End-user Experience Running Windows Applications on E2E Cloud

October 26, 2020

Any organization having diverse business operations requires applications that can lighten the workload. Hence, organizations need consistent availability of different enterprise applications. Most organizations are using Windows-server for their day-to-day operations. 

According to IDC, approximately 45% of servers that were shipped in 2019 globally were being run by Windows Operating System. This shows the possibility of a higher workload generated from Windows server-based applications across the world.  

One cloud provider that is India’s very own is E2E Cloud. This cloud provider is gaining more and more appreciation from the end-users due to its reliability, low-cost, scalability, and enhanced security features while running the Windows-based applications. 

In this article, we’ll have a closer look at the experiences of the E2E cloud platform's end-users. We also discuss end users' opinions and why they think the E2E Cloud is thoroughly optimized to handle the workload generated from the Windows server based applications.  

Why do Some Users Hesitate to Switch to a Cloud? 

There are two key types of workload suited for Windows server that you must know about. Any enterprise application built with .NET framework and any database application built with an SQL server falls under this category. There’s one thing common for both these applications. They deeply rely on the infrastructure frameworks for rapid performance, more robust security protection, and proper availability. 

Another thing common about these applications is that they’re designed with a group of tightly coupled components. Let’s take the example of applications created with Model View Controller (MDC). For this design pattern, one can easily notice how components like controller and database backend and view and model are vigorously tied with each other. 

If the example of Windows Server-based enterprise applications is taken, one can observe that the SQL server-based database is dependent on the storage cluster. This is done to ensure that availability is high and there’s proper data control. In fact, in that case, one can have a tough time considering the storage cluster's complex set-up. Many organizations hesitate to move all their information and databases to the cloud platform due to these complexities. 

E2E Cloud is a smart choice for users who want to avoid unnecessary complexities. There are many features of E2E Cloud that make it the most fitting Cloud provider for running Windows applications. Here are a few reasons why many end-users are giving positive feedback to E2E Cloud. 

E2E Cloud Comes with High Scalability and Continuous Data Protection Feature

Scalability is often in great demand among many start-ups as they’re constantly in need of upgrading the infrastructure if the demand increased. So, for them, the E2E cloud is perfect as it can offer the users scaling up in their operations. Further, the E2E network comes with a self-service portal so there is no need to wait for when somebody will help you out. Customers prefer that all resources are readily available at one place, and they can access necessary resources whenever they need. This has boosted the customers’ appreciation level to the highest degree.

Customers also prefer E2E network because of its continuous data protection service. In situations of disaster, E2E has helped its users with easy data recovery. Customers who were fond of data centers previously have explained that they could never avail similar facilities with their other data centers. The data recovery feature is a major reason why so many users are switching to the E2E Cloud.

The users also prefer why E2E offers them limitless back-up options. That’s a bonus for them.

Easy Deployment and Customer-centric Solutions

Customers prefer using the E2E Cloud because of its simple and fast deployment process. You must know that you can deploy several ready to use images with pre-installed scripts with a single click. Most customers are satisfied with this feature because they don’t have to be tech professional to handle E2E cloud. The user interface is responsive, and every feature is just a click away. This makes E2E a great choice among the users.

Customers’ needs and preferences is another major reason why so many users are trusting E2E cloud. E2E tries to understand the requirements of different users and accordingly, this brand offers different services. The level of customization and different types of series offered by E2E is a major reason why customers appreciate this brand.

Great Accessibility and Strong Security

When customers are opting for a cloud, they are looking for best possible accessibility. With the E2E Cloud, availing such features are possible. One of the major reasons why customers are getting tempted by the E2E Cloud is the options for accessing necessary datasets from anywhere and everywhere.

People also prefer E2E cloud because of its strong security features. E2E has a strong security policy. 

E2E Cloud is a Great Option for Modernization 

Most users believe that to modernize their workflows based on Windows; nothing can be a better alternative than E2E Cloud. This shows that most E2E Cloud users are satisfied and believe that migrating all enterprise applications to E2E Cloud is a good idea.

From insight into the users' opinions, it is understandable that most users are inclined towards Cloud Technology because of the modern and convenient features it offers and the swift migration functions it provides. Some users are even planning to switch off Windows permanently by replacing the Windows applications with Linux-based applications.

The Technical Potential of E2E Cloud are Top-notch

Enterprise end-users are also looking for an alternative with greater technology potential and E2E Cloud fill this gap. The E2E Cloud technology is recognized as technologically inclined. This is a decision-making factor for most end-users. 

End-users who were previously accustomed to an on-premise server also have many features to look forward to with E2E Cloud. With E2E Cloud, end-users can easily choose VM sizes without affecting the cost-performance metrics of the end-users. 

With E2E Cloud, sanctioning and installing the Microsoft Active Directory is also simpler.  

Optimising Costs is also Possible with E2E Cloud

Cost optimization is also a significant decision-making factor for small and large enterprises.

Nevertheless, E2E Cloud customers are content with features like reserved IP,  E2E Cloud API. The strategic application of these features can assist with cost control. The Windows Server 2016 can be run powerfully within the E2E Cloud network, an entire SSD platform. Users have already observed how E2E Cloud offers spectacular pricing packages and provides several opportunities to control costs. 

10 available plans are ranging in the price bracket of INR 3 per hour to INR 108 per hour. The users select their desired options based on the requirements and the relevant prices. 

Final Words 

While concluding, it is important to note that E2E Cloud is indeed a desired choice for most respondents. As most enterprise personnel are switching towards a cloud framework for Windows, the E2E Cloud network can be a smart choice for them. 

E2E Cloud network can be easily identified as a customer-centric option that eases the workload generated from Windows applications. The E2E Cloud infrastructure is recognized as a simple cloud infrastructure that can be operated by anyone. They can now switch to the cloud with the least challenges involved. 

For free trial please click here :- http://bit.ly/3hyNiWB

Latest Blogs
This is a decorative image for Project Management for AI-ML-DL Projects
June 29, 2022

Project Management for AI-ML-DL Projects

Managing a project properly is one of the factors behind its completion and subsequent success. The same can be said for any artificial intelligence (AI)/machine learning (ML)/deep learning (DL) project. Moreover, efficient management in this segment holds even more prominence as it requires continuous testing before delivering the final product.

An efficient project manager will ensure that there is ample time from the concept to the final product so that a client’s requirements are met without any delays and issues.

How is Project Management Done For AI, ML or DL Projects?

As already established, efficient project management is of great importance in AI/ML/DL projects. So, if you are planning to move into this field as a professional, here are some tips –

  • Identifying the problem-

The first step toward managing an AI project is the identification of the problem. What are we trying to solve or what outcome do we desire? AI is a means to receive the outcome that we desire. Multiple solutions are chosen on which AI solutions are built.

  • Testing whether the solution matches the problem-

After the problem has been identified, then testing the solution is done. We try to find out whether we have chosen the right solution for the problem. At this stage, we can ideally understand how to begin with an artificial intelligence or machine learning or deep learning project. We also need to understand whether customers will pay for this solution to the problem.

AI and ML engineers test this problem-solution fit through various techniques such as the traditional lean approach or the product design sprint. These techniques help us by analysing the solution within the deadline easily.

  • Preparing the data and managing it-

If you have a stable customer base for your AI, ML or DL solutions, then begin the project by collecting data and managing it. We begin by segregating the available data into unstructured and structured forms. It is easy to do the division of data in small and medium companies. It is because the amount of data is less. However, other players who own big businesses have large amounts of data to work on. Data engineers use all the tools and techniques to organise and clean up the data.

  • Choosing the algorithm for the problem-

To keep the blog simple, we will try not to mention the technical side of AI algorithms in the content here. There are different types of algorithms which depend on the type of machine learning technique we employ. If it is the supervised learning model, then the classification helps us in labelling the project and the regression helps us predict the quantity. A data engineer can choose from any of the popular algorithms like the Naïve Bayes classification or the random forest algorithm. If the unsupervised learning model is used, then clustering algorithms are used.

  • Training the algorithm-

For training algorithms, one needs to use various AI techniques, which are done through software developed by programmers. While most of the job is done in Python, nowadays, JavaScript, Java, C++ and Julia are also used. So, a developmental team is set up at this stage. These developers make a minimum threshold that is able to generate the necessary statistics to train the algorithm.  

  • Deployment of the project-

After the project is completed, then we come to its deployment. It can either be deployed on a local server or the Cloud. So, data engineers see if the local GPU or the Cloud GPU are in order. And, then they deploy the code along with the required dashboard to view the analytics.

Final Words-

To sum it up, this is a generic overview of how a project management system should work for AI/ML/DL projects. However, a point to keep in mind here is that this is not a universal process. The particulars will alter according to a specific project. 

Reference Links:

https://www.datacamp.com/blog/how-to-manage-ai-projects-effectively

https://appinventiv.com/blog/ai-project-management/#:~:text=There%20are%20six%20steps%20that,product%20on%20the%20right%20platform.

https://www.datascience-pm.com/manage-ai-projects/

https://community.pmi.org/blog-post/70065/how-can-i-manage-complex-ai-projects-#_=_

This is a decorative image for Top 7 AI & ML start-ups in Telecom Industry in India
June 29, 2022

Top 7 AI & ML start-ups in Telecom Industry in India

With the multiple technological advancements witnessed by India as a country in the last few years, deep learning, machine learning and artificial intelligence have come across as futuristic technologies that will lead to the improved management of data hungry workloads.

 

The availability of artificial intelligence and machine learning in almost all industries today, including the telecom industry in India, has helped change the way of operational management for many existing businesses and startups that are the exclusive service providers in India.

 

In addition to that, the awareness and popularity of cloud GPU servers or other GPU cloud computing mediums have encouraged AI and ML startups in the telecom industry in India to take up their efficiency a notch higher by combining these technologies with cloud computing GPU. Let us look into the 7 AI and ML startups in the telecom industry in India 2022 below.

 

Top AI and ML Startups in Telecom Industry 

With 5G being the top priority for the majority of companies in the telecom industry in India, the importance of providing network affordability for everyone around the country has become the sole mission. Technologies like artificial intelligence and machine learning are the key digital transformation techniques that can change the way networks rotates in the country. The top startups include the following:

Wiom

Founded in 2021, Wiom is a telecom startup using various technologies like deep learning and artificial intelligence to create a blockchain-based working model for internet delivery. It is an affordable scalable model that might incorporate GPU cloud servers in the future when data flow increases. 

TechVantage

As one of the companies that are strongly driven by data and unique state-of-the-art solutions for revenue generation and cost optimization, TechVantage is a startup in the telecom industry that betters the user experiences for leading telecom heroes with improved media generation and reach, using GPU cloud online

Manthan

As one of the strongest performers is the customer analytics solutions, Manthan is a supporting startup in India in the telecom industry. It is an almost business assistant that can help with leveraging deep analytics for improved efficiency. For denser database management, NVIDIA A100 80 GB is one of their top choices. 

NetraDyne

Just as NVIDIA is known as a top GPU cloud provider, NetraDyne can be named as a telecom startup, even if not directly. It aims to use artificial intelligence and machine learning to increase road safety which is also a key concern for the telecom providers, for their field team. It assists with fleet management. 

KeyPoint Tech

This AI- and ML-driven startup is all set to combine various technologies to provide improved technology solutions for all devices and platforms. At present, they do not use any available cloud GPU servers but expect to experiment with GPU cloud computing in the future when data inflow increases.

 

Helpshift

Actively known to resolve customer communication, it is also considered to be a startup in the telecom industry as it facilitates better communication among customers for increased engagement and satisfaction. 

Facilio

An AI startup in Chennai, Facilio is a facility operation and maintenance solution that aims to improve the machine efficiency needed for network tower management, buildings, machines, etc.

 

In conclusion, the telecom industry in India is actively looking to improve the services provided to customers to ensure maximum customer satisfaction. From top-class networking solutions to better management of increasing databases using GPU cloud or other GPU online services to manage data hungry workloads efficiently, AI and MI-enabled solutions have taken the telecom industry by storm. Moreover, with the introduction of artificial intelligence and machine learning in this industry, the scope of innovation and improvement is higher than ever before.

 

 

References

https://www.inventiva.co.in/trends/telecom-startup-funding-inr-30-crore/

https://www.mygreatlearning.com/blog/top-ai-startups-in-india/

This is a decorative image for Top 7 AI Startups in Education Industry
June 29, 2022

Top 7 AI Startups in Education Industry

The evolution of the global education system is an interesting thing to watch. The way this whole sector has transformed in the past decade can make a great case study on how modern technology like artificial intelligence (AI) makes a tangible difference in human life. 

In this evolution, edtech startups have played a pivotal role. And, in this write-up, you will get a chance to learn about some of them. So, read on to explore more.

Top AI Startups in the Education Industry-

Following is a list of education startups that are making a difference in the way this sector is transforming –

  1. Miko

Miko started its operations in 2015 in Mumbai, Maharashtra. Miko has made a companion for children. This companion is a bot which is powered by AI technology. The bot is able to perform an array of functions like talking, responding, educating, providing entertainment, and also understanding a child’s requirements. Additionally, the bot can answer what the child asks. It can also carry out a guided discussion for clarifying any topic to the child. Miko bots are integrated with a companion app which allows parents to control them through their Android and iOS devices. 

  1. iNurture

iNurture was founded in 2005 in Bengaluru, Karnataka. It provides universities assistance with job-oriented UG and PG courses. It offers courses in IT, innovation, marketing leadership, business analytics, financial services, design and new media, and design. One of its popular products is KRACKiN. It is an AI-powered platform which engages students and provides employment with career guidance. 

  1. Verzeo

Verzeo started its operations in 2018 in Bengaluru, Karnataka. It is a platform based on AI and ML. It provides academic programmes involving multi-disciplinary learning that can later culminate in getting an internship. These programmes are in subjects like artificial intelligence, machine learning, digital marketing and robotics.

  1. EnglishEdge 

EnglishEdge was founded in Noida in 2012. EnglishEdge provides courses driven by AI for getting skilled in English. There are several programmes to polish your English skills through courses provided online like professional edge, conversation edge, grammar edge and professional edge. There is also a portable lab for schools using smart classes for teaching the language. 

  1. CollPoll

CollPoll was founded in 2013 in Bengaluru, Karnataka. The platform is mobile- and web-based. CollPoll helps in managing educational institutions. It helps in the management of admission, curriculum, timetable, placement, fees and other features. College or university administrators, faculty and students can share opinions, ideas and information on a central server from their Android and iOS phones.

  1. Thinkster

Thinkster was founded in 2010 in Bengaluru, Karnataka. Thinkster is a program for learning mathematics and it is based on AI. The program is specifically focused on teaching mathematics to K-12 students. Students get a personalised experience as classes are conducted in a one-on-one session with the tutors of mathematics. Teachers can give scores for daily worksheets along with personalised comments for the improvement of students. The platform uses AI to analyse students’ performance. You can access the app through Android and iOS devices.

  1. ByteLearn 

ByteLearn was founded in Noida in 2020. ByteLean is an assistant driven by artificial intelligence which helps mathematics teachers and other coaches to tutor students on its platform. It provides students attention in one-on-one sessions. ByteLearn also helps students with personalised practice sessions.

Key Highlights

  • High demand for AI-powered personalised education, adaptive learning and task automation is steering the market.
  • Several AI segments such as speech and image recognition, machine learning algorithms and natural language processing can radically enhance the learning system with automatic performance assessment, 24x7 tutoring and support and personalised lessons.
  • As per the market reports of P&S Intelligence, the worldwide AI in the education industry has a valuation of $1.1 billion as of 2019.
  • In 2030, it is projected to attain $25.7 billion, indicating a 32.9% CAGR from 2020 to 2030.

Bottom Line

Rising reliability on smart devices, huge spending on AI technologies and edtech and highly developed learning infrastructure are the primary contributors to the growth education sector has witnessed recently. Notably, artificial intelligence in the education sector will expand drastically. However, certain unmapped areas require innovations.

With experienced well-coordinated teams and engaging ideas, AI education startups can achieve great success.

Reference Links:

https://belitsoft.com/custom-elearning-development/ai-in-education/ai-in-edtech

https://www.emergenresearch.com/blog/top-10-leading-companies-in-the-artificial-intelligence-in-education-sector-market

https://xenoss.io/blog/ai-edtech-startups

https://riiid.com/en/about

Build on the most powerful infrastructure cloud

A vector illustration of a tech city using latest cloud technologies & infrastructure