuery Prices). Additionally, when you use Google Cloud Machine Learning, you may be charged for Cloud Learning Machine and / or Google Cloud Dataflow.

Other resources: You may be charged for other API requests that you make in the Cloud Datalab notebook environment. This fee will vary according to the API.

If you are interested and want to do calculations, we provide Google Cloud Pricing Calculator

Getting Started with the Google Cloud Platform. The following video explanation

Get to know Google Cloud Server

Get to know Google Cloud Server

Get more done with Google Cloud

Google Cloud Platform, (or GCP) is a collection of cloud computing services offered by Google. GCP runs on the same infrastructure that is used by Google for its internal products, such as Google Search, YouTube, and Gmail. Along with a set of management tools, GCP provides a range of modular cloud services including computing, data storage, data analysis, and machine learning. Registration requires a credit card or bank account details.

Google Cloud Server
Google Cloud Server

Google’s cloud platform provides infrastructure services, platform services, and a server-free computing environment. In April 2008, Google announced an application engine, a platform for developing and hosting web applications in a data center managed by Google, which is the company’s first cloud computing service.

This service is generally available in November 2011. Since the announcement of the application engine, Google has added several platform services to the cloud. Google’s cloud platform is part of Google’s cloud, which includes Google’s cloud platform public cloud infrastructure, as well as, G Suite, enterprise versions of Android and Chrome, and application programming interfaces for machine learning and enterprise mapping services.

Why Choose Google Cloud

Google cloud server providing solutions is the most important thing, take advantage of it. Reducing risk with world-class security The same security technology that supports Google’s global private network protects your data while meeting stringent industry-specific compliance standards.

Trust and safety

Trust & Security, Google cloud server has a unique security model, world-scale infrastructure, and innovation capability to help your organization stay safe and compliant.

Cloud open

Why believe in an open cloud? Openness enables faster innovation, tighter security, and offers freedom from vendor lock-in. Google believes openness is more important in the cloud than ever before.

Open is about being able to retrieve and move your applications. Open Cloud is based on the belief that being bound to a particular cloud must not impede the achievement of your goals.

Open Cloud applies the idea that the ability to send your application to a different cloud while using the same operating and development approach will help you meet whatever your priorities are at any given time — whether it makes the most of the skills widely shared throughout your team or accelerates innovation.

Open source is an open cloud activator because open source in the cloud maintains your control over where your IT investment is deployed. For example, customers use Kubernetes to manage containers and TensorFlow to create machine learning models locally and in multiple clouds.

Product Document

What are the benefits of Google Cloud Server:

1. Modernize your workload on world-class infrastructure

Migrate quickly with pre-packaged cloud infrastructure solutions for SAP, VMware, Windows, Oracle, data center migration, and other corporate workloads.

2. Protect your data with multiple layers of security

Infrastructure designed for security protects your data, applications, and users with advanced threat detection and anti-malware.

3. Encourage decision making with intelligent analysis

Find actionable analysis results from your data, with a series of scalable solutions for a data warehouse, analysis, and AI and machine learning.

4. Implement hybrid and multi-cloud solutions without being tied to specific vendors

Create the application once and run it in a hybrid and multi-cloud environment with other cloud providers.

Here Google registered more than 90 products under the Google Cloud brand. Some of the main services are listed below.

Region and Zone

Google Cloud Platform is available in 17 regions and 52 zones. The region is a specific geographical location where users can use cloud resources. Each region is an independent geographical area consisting of zones.

A zone is an implementation area for Google Cloud Platform resources in a region. The zone must be considered as a single failure domain in an area. Most areas have three or more zones. Starting in September 2018, the Google Cloud Platform is available in the following regions and zones:

Region Name Location Zone
northamerica-northeast1 Montréal, Canada
  • northamerica-northeast1-a
  • northamerica-northeast1-b
  • northamerica-northeast1-c
us-central1 Council Bluffs, Iowa, USA
  • us-central1-a
  • us-central1-b
  • us-central1-c
  • us-central1-f
us-west1 The Dalles, Oregon, USA
  • us-west1-a
  • us-west1-b
  • us-west1-c
us-west2 Los Angeles, California, USA
  • us-west2-a
  • us-west2-b
  • us-west2-c
us-east4 Ashburn, Virginia, USA
  • us-east1-b
  • us-east1-c
  • us-east1-d
us-east1 Moncks Corner, South Carolina, USA
  • us-east1-b
  • us-east1-c
  • us-east1-d
southamerica-east1 São Paulo, Brazil
  • southamerica-east1-a
  • southamerica-east1-b
  • southamerica-east1-c
europe-north1 Hamina, Finland
  • europe-north1-a
  • europe-north1-b
  • europe-north1-c
europe-west1 St. Ghislain, Belgium
  • europe-west1-b
  • europe-west1-c
  • europe-west1-d
europe-west2 London, U.K.
  • europe-west2-a
  • europe-west2-b
  • europe-west2-c
europe-west3 Frankfurt, Germany
  • europe-west3-a
  • europe-west3-b
  • europe-west3-c
europe-west4 Eemshaven, Netherlands
  • europe-west4-a
  • europe-west4-b
  • europe-west4-c
asia-south1 Mumbai, India
  • asia-south1-a
  • asia-south1-b
  • asia-south1-c
asia-east1 Changhua County, Taiwan
  • asia-east1-a
  • asia-east1-b
  • asia-east1-c
asia-northeast1 Tokyo, Japan
  • asia-northeast1-a
  • asia-northeast1-b
  • asia-northeast1-c
asia-southheast1 Jurong West, Singapore
  • asia-southheast1-a
  • asia-southheast1-b
  • asia-southheast1-c
australia-southeast1 Sydney, Australia
  • australia-southeast1-a
  • australia-southeast1-b
  • australia-southeast1-c

The following regions are expected to operate in 2018:

– Zürich (Switzerland)
– Osaka (Japan)
– Hong Kong

The similarity to services by other cloud service providers

For those familiar with other leading cloud service providers, a comparison of similar services might be useful in understanding Google Cloud Platform offerings.

Google Cloud Platform Amazon Web Services Microsoft Azure Alibaba Cloud Oracle Cloud
Google Compute Engine Amazon EC2 Azure Virtual Machines Elastic Compute Service Oracle Cloud Infra OCI
Google App Engine AWS Elastic Beanstalk Azure Cloud Services Oracle Application Container
Google Kubernetes Engine Amazon Elastic Container Service

for Kubernetes

Azure Kubernetes Service ECS Bare Metal Instance Oracle Kubernetes Service
Google Cloud Bigtable Amazon DynamoDB Azure Cosmos DB
Google BigQuery Amazon Redshift Microsoft Azure SQL Database Oracle Autonomous DataWarehouse
Google Cloud Functions AWS Lambda Azure Functions Function Computes Oracle Cloud Fn
Google Cloud Datastore Amazon DynamoDB Cosmos DB
Google Cloud Storage Amazon S3 Azure Blob Storage Object Storage Service Oracle Cloud Storage OCI

Complete your toughest business challenges with google cloud server

As we have clear above we will complete several advantages that make you choose Google Cloud Server.

1. Modernize infrastructure

Modernize your cloud infrastructure and run critical workloads such as VMware, SAP, Oracle, and Windows natively on Google Cloud.

2. Data management and analysis

Encourage more analysis results that can be followed up with solutions for data management, data warehouse modernization, and predictive analysis.

3. Modernization of applications

Modernize old applications and create new services that utilize Kubernetes, containers, and other cloud-based capabilities.

4. Business application platform

Combine multiple business processes without obstacles and access new business channels by providing valuable data and services as APIs.

5. AI & machine learning

Include AI and ML in the work of people who are directly involved with your business, and increase efficiency in customer service, recruitment, and others.

6. Security

Detect, investigate, and respond to threats online with proven security solutions to help protect your business.

7. Productivity & collaboration

Work faster, smarter, and more collaborative with G Suite, a workplace productivity solution with applications such as Gmail, Docs, Drive, and Meet.

8. Media & entertainment

Create world-class content, simplify workflows, launch new digital services quickly, and transform audience experience.

9. Retail

Stay deft throughout the entire retail value chain, from store operations to merchandising and customer acquisition and retention.

10. Health services & life sciences

Personalize the patient experience, modernize research and development, and overcome severe challenges in the field of health services and life sciences.

11. Financial services

Manage risk, make decisions more timely, and stay competitive while maintaining compliance in the fast-changing financial markets.

12. Public sector

Help improve public services, increase operational effectiveness, and provide proven innovation in your government agency.

The next step

1. Start creating projects on Google Cloud with a free credit of $ 300 and 20+ products that are always free.

Get started for free

2. Let us know the problem you are having. Google experts will help you find the best solution.

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