Guide on How to Use E2E Cloud Servers More Efficiently

January 27, 2021

In an attempt to find access and download files from a server, cloud servers prove as an effective solution where it offers the ability to access the files from any remote location and a gadget. Cloud servers have made its place in every business, as it offers the most suitable solution for online data storage.

Need for Cloud servers

With conventional hard drives, there were many persisting issues like storage capacity limit, more exposure to files getting corrupted, and the offline storage costs. The issues were resolved through the implementation of cloud servers effectively. Cloud servers have made the process of sharing files and resources a secure and hassle-free process. All businesses and IT professional industries are inclined towards having a digital servers space to ensure never losing out on important data. All of this comes with a guarantee that the contents of the servers would be encrypted for maintaining privacy and ensuring safety against any hardware failure.

The global cloud computing market is aimed to cross the $330 Billion mark by the end of 2020

E2E has been a household name in the Indian market providing cloud computing solutions to businesses and SMEs. It has helped provide effective solutions to more than 10,000 customers actively using the platform. E2E has been successful in serving its customers with superior performance at affordable costs with bankable customer service.

What are the Different Types of Cloud servers Offered at E2E?

There is a wide range of cloud solutions offered at E2E, developed by understanding the market scenario and the customer requirements be it GPU cloud server, VPS and windows cloud servers, or any other solution.

  • CPU Intensive Computing C2- Series

This product is a perfect fit for businesses looking to expand their reach and reduce their downtime to a negligible rate with high performance and considerably high server space. Infused with the latest set of Intel processors, the C2 series will ensure heavy data operating applications.

  • C2 series with Red hat enterprise Linux

C2 series offers high performance to compute instances capable of supporting high IOPS and memory for website applications. This helps to compute high computing-based workloads to improvise on performance and without any downtime. The red hat enterprise is of the very recent offerings and top-ranked in the public cloud environments.

  • High Memory Cloud

Offering a cloud disk space of 225 GB SSD, the 2nd generation memory focussed plans are more inclined towards providing sufficient RAM support for the websites to maintain prolonging customer satisfaction.

  • Windows Cloud

Windows cloud hosting is one of the most affordable and opted services. At E2E, we offer numerous ranges of features offered at different price ranges to help you find your most suited solution.

  • Windows SQL Cloud

The SQL cloud is a perfect fit for windows operated systems as they are configured to support database workloads. It helps you adjust to the website’s needs and increase the capacity and the servers to ensure that there is no effect on the website application and the processes operated on it.

  • Plesk Windows Cloud

Plesk is an innovative control panel that helps ease the management process with a Graphic User Interface (GUI). This feature comes pre-installed on the windows cloud servers. It proves as a viable solution to enterprising reseller platforms and online stores to support the applications on Windows.

  • GPU Smart Dedicated

Built with the integration of the Nvidia T4, Tesla V100 and NVIDIA A100, it ensures that the upcoming and improving sectors like machine learning and artificial intelligence would not be limited by hardware support. The GPU based web cloud solution would help configure the visualization process with the combination of unbeatable performance for professional workflow requirements.

  • Linux Smart Dedicated

Offered at the lowest hourly rates, the smart, dedicated cloud servers solution aims to increase the performance of the machine learning processes and eliminate the effects of CPU steal along with customized automation to numerous backups, ensuring the safety and security of your data. The dedicated server offers an interactive API to give the managing ability of the machines via programming code.

  • cPanel Linux Cloud

Web hosting services have increased exponentially due to the rise in demand for online stores and learning management systems. cPanel cloud server comes with full root access and licensing for optimized security and with no additional cost. The customized solutions are offering a security tool to ensure website application safety and a plugin that will help with the onboarding of any other additional applications required on the website.

All the solutions offered by E2E are affordable and stored locally on Indian data centers, configured with high frequency for optimum performance characteristics. All the web hosting and cloud solutions are configured towards the optimization and smooth working of plugins and high data-based applications.

After understanding the types of solutions offered, the important aspect revolves around choosing the right cloud servers solution for your needs.

  • Look for plans that go beyond servers and offer excellent customer support

Cloud servers solutions though easy to operate, but on the back end, require extensive support from the service providers to ensure that the business owners are not affected in any way.

E2E ensures that the customers are justified for their services and providing them a great experience overall.

We help you understand and offer the best suitable plans for your needs with a personal touch to ensure that the user experience does not arise any conflict and look for solutions that are more focused on online and offline support.

  • Sync data across multiple devices

Secure servers or server windows VPS, all solutions are provided by E2E as cloud servers eliminate the need for syncing devices. All your data is being uploaded on the server mainframe, giving them the freedom to access the server from any device.

E2E cloud computing systems also facilitate the use of real-time collaboration that helps multiple users make changes for a file simultaneously. This is a great solution for project management and multitasking scenarios.

Close to 90% of the IT-based organizations have their database online on the cloud today, and more than 30% of the revenue stream of such companies are spent towards cloud handling and management services.

  • Using tools that facilitate cloud servers for better accessibility

Cloud-based applications have registered a staggering growth of 46%

The applications, when shared and installed on online servers, provide instant access to the data, which can be retrieved from any local connection or a mobile device. It comes with an easy-to-use user interface that helps make this process simplistic and features the ability to drag and drop files to be saved to the server's drive.

  • Keep data encrypted

Encrypted data ensures that even if data is misplaced or tampered with, it is useless and almost impossible to break into. The encryption process involves encoding the data before being uploaded to the server, which can only be accessed by the authorized user from an encrypted connection. The need for encryption equipped products is quite serious. The cloud encryption market alone is worth $2401 million by 2022.

  • Conduct performance analysis and implement continuous monitoring

With constant performance evaluation of your servers plan, it helps to keep track of all the attributes that the plan was designed to offer. It shows the areas requiring attention and improvement statistics to increase the server’s response time and overall quality.

  • Make sure to evaluate additional features and use auto-scaling

While taking up on a server's plan, make sure to have an understanding of all the features and functionalities for better perception. E2E helps potential customers by explaining each feature on a deeper level and connecting with their products.

With the help of auto-scaling, users can identify the amount and capacity of the computational resources that are measured in terms of server status. It helps to identify the traffic scenario on the web page application and ensures that the cloud can handle the current traffic demand.

  • Opt for automation-based control systems

Cloud servers work like clockwork. It finishes the ongoing job at hand and then carries out the other uploading processes. There are times when multiple users are accessing the servers platform. This increases the time.

The data optimization and restructuring methods are implemented in automation to make proper use of the servers space and services.

  • Retention period of data and value criteria

There are different policies implemented on different plans that provide a retention period of one week to one year. Before subscribing to a plan make sure to go through the server's retention period.

Define the duration time as per requirement and replace the existing policy to ensure you have the full benefit of the cloud service.

Windows cloud hosting or cloud servers have their servers API console, and so does E2E provide support on meeting the compliance standards and save your time.

  • Optimize cost and expenditures

Cloud servers are used to optimize costs and expenditures incurred to sustain the website and web page applications. If the current servers plan is not sufficient, the service plan should always cater to the possibility of modifying the services offered.

Comparing SSD-based Cloud Servers with HDD-based Cloud Server

SSD-based servers can read sequential data up to 550 Mbps, whereas HDD can perform at 125 Mbps in terms of writing speed.

SSD has been outperforming conventional hard drives as they offer high reliability, less and effective power usage with proper streamlining of processes. SSD does not cater to dropping variable seek time or latency issues, as HDD slots require to write NAND cells, their writing speeds are increased and consumes high power.


The aging process is quite slow in terms of SSD servers, where the servers can last easily close to a decade compared to HDD, which facilitates three to five years of working time. It is due to the absence of rotating parts that increase the endurance and enhance data integrity of SSD type, and data remains intact in SSD even when there is no power supply.

There is a downside to the SSD drives as they have a finite number of writes until it requires to be replaced. There are close to 3,000 write cycles on an average before breakdown. As HDD is built for writing data 24/7, they have comparatively more durability but also require more maintenance.

Power usage

While choosing a cloud plan, there has to be a proper research analysis done to rectify the needs and expectations that need to be satisfied from a cloud servers solution. Power usage is an essential deciding factor to weigh out the additional costs that go into maintaining the servers.

HDD drives tend to generate more heat due to their writing capacity, increasing overall power usage. SSD performs better because of its idle state and has a considerably low consumption rate.


HDDs are preferred mainly due to being cost-effective but fighting to compete against the server space SSD offers. The lower costs offered with large HDDs have competed against the new range of SSD with medium capacities. The cost is marginally dependent on the needs and budget capacity of a business.

SSD proves to be the most viable option in terms of durability and writing speeds, and overall performance over time. SSD also offers an excellent reduction in server load and processing time.


Businesses and individuals must have a good look at the product range and decide the solutions that are best suited for their needs. No matter the size requirement, everyone needs a cloud-based solution as it holds a lot of potentials and provides a gateway to better communication and integration.

For more information or Register for a free trial

Latest Blogs
This is a decorative image for: A Complete Guide To Customer Acquisition For Startups
October 18, 2022

A Complete Guide To Customer Acquisition For Startups

Any business is enlivened by its customers. Therefore, a strategy to constantly bring in new clients is an ongoing requirement. In this regard, having a proper customer acquisition strategy can be of great importance.

So, if you are just starting your business, or planning to expand it, read on to learn more about this concept.

The problem with customer acquisition

As an organization, when working in a diverse and competitive market like India, you need to have a well-defined customer acquisition strategy to attain success. However, this is where most startups struggle. Now, you may have a great product or service, but if you are not in the right place targeting the right demographic, you are not likely to get the results you want.

To resolve this, typically, companies invest, but if that is not channelized properly, it will be futile.

So, the best way out of this dilemma is to have a clear customer acquisition strategy in place.

How can you create the ideal customer acquisition strategy for your business?

  • Define what your goals are

You need to define your goals so that you can meet the revenue expectations you have for the current fiscal year. You need to find a value for the metrics –

  • MRR – Monthly recurring revenue, which tells you all the income that can be generated from all your income channels.
  • CLV – Customer lifetime value tells you how much a customer is willing to spend on your business during your mutual relationship duration.  
  • CAC – Customer acquisition costs, which tells how much your organization needs to spend to acquire customers constantly.
  • Churn rate – It tells you the rate at which customers stop doing business.

All these metrics tell you how well you will be able to grow your business and revenue.

  • Identify your ideal customers

You need to understand who your current customers are and who your target customers are. Once you are aware of your customer base, you can focus your energies in that direction and get the maximum sale of your products or services. You can also understand what your customers require through various analytics and markers and address them to leverage your products/services towards them.

  • Choose your channels for customer acquisition

How will you acquire customers who will eventually tell at what scale and at what rate you need to expand your business? You could market and sell your products on social media channels like Instagram, Facebook and YouTube, or invest in paid marketing like Google Ads. You need to develop a unique strategy for each of these channels. 

  • Communicate with your customers

If you know exactly what your customers have in mind, then you will be able to develop your customer strategy with a clear perspective in mind. You can do it through surveys or customer opinion forms, email contact forms, blog posts and social media posts. After that, you just need to measure the analytics, clearly understand the insights, and improve your strategy accordingly.

Combining these strategies with your long-term business plan will bring results. However, there will be challenges on the way, where you need to adapt as per the requirements to make the most of it. At the same time, introducing new technologies like AI and ML can also solve such issues easily. To learn more about the use of AI and ML and how they are transforming businesses, keep referring to the blog section of E2E Networks.

Reference Links

This is a decorative image for: Constructing 3D objects through Deep Learning
October 18, 2022

Image-based 3D Object Reconstruction State-of-the-Art and trends in the Deep Learning Era

3D reconstruction is one of the most complex issues of deep learning systems. There have been multiple types of research in this field, and almost everything has been tried on it — computer vision, computer graphics and machine learning, but to no avail. However, that has resulted in CNN or convolutional neural networks foraying into this field, which has yielded some success.

The Main Objective of the 3D Object Reconstruction

Developing this deep learning technology aims to infer the shape of 3D objects from 2D images. So, to conduct the experiment, you need the following:

  • Highly calibrated cameras that take a photograph of the image from various angles.
  • Large training datasets can predict the geometry of the object whose 3D image reconstruction needs to be done. These datasets can be collected from a database of images, or they can be collected and sampled from a video.

By using the apparatus and datasets, you will be able to proceed with the 3D reconstruction from 2D datasets.

State-of-the-art Technology Used by the Datasets for the Reconstruction of 3D Objects

The technology used for this purpose needs to stick to the following parameters:

  • Input

Training with the help of one or multiple RGB images, where the segmentation of the 3D ground truth needs to be done. It could be one image, multiple images or even a video stream.

The testing will also be done on the same parameters, which will also help to create a uniform, cluttered background, or both.

  • Output

The volumetric output will be done in both high and low resolution, and the surface output will be generated through parameterisation, template deformation and point cloud. Moreover, the direct and intermediate outputs will be calculated this way.

  • Network architecture used

The architecture used in training is 3D-VAE-GAN, which has an encoder and a decoder, with TL-Net and conditional GAN. At the same time, the testing architecture is 3D-VAE, which has an encoder and a decoder.

  • Training used

The degree of supervision used in 2D vs 3D supervision, weak supervision along with loss functions have to be included in this system. The training procedure is adversarial training with joint 2D and 3D embeddings. Also, the network architecture is extremely important for the speed and processing quality of the output images.

  • Practical applications and use cases

Volumetric representations and surface representations can do the reconstruction. Powerful computer systems need to be used for reconstruction.

Given below are some of the places where 3D Object Reconstruction Deep Learning Systems are used:

  • 3D reconstruction technology can be used in the Police Department for drawing the faces of criminals whose images have been procured from a crime site where their faces are not completely revealed.
  • It can be used for re-modelling ruins at ancient architectural sites. The rubble or the debris stubs of structures can be used to recreate the entire building structure and get an idea of how it looked in the past.
  • They can be used in plastic surgery where the organs, face, limbs or any other portion of the body has been damaged and needs to be rebuilt.
  • It can be used in airport security, where concealed shapes can be used for guessing whether a person is armed or is carrying explosives or not.
  • It can also help in completing DNA sequences.

So, if you are planning to implement this technology, then you can rent the required infrastructure from E2E Networks and avoid investing in it. And if you plan to learn more about such topics, then keep a tab on the blog section of the website

Reference Links

This is a decorative image for: Comprehensive Guide to Deep Q-Learning for Data Science Enthusiasts
October 18, 2022

A Comprehensive Guide To Deep Q-Learning For Data Science Enthusiasts

For all data science enthusiasts who would love to dig deep, we have composed a write-up about Q-Learning specifically for you all. Deep Q-Learning and Reinforcement learning (RL) are extremely popular these days. These two data science methodologies use Python libraries like TensorFlow 2 and openAI’s Gym environment.

So, read on to know more.

What is Deep Q-Learning?

Deep Q-Learning utilizes the principles of Q-learning, but instead of using the Q-table, it uses the neural network. The algorithm of deep Q-Learning uses the states as input and the optimal Q-value of every action possible as the output. The agent gathers and stores all the previous experiences in the memory of the trained tuple in the following order:

State> Next state> Action> Reward

The neural network training stability increases using a random batch of previous data by using the experience replay. Experience replay also means the previous experiences stocking, and the target network uses it for training and calculation of the Q-network and the predicted Q-Value. This neural network uses openAI Gym, which is provided by taxi-v3 environments.

Now, any understanding of Deep Q-Learning   is incomplete without talking about Reinforcement Learning.

What is Reinforcement Learning?

Reinforcement is a subsection of ML. This part of ML is related to the action in which an environmental agent participates in a reward-based system and uses Reinforcement Learning to maximize the rewards. Reinforcement Learning is a different technique from unsupervised learning or supervised learning because it does not require a supervised input/output pair. The number of corrections is also less, so it is a highly efficient technique.

Now, the understanding of reinforcement learning is incomplete without knowing about Markov Decision Process (MDP). MDP is involved with each state that has been presented in the results of the environment, derived from the state previously there. The information which composes both states is gathered and transferred to the decision process. The task of the chosen agent is to maximize the awards. The MDP optimizes the actions and helps construct the optimal policy.

For developing the MDP, you need to follow the Q-Learning Algorithm, which is an extremely important part of data science and machine learning.

What is Q-Learning Algorithm?

The process of Q-Learning is important for understanding the data from scratch. It involves defining the parameters, choosing the actions from the current state and also choosing the actions from the previous state and then developing a Q-table for maximizing the results or output rewards.

The 4 steps that are involved in Q-Learning:

  1. Initializing parameters – The RL (reinforcement learning) model learns the set of actions that the agent requires in the state, environment and time.
  2. Identifying current state – The model stores the prior records for optimal action definition for maximizing the results. For acting in the present state, the state needs to be identified and perform an action combination for it.
  3. Choosing the optimal action set and gaining the relevant experience – A Q-table is generated from the data with a set of specific states and actions, and the weight of this data is calculated for updating the Q-Table to the following step.
  4. Updating Q-table rewards and next state determination – After the relevant experience is gained and agents start getting environmental records. The reward amplitude helps to present the subsequent step.  

In case the Q-table size is huge, then the generation of the model is a time-consuming process. This situation requires Deep Q-learning.

Hopefully, this write-up has provided an outline of Deep Q-Learning and its related concepts. If you wish to learn more about such topics, then keep a tab on the blog section of the E2E Networks website.

Reference Links

This is a decorative image for: GAUDI: A Neural Architect for Immersive 3D Scene Generation
October 13, 2022

GAUDI: A Neural Architect for Immersive 3D Scene Generation

The evolution of artificial intelligence in the past decade has been staggering, and now the focus is shifting towards AI and ML systems to understand and generate 3D spaces. As a result, there has been extensive research on manipulating 3D generative models. In this regard, Apple’s AI and ML scientists have developed GAUDI, a method specifically for this job.

An introduction to GAUDI

The GAUDI 3D immersive technique founders named it after the famous architect Antoni Gaudi. This AI model takes the help of a camera pose decoder, which enables it to guess the possible camera angles of a scene. Hence, the decoder then makes it possible to predict the 3D canvas from almost every angle.

What does GAUDI do?

GAUDI can perform multiple functions –

  • The extensions of these generative models have a tremendous effect on ML and computer vision. Pragmatically, such models are highly useful. They are applied in model-based reinforcement learning and planning world models, SLAM is s, or 3D content creation.
  • Generative modelling for 3D objects has been used for generating scenes using graf, pigan, and gsn, which incorporate a GAN (Generative Adversarial Network). The generator codes radiance fields exclusively. Using the 3D space in the scene along with the camera pose generates the 3D image from that point. This point has a density scalar and RGB value for that specific point in 3D space. This can be done from a 2D camera view. It does this by imposing 3D datasets on those 2D shots. It isolates various objects and scenes and combines them to render a new scene altogether.
  • GAUDI also removes GANs pathologies like mode collapse and improved GAN.
  • GAUDI also uses this to train data on a canonical coordinate system. You can compare it by looking at the trajectory of the scenes.

How is GAUDI applied to the content?

The steps of application for GAUDI have been given below:

  • Each trajectory is created, which consists of a sequence of posed images (These images are from a 3D scene) encoded into a latent representation. This representation which has a radiance field or what we refer to as the 3D scene and the camera path is created in a disentangled way. The results are interpreted as free parameters. The problem is optimized by and formulation of a reconstruction objective.
  • This simple training process is then scaled to trajectories, thousands of them creating a large number of views. The model samples the radiance fields totally from the previous distribution that the model has learned.
  • The scenes are thus synthesized by interpolation within the hidden space.
  • The scaling of 3D scenes generates many scenes that contain thousands of images. During training, there is no issue related to canonical orientation or mode collapse.
  • A novel de-noising optimization technique is used to find hidden representations that collaborate in modelling the camera poses and the radiance field to create multiple datasets with state-of-the-art performance in generating 3D scenes by building a setup that uses images and text.

To conclude, GAUDI has more capabilities and can also be used for sampling various images and video datasets. Furthermore, this will make a foray into AR (augmented reality) and VR (virtual reality). With GAUDI in hand, the sky is only the limit in the field of media creation. So, if you enjoy reading about the latest development in the field of AI and ML, then keep a tab on the blog section of the E2E Networks website.

Reference Links

Build on the most powerful infrastructure cloud

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