Future of Industrial Robotics technology

Robotics is a technology which deals with the design, construction, operation, structural disposition, manufacture and application of robots. Robotics includes multiple areas of skills and engineering disciplines like mechanics, electronics, electrical, computer science etc.


Robotics is a rapidly growing field. Robotics is used in STEM (Science, Technology, Engineering, and Mathematics). Research, design and building new robots with enhanced technologies will help in serving many practical problems irrespective of whether it is commercial or domestic or military. Many robots are built to do the jobs that are hazardous to human beings. For Ex: bomb detection and its diffusion, exploring mines, finding survivors in natural catastrophes, shipwrecks etc.

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Soft robotics is a branch of robotic technology, which deals with non-rigid robots constructed with silicon, fabric, rubber and other compliant mechanical parts like spring. These have a large number of advantages over rigid robots. For example, locomotion in rough and unknown terrain, grasping of unknown objects etc. Used materials are much economic as compared to rigid robots.

There are some ethics for robots as well which is termed as roboethics. The concerns are about whether the robots pose a threat to humans (Ex: in health care sector, war field). Some of the fields included in roboethics are cognitive science, neurosciences, psychology, industrial design, philosophy, biology, theology, law, and sociology.

Commercial and Industrial robots are widely used to perform tasks as they are more accurate and reliable compared to humans. They are also widely used in surgery, manufacturing, assembling, weaponry, packing, transporting, laboratory research, mass production of goods, earth and space exploration. Some robots are specially built for heavy duty hence called “heavy duty robots” . With the advancement in technology, there are applications that can be developed, create the behaviors and play interactive robotic games. There are multiple toy robots to play with.

Cloud robotics

Cloud robotics is one more interesting field of robotics. It invokes cloud computing, cloud storage and other shared services of robotics.Some of its applications are:

Autonomous mobile robots:

Google’s self-driving cars to use the network to access the enormous database of maps and satellite.

Cloud medical robots:

By connecting to the clinical cloud they can assist doctors (co-surgery robot), service to patients etc

Industrial robots:

Robots can share information for collaborative tasks. A consumer can order customized product to the manufacturing system.

Robotics has its vast application in the military. Military robots are autonomous robots or remote controlled robots. Military robots date back to World War 2. Military robots are fitted with multiple cameras, radar, sensors, firearms etc

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Using the robotics technology several robots are built to help in various activities. To name a few of them are listed below.

  • Ant robotics – Robots with this technology have limited sensing and computational capabilities.
  • Autonomous Underwater Vehicles (AUV) – These robots travel underwater without requiring input from an operator. In the military, they are often referred to as Unmanned Undersea Vehicles. Scientists make use of these robots to study the ocean. These are also used to find wreckages of missing airplanes.
  • Justin – It’s a space robot; light weighted, tends to repair other satellites and is controlled from earth.
  • Mobile manipulator – It has advantages of both robotic manipulator and mobile platforms, that reduce their drawbacks.
  • Robotic mapping – Autonomous robots construct the maps and localize themselves in it.
  • Rover (space exploration) – It’s a space exploration vehicle.
  • Unmanned Aerial Vehicle (commonly known as a drone, Unmanned aircraft system) – It’s an aircraft without a pilot onboard.
  • Humanoid Robots – It resembles the human form. Many companies across the globe have invested in these humanoid robots. They are now used in the research field. They are also developed to assist the sick and elderly, receptionist jobs, education, retail, distribution, tourism etc. They are also becoming extremely popular for providing entertainment. One such example is Ursula, a female robot which sings dances and speaks to her audiences at universal studios.

Some robots are also built with the combination of navigation hardware and software in order to traverse. There are some advanced robots which are capable of sensing the environment well and make decisions on the navigation based on the information gained. Most of these robots are built GPS navigation with waypoints, radar, and other sensory data like lidar, video cameras and inertial guidance systems for better navigation between waypoints.

How to Fix the iCloud Key­chain Not Sync­ing Issue

Fix Syncing sensitive data among devices is pretty much commonplace these days, but the technology is susceptible to bugs and glitches. Same goes for the Apple ecosystem. Often, you will find instances of iCloud Keychain not syncing your passwords and credit card info between your iOS, iPadOS, and macOS devices.
Fix  that’s happening to you right now, I highly recommend you to fix iCloud Keychain to start syncing your data once again. Manually inserting lengthy alphanumeric passwords or typing in your credit card details repeatedly isn’t exactly a fun experience.

Thankfully, it’s relatively easy to fix syncing issues with iCloud Keychain. So without any further ado, let’s check out how.

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If iCloud Keychain doesn’t sync your data between your devices, then there’s a simple fix (recommended by Apple itself) to solve the problem. It involves turning off iCloud Keychain across all of your Apple devices, and then turning it back on starting from the device that has your most up-to-date data. That will cause iCloud Keychain to sync your data without issues once again.

To make things easier, let’s break the process down. We shall start from disabling iCloud Keychain on your iPhone and iPad and turning it off on any macOS devices that you own. After that, we shall re-enable it in the correct order. Just make sure to be connected to a strong internet connection (Wi-Fi or cellular) during the process.

Disable iCloud Keychain – iPhone and iPad

Step 1: On the iPhone and iPad, open the Settings app, and then tap your user profile. Follow that up by tapping iCloud.

Step 2: Scroll down the screen, and then tap Keychain. On the next screen, turn off the switch next to iCloud Keychain.

Step 3: Tap Keep On My iPhone when asked for confirmation.

Wait for a moment, and then disable iCloud Keychain on any other iOS or iPadOS devices that you own.

Disable iCloud Keychain – Mac

Step 1: Open the Apple menu on your Mac, and then click System Preferences.

Step 2: Double-click the option labeled iCloud.

Step 3: Uncheck the box next to Keychain.

Step 4: On the pop-up menu that shows up, click Keep On This Mac.

Continue disabling iCloud Keychain on any other macOS devices that you own.

Re-Enable iCloud Keychain

Once you’ve finished disabling iCloud Keychain across your iPhone, iPad, and Mac, the next thing that you must do is to re-enable it on all of the devices.

But preferably, you must enable iCloud Keychain first on the device that has the latest version of your Keychain data. For example, if you changed your passwords or credit card details on a device after the syncing issue first started, then start off by enabling iCloud Keychain on that device first.

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If you can’t remember the exact device that contains your latest data, you can try checking your list of saved passwords and credit card info manually. But if there are lots of passwords, it’s not that easy to figure that out. In that case, go with your gut. At the most, you will have to redo the entire procedure from scratch if iCloud Keychain fails to work.

iPhone and iPad

On the iPhone and iPad, visit the Settings panel, tap Passwords & Accounts, and then tap Website & App Passwords to check out your list of passwords.

To check your saved credit card information, tap Safari within the Settings panel, and then tap Saved Credit Cards.


On the Mac, open Safari. Next, click Safari on the Menu bar to the top of the screen, and then click Preferences.

When the Passwords pop-up box shows up, click AutoFill and Passwords to check your credit card info and passwords respectively.


The iCloud Keychain syncs your data seamlessly, for the most part. So losing out on that incredible convenience factor can be maddening. Hopefully, you ended up resolving the issue, and can now access your passwords and credit card info across all your Apple devices. Things have vastly improved compared to how iCloud was before, but we will have to wait a while before a totally bug-free sync experience becomes the norm. So don’t forget this fix the next time iCloud Keychain breaks down on your devices.

The Current State of the Healthcare Industry & AI

Artificial intelligence (AI)has the potential to improve every aspect of our lives and help us transform healthcare. Let’s have a look at how healthcare is practiced today and how AI is transforming it. Healthcare implies keeping the health of an individual up to the mark or improving it. It covers injuries as small as paper cuts to blood cancer.


Healthcare can be divided into three categories, namely the following.

  • Curing
  • Preventive
  • Predictive

We can use the huge amount of data produced every day to find a better cure for a disease, find new drugs, and even predict the probability of a disease long before any symptoms relating to it are observed.

Healthcare industry problems

The problems of the healthcare industry can be divided into two broad categories. One category of the problem arises from the sociopolitical and financial issues, while the other arises from the technological challenges in the industry. Issues like shortage of beds, shortage of healthcare workers, and unqualified medical practitioners belong to the first category. The second category contains issues like slow research, human errors in analyzing data, and the lack of data transparency among the organizations.

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AI to improve healthcare

Artificial Intelligence offers an amazing opportunity to transform the world in a huge manner. It has been called as the new electricity by Andrew Ng. It has the potential to touch every person’s life in a meaningful way, just like electricity did.

In healthcare, AI can help in improving each step of the ecosystem. From the prediction of disease to finding a new drug to making all new gene modifications.

AI-Healthcare ecosystem

Imagine a scenario where a couple is about to get married. An AI system can check the compatibility of their genes to figure out if there is any risk to the child or some gene that can result in a complication in the child’s normal life. This system can then help in figuring out the right measures that can be taken before and after the baby is born.

AI in action

Digital Diagnostics using Computer Vision

Currently, a lot of diagnostics require a trained professional to analyze samples of blood, saliva, tissues, semen, etc. under a microscope. This is very time consuming and error-prone. Dedicated machines exist for different tests, but a cheaper solution is possible using AI.

Digital diagnostics use computer vision technology to analyze images of these samples and then apply algorithms such as ANN and CNN to figure out the size shape and movement of cells. This data is then used as the features to train a machine learning model to find the problems that the patient might have.

Predicting Spread of Virus Outbreaks

Various machine learning models have been used to predict the spread of viruses and other infectious diseases. Social media data from platforms like Facebook, Twitter, etc. are used to fit regression models to predict areas of next outbreaks.

Patient flow optimization

We can use data like the number of patients per hour visiting the hospital, current weather conditions, and common injuries to predict the number of patients that might come to the hospital on a given day. This intelligence is useful for medical centers to optimize their supplies and be better prepared for emergencies.

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 Personal Doctors

Advances in Natural Language Processing has made it possible to create smarter chatbots to help patients at any hour of the day. A user can simply type in the common symptoms that she is facing, and her chatbot will tell her if she should see a doctor or not. The assistant can also book an appointment with the doctor automatically based on the urgency of the situation.

Ethics in Healthcare

Ethics is one of the most important pieces of the puzzles when we are talking about AI in healthcare. I leave it to the reader to think about the following scenarios and realize how complex it could get when we have intelligent machines making decisions for us.

  • Who owns your data? The Electronic Health Record(EHR) that your hospital has belongs to you, but should you be allowed to take ownership of it? What if you had a very rare disease and your data is of prime importance, should the society be allowed to use the data even though you don’t want it?
  • Suppose the AI system finds out that you are very likely to have a type of cancer that is incurable. Would you like to learn about it? Think about the emotional toll it can have on the person.
  • What if the predictions made by AI were wrong. Who should be responsible for that, is it the developer who coded it or the organizations that made the system or the data that was used to make the system in the first place?

AI in healthcare has a huge potential if we can solve some of the aforementioned issues. We see tremendous advancements in the area, and most of the things described in this article are not as fictional as they sound.

Using Docker to Increase Developer Efficiency

Docker is a cross-platform virtualization program used to create containers: lightweight, portable, self-contained environments where software runs independently of other software installed on the host machine. Containers are largely isolated from each other and communicate through specific channels.


They contain their own application, tools, libraries and configuration files, but they’re still more lightweight than virtual machines. Though container technology has been around since 2008, Docker’s release in late 2013 boosted their popularity. The program featured simple tooling that created an easy path for adoption.

Now, it’s a favorite DevOps tool which facilitates the work of developers and system administrators alike.

The Power of Containers

Containerization provides a workaround for some irritating development hurdles. For instance, running several different applications in a single environment causes complexity. The individual components don’t always work well together, and managing updates gets complicated fast.

Containers solve these problems by separating applications into independent modules. They feed into the enterprise-oriented microservice architecture style, letting developers work on different parts of an application simultaneously.

This increases the speed and efficiency of development while making applications that are easier to maintain and update. Taken as a whole, it’s obvious why both software developers and IT teams like containers.

The technology enables the rapid, iterative development and testing cycles which lie at the core of Agile methodologies. It also takes the burden of dependency management off system administrators, who can then focus on runtime tasks (such as logging, monitoring, lifecycle management and resource utilization).


Why Docker Is the Right Choice

Docker isn’t the only containerization software around, but it is the industry standard. It’s a robust, easy-to-use API and ecosystem that makes using containers more approachable to developers and more enterprise-ready. The program has an edge on previous solutions when it comes to portability and flexibility.

Using Docker simplifies the process of coordinating and chaining together container actions, and it can be done faster than on virtual machines. Docker removes dependencies and allows code to interact with the container instead of the server (Docker handles server interactions).

Plus, there’s a large repository of images available:

Getting up to speed with Docker doesn’t take long. The documentation is thorough, and there are plenty of tutorials online for self-taught developers.

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Docker In Action: The Financial Times

The Financial Times is a London newspaper founded in 1888. Their online portal, FT.com, provides current business and economic news to an international audience. The media outlet was one of the earlier adopters of Docker back in 2015. Docker containers helped cut their server costs by 80%.

Additionally, they were able to increase their productivity from 12 releases per year to 2,200.

Looking Forward

Last year, the median container density per host rose 50% from the previous year. In fact, the application container market is poised to explode over the next five years.  Experts predict that annual revenue will quadruple, rising from $749 million in 2016 to over $3.4 billion by 2021. Docker specifically still leads the pack despite the niche popularity of emerging tools.

83% of developers use Docker. CoreOS trails well behind it at 12% with Mesos Containerizer at 4%. Overall, Docker Containers is a highly enterprise-oriented solution. Other tools are emerging to add functionality (like container orchestration platform Kubernetes), so there’s no reason it shouldn’t continue growing in popularity.

Omnichannel Retailing? Trends, Strategies

Omnichannel  If you’re in the retail industry, you know that the competition is unlike anywhere else. Businesses are using every available sales and marketing avenue to convert shoppers into customers and customers into long-term, loyal consumers.


While retailers may be taking advantage of new sales channels like social media accounts and ecommerce platforms, so is everyone else. To keep up with — and hopefully surpass — the competition, businesses need to deliver personalized, unique experiences. That’s where omnichannel retailing comes in.

What is Omnichannel Retailing?

Today’s consumers are researching, browsing, and purchasing products on multiple channels and devices. In fact, 98 percent of consumers switch between devices every day, which is why many retail brands have adopted a multichannel retail strategy.

Multichannel retailing creates a separate strategy for each sales channel and device. While this was once the latest technological trend, it can lead to disconnected messaging and offers for consumers — especially the 98 percent who are using multiple devices throughout the day.

With an omnichannel approach, retailers develop one strategy that is executed across all channels to create a connected, customer-focused experience. An omnichannel strategy also enables customers to convert through any available online or offline touchpoints.

An omnichannel strategy means that a shopper who begins browsing a brand’s website will have the same experience whether they visit the brand’s mobile app, social media accounts, or brick-and-mortar store, and whether they use a mobile phone, tablet, desktop, or laptop.

In addition to consistent customer experiences and a unified brand, there are many business opportunities that come with omnichannel retailing. Companies that implement omnichannel tactics have an average customer retention rate of 89%while those that don’t use this strategy only average 33 percent retention.

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Omnichannel Retail Trends

The decision to utilize omnichannel retailing is just the beginning. Every brand needs to strategize specific ways to align their brand, company goals, and customer needs. Below are a few trends that retailers are tailoring to their business.

Augmented Reality

Customers might be hesitant to order certain products online. A couch, for example, might be available at a great deal but not knowing how it will look in a certain environment might deter someone from adding it to their cart.

A modern-day spin on “try before you buy,” augmented reality is an easy and interactive way for customers to visualize products in a real-world, at-scale setting. Shoppers simply select a product to be superimposed into their environment and can then decide if they’d like it in a different size, shape, color, or other option. The Amazon app is one of the most popular examples of successful augmented reality implementation.

Augmented reality brings inventory directly to the customer and can help boost customer confidence, reduce shopping cart abandonment, and limit returns.

In-Store and Mobile Connectivity

Companies like Starbucks are fully embracing mobile app capabilities by enabling customers to place orders on their phones for in-store pickup. The coffee giant has also created a loyalty program that rewards customers every time they use their mobile app to pay.

Not only does this give consumers an incentive to visit Starbucks over other coffee shops, it’s also an opportunity for the company to use their app as a way to market and upsell to existing customers. And since 71 percent of customers who shop in a brick-and-mortar store say that their mobile device is important to their in-store experience, unifying the two channels is an effective way to recruit and retain customers.


Tech-savvy shoppers know when they’re being marketed to. And with shoppers visiting various channels across multiple devices, generic strategies will only lead to generic customer experiences.

Delivering tailored content and product recommendations is how modern-day retailers captivate shoppers. Using a customer relationship management (CRM) platform, businesses can record and analyze customer demographics and preferences to better appeal to their audience.

Personalization can be executed throughout all sales channels — from following up via email after a customer makes a purchase, to retargeting relevant ads on social media, to training employees on how to better communicate with customers.

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Here’s an example of how these three omnichannel trends can work together:

A customer visits a houseware store’s website. Since they didn’t purchase anything, they are later remarketed to on Facebook. The ad includes a photo of the exact lamp the customer was considering, as well as information about using the website’s augmented reality feature to see how the specific lamp would look in their living room.

The next day, the customer decides to purchase the lamp online and pick it up in the brick-and-mortar store. While chatting with a store employee, the customer reveals that they’ve recently moved and are in the process of furnishing their new place. The store employee makes a note of this on the customer’s profile in the store CRM.

A day after picking up the lamp, the customer receives an email from the housewares store recommending other types of home décor that would go with the lamp. With omnichannel retailing, the store was able to totally personalize the research, purchase, and follow-up process.

How to Implement an Omnichannel Strategy

To get started with an omnichannel strategy, retailers need to develop a holistic view of all of their available sales channels, including:

  • Brick-and-mortar stores
  • Ecommerce platforms
  • Social media accounts
  • Email marketing campaigns
  • Telephone sales
  • Mobile apps

In addition to unifying these channels, creating a strong brand presence will be key for strategy development and consistency.

Talk to an Expert to Get Started

From retailers to restaurants, Hitachi Solutions is uniquely positioned to help businesses implement the full suite of end-to-end capabilities offered with Microsoft Dynamics 365.

Implementing good information governance

Information governance is much more than compliance and should not be used interchangeably. It is the strategy behind the entire information lifecycle, including effective management of information’s authority, control, accessibility, and visibility. Furthermore, information governance can bring much greater value to organisations as it has the potential to uncover business opportunities and protect them from security threats. Businesses should see compliance as the end goal and information governance as the way to achieve it.


Answering these simple questions helps you on your path to good information governance:

  • Do you know how your employees are working and what applications they use?
    • Do you know where your business’ information is being stored?
    • Do you know if you have full control of your business information?

How would you answer that last question? Unfortunately, most organisations would answer ‘no’. A recent Association for Information and Image Management (AIIM) study found two-thirds of organisations had some level of information governance policy in place but nearly one-third admitted that their inferior electronic records kept causing problems with regulators and auditors. So what are the hurdles and how can they be overcome?

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There are common pitfalls

Poor information governance varies from the unfortunate to the catastrophic. At worst, hackers get a hold of sensitive information. At best, out-of-date information may be used and then commitments have to be honoured based on this inaccurate information. While in between is a range of incidents of information mismanagement and examples of employees using unsanctioned tools, all of which can be prevented.

One great example is email. Its very nature puts valuable information at risk on an hourly basis. Potentially confidential information contained within an email is frighteningly susceptible to interception and vulnerable to security threats. Yet countless employees use email as a method for sharing sensitive information. But worse still employees use both approved work email accounts and unsanctioned private email accounts. A recent Alfresco survey found that over half (54 per cent) of end users have turned to their private email for work, most likely due to the limitation of enterprise email.

Many knowledge workers have turned to consumer solutions to provide collaboration and access capabilities not enabled within the enterprise. None of these applications are approved or controlled by corporate IT. These ‘Shadow IT’ solutions can pose a serious security risk for organisations, leading to information leaks from unsecure practices and the failure of compliance regulations.

Another critical challenge is implementing policies for the use of other tools such as instant messaging and social media. This is born out by the results of a recent AIIM study that highlighted that less than 15 per cent of organisations included social postings in their information governance policies. While some conversations are essential to business growth, 37 per cent of respondents agreed that there are important social interactions that are not being saved or archived due to a lack of information governance.

Rather than being a one off catch up activity done at year end, information governance should be an on-going, critical initiative that runs throughout the year

Good information governance can be achieved

A lot of organisations have a focus on compliance, management, and security controls in place, but what is really required is information governance. Here are some simple steps organisations can take:

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Understand the range of information you have and how it needs to be managed and where it is currently being stored.


Rank your information and the associated processes to assess the level of risk: compliance risk, regulatory risk, and reputational risk. For ease consolidate this to a minimum.


Policies need to be decided. What needs to be kept, for what purpose, which employees need access, and for how long? The information should be stored where it can be most effectively used, while also addressing business objectives and risks.


Once these protocols are set, there should be regular checks of what information is maintained. Archiving or deleting content once it has outlived its useful life should be encouraged. Pruning old data will reduce storage costs and the associated management costs.


Keep Shadow IT in check. Where you can restrict access to unsanctioned tools and stop employees using personal accounts for business.


Most importantly, develop an information management system with people at the heart of it. Implementing tools to support your employees – ones they find easy to use – so that they will, indeed, use them.

[easy-tweet tweet=”Organisations may focus on compliance, management, and security controls, when information governance is needed”]

Following these steps will enable organisations to take information in any format; analyse what needs to be preserved and protected, and delete what is unwanted. Content can now be easily sorted and managed, access and monitoring controls can be easily implemented where needed. Being able to say you know how your employees are working, where your information is being stored and that you have full control of that information will lead to a boost in efficiency and productivity.

How to Build a Data Backup Service for SaaS

As SaaS solutions become more popular, companies need to pay more attention to data protection. Important corporate data stored in the cloud should be protected as reliably as data stored on-site. This article will be useful for developers who are working on their own cloud backup solution.


Importance of a data backup service for SaaS

One of the most significant benefits of cloud storage is that a cloud service vendor is responsible for data management and is in control of your SaaS data security and backups. While this might be true in most cases, however, not all cloud service providers can assist in recovering company’s data if a single change made by one of employees causes data corruption or even loss.

With the growing popularity of SaaS solutions, companies that maintain data in the cloud are getting interested in cloud-to-cloud backup tools for the following reasons:

Cloud-to-cloud backup solutions are easy to implement. Cloud-based software doesn’t require large initial infrastructure investment and can be easily deployed with just an agent installation.

Cloud-to-cloud backup solutions have predictable costs. With no big upfront costs, companies can focus on maintaining current operational costs regardless their chosen backup solution.

Cloud-to-cloud backup solutions are simple to manage. Since a service provider is responsible for data management, the only thing a company has to worry about is backing its servers.

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Why cloud services need backup

Cloud-to-cloud backup ensures that data stored on distributed cloud-based platforms – such as Salesforce, Microsoft Office 365, and Google Apps – is safe. Cloud-to-cloud backup solutions allow you to easily recover data from any time. Google Apps, for instance, allows data restoration only within 25 days according to an all-or-nothing principle. Therefore, there’s a need on the market for new cloud-to-cloud solutions.

Overview of existing solutions

Cloud-to-cloud backup solutions let you implement scalable, manageable, and dependable cloud-based data backups. When developing a particular SaaS system or striving to improve your SaaS backup strategy, you should follow the same principles you would when managing on-site deployments. When developing your cloud-to-cloud backup and data protection solution, consider the following:

Performance. Before offering backup software, first test its performance. You might need to develop a backup speed testing tool if it has no one. This tool should be able to perform upload and download speed tests as well as latency tests.

How saved backups work for actual recovery. Test to make sure that backups will work in an emergency.

SSAE 16(Statement on Standards for Attestation Engagements) compliance. This is a mandatory standard for US service organizations for reporting their system and security controls and is comparable to international standard ISAE 3402.

Pricing. The costs of a backup for cloud services involves comparing total expenses, not only the starter price. Vendors usually charge for the average amount of stored data per year, though there might be exceptions.

The ability of restore and backup processes to meet recovery time objectives (RTO) and recovery point objectives (RPO) for your company’s customers. Meet RTO and RPO requirements for third-party SaaS applications.

Building your own cloud backup solution

When you decide to create your own backup software for SaaS, you should first determine the set of features you need. The following features are in high demand and are part of the most competitive cloud-to-cloud backup solutions currently on the market:

Data encryption prior to transfer – Encrypting data before transferring prevents access by unauthorized users.

Deduplication – Data deduplication is a compression technique to avoid data repeating. It allows companies to optimize their storage resources and decrease bandwidth requirements.

Hybrid cloud backup – Cached backups stored on a company’s premises reduce the time needed to restore data.

Extracting and saving cloud-based data to physical devices – Storing cloud-based data on a physical disk on-site reduces time for both initial backup and data restoration.

Ongoing backups (incremental forever) – Perform one initial database backup and then save ongoing backups with active users in the database instead of backing up the whole database every time. This reduces the amount of data coming and going across a company’s network.

Sub-file-level backups – This feature reduces the volume of data that needs to be copied by only backing up changed parts within individual files and works best with large files.

Bandwidth options – Zipping data and scheduling backups to avoid impacts on users within a corporate network.

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Requirements for cloud backup solutions

In addition to necessary features, your cloud-to-cloud backup solution should meet certain requirements to ensure the efficiency of data backups and restores. Let’s cover these requirements in detail.

Regulatory Сompliance

Your cloud-to-cloud data backup and recovery solution should ensure compliance with regulations such as the Health Insurance Portability and Accountability Act (HIPAA). Even though your company may not currently work with health service providers, you may in the future. Therefore, you should consider implementing data security measures to ensure compliance.

Data Backup Frequency

Define how often users should back up their data. Should users be able to set a custom schedule or should they use a regular schedule? Or both? Your solution should also let users manually make backups at any time.

Effective Search

It’s hard to remember the name of each file stored in a database. Therefore, your cloud-to-cloud data backup solution should have a convenient search feature that will help your users quickly find files.


Generating backups is necessary to protect data created in SaaS services from corruption or loss. Since there are various SaaS backup services on the market, you should consider the pricing and features of existing services in order to develop a competitive solution.

Risks of Shadow IT and How To Mitigate Them

Shadow IT is one of the most worrying problems for any organization, from small businesses to large enterprises. It creates additional challenges for IT departments and often puts an organization’s entire network at risk. According to Gartner, by 2020, around 30 percent of successful attacks on enterprises will be on their unsanctioned shadow IT resources.

ShadowThis article explains the main risks of shadow IT and what can be done to detect and mitigate this problem.

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Hiding in the shadows

What is shadow IT? Basically it’s any IT system, technology, or application that’s deployed and used without the approval of the corporate IT department. In some cases, personal devices including cell phones and USB devices may also be considered part of shadow IT.

The most common examples of shadow IT are popular cloud services like Dropbox and Salesforce and commonly used messengers like Viber and WhatsApp. However, what’s considered part of shadow IT mostly depends on a particular company’s corporate policy.

People turn to shadow IT for different reasons. The most common reasons for using shadow IT are:

  • Efficiency – Approved software and solutions can be (or at least seem to be) slower, less effective, and less productive than unsanctioned alternatives.
  • Compatibility – Corporate solutions may be incompatible with users’ personal devices.
  • Comfort – People tend to use software and solutions they’re used to.

Even though shadow IT often seems to be helpful to end users, it poses a serious threat to enterprises.

But why is shadow IT so dangerous? The main threat posed by unsanctioned software and applications hides in its unaccountability — you can’t effectively manage something that you don’t even know exists. As a result, both security and performance of the entire network are put at risk.

Let’s take a closer look at the most common risks of shadow IT:

  • Lack of security – Lack of visibility and control over network elements are the main cybersecurity risks of using shadow IT. They create numerous weak spots that hackers may use for compromising a system and collecting or stealing sensitive business information. Plus, since unsanctioned software and applications aren’t managed by the IT department, they usually have lots of unpatched errors and vulnerabilities.
  • Performance issues – Certain products and solutions can be incompatible with the main components of the IT infrastructure, leading to serious performance issues.
  • Data loss – An IT department can’t create backups for software they don’t know is present in the network, while shadow IT users usually don’t think (or know) that backups are necessary. As a result, there’s always a significant risk of losing important, valuable, and sensitive data.

    Throwing light upon shadow IT

    Currently, there are two common ways to deal with unapproved software and cloud applications: deploy shadow IT discovery and management solutions or turn to DevOps. Let’s take a closer look at each of these options.

    Shadow IT discovery and management solutions

    IT asset inventory systems are one tool that can be used to detect shadow IT. These systems gather detailed inventory information on hardware and software running in the network. Based on this information, you can analyze how different assets are used.

    In order to ensure efficient detection of unsanctioned cloud applications, the following four features are needed:

    • Visibility – An IT asset inventory system should provide full visibility of the monitored IT environment and all IT assets present in it.
    • Automatic updates – All received data should be accurate and up-to-date so you can see what’s happening and react immediately when needed.
    • Asset categorization – Not all IT assets have the same importance and criticality, so it’s crucial to rank assets according to their importance.
    • Compatibility with the configuration management database – An IT asset inventory solution should be fully compatible with the configuration management database (CMDB) so it can perform constant information updates to the database.

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Do you even need to fight it?

There’s no denying that shadow IT is dangerous and can pose a serious threat to any company. However, that doesn’t mean there are zero benefits to using unsanctioned software in the corporate network.

What are the benefits of shadow IT? First and foremost, the mere fact that unapproved software is running on a company’s systems shows that approved solutions don’t meet the requirements of employees: they’re either inefficient or uncomfortable or both.

Secondly, there’s always a chance of shadow IT turning out to be more productive and cost-effective than already deployed solutions. The main task here is to recognize the solutions that can be more beneficial to the company and find a way to implement them effectively into the current infrastructure.

Edge Computing and the Internet of Things

Thinking about the biggest trends in computing, chances are you will come up with the cloud, Artificial intelligence, and the Internet of things. Nearly everyone knows about the cloud but this technology is not stagnant, it is evolving which has resulted in the rise of a new computing model — Edge computing (EC.)


Thus, new scenarios are being composed inspired by these four technologies as foundational to the optimization of data handling processes.

From Cloud to Edge — back to the roots

The bigger the loads of data that need to be operated on, the better. In the context of the evolution of the Internet technologies that the IoT is triggering, this upward trend required and is still requiring changes in the computing paradigm. This is how Cloud computing (CC) happened to dominate the global IoT market recently.

Since isolated embedded systems provide applications with the relatively small data volumes, they have given way to cloud-based services, systems, and solutions. At some point, Cloud computing decisively changed the form of IT discourse. As equally revolutionizing technologies, IoT and the cloud turned out to complement each other perfectly — there are platforms that are provided with content to be generated on. Thus, using the metaphor of a cloud, we, as single users and employees or managers of large and small companies, have storage and processing tasks offloaded. Luckily, there is a whole variety of platforms that allow the merge of CC and IoT. To put it in a nutshell, the benefits of Intelligence in Cloud for IoT can be presented as follows:

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  • remote management of data
  • the merging of data from multiple devices
  • infinite storage that let AI tools improve their algorithmsWe seem to hold all the cards in our hands, yet this is just for now and, in fact, one should look ahead. This type of computing works well with PCs, smartphones, and tablets, while the number of IoT devices is, in turn, expected to triple by 2025 growing to alarming 75.44 billion. More devices mean there will be more data to process. Although the cloud serves as a relatively reliable intermediate layer between smart objects and applications, its scope must be broadened with the load growth. The shift in the computing paradigm has been needed badly.

    Why Edge Computing?

    Though we’ve emphasized the relation of computing to IoT specifically, Edge is not all about it. The primary motivation behind the use of Edge touched a broad question of efficient data collection and management. In the course of time, the new form of computing proved to be the best place for the realization of these purposes and started getting anchored in the corporate strategies. But how and why?

    Edge computing became an alternative method of eliminating time and distance and a perfect solution for accelerating and improving the performance of the cloud for users introducing the following huge improvements:

    • Latency reduction. Experiencing boosts in data volumes might be much more comfortable while living at the edge. Instead of network latency caused by non-stop transferring data back and forth between devices and clouds, the edge allows this interaction to be dynamic offering the ways of hyper-interactivity implementation. The edge does not merely replace clouds, it minimizes the latency. For example, if user bases are dispersed, clouds can be replicated remotely by installing intermediary data centers or servers. Physical proximity affects not only users’ trust but also the latency. As a result, end users who, figuratively speaking, live in Tier-2 cities far from big data centers have an opportunity to experience a better UX.
    • Advanced security management. Another reason to consider EC is the pressing security issues. Data privacy in IoT must be a focus of attention. Now that systems are connected to the cloud and to the Internet, there is a danger not only to data but to what is happening in the real world too. The aforementioned time and distance elimination can reduce the risk. The basic logical network elements — edge nodes — are being designed and arranged in hierarchical order to optimize the whole architecture. Lying between the cloud and the IoT devices they serve, the nodes contribute to enhancing the security. The closer they are located to the sensors, the shorter the data flow distances are — the smaller the attack surface is.

    Edge Computing: How is it different from the Fog?

    Sometimes, these two notions are used interchangeably, but they actually convey different meanings. Similar to edge computing, the fog is a mediator between end users and cloud data centers. However, Cisco, who has introduced fog computing, claims that the fog is the standard according to which the edge is brought into action, not the edge itself.

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    Azure IoT Edge

    Indeed, the concept of Edge computing is exciting but it means nothing without the real-life examples of its application. Yet in 2008, Microsoft raised the question of the future of Cloud computing and then, a decade later, in 2017, came up with the Azure IoT Edge Runtime.

    Crosser Edge Computing Solution

    Since EC is growing in popularity and evolving, companies that are focusing on the development of the software solutions for the edge exclusively are coming on the scene. One of these companies is Crosser. They have engaged in the EC solutions development activities for the following reasons:

    • Aspects of IT security. Cleaning at the edge (filtering out the relevant data, normalizing it from different sources, and aggregating to reduce its amount and get a clean data set) allows anonymizing data before sending it to the cloud and transferring only the relevant and critical information there.
    • Streaming analytics. Moving the analytics to the edge instead of sending it to the cloud or to an on-premise environment along with applying more advanced algorithms detecting data anomalies helps to generate notifications about the maintenance procedures and security measures that are needed locally.
    • Available under any circumstances. Poor connectivity to the cloud is not an obstacle anymore. EC introduces buffering of data to store it temporarily and then upload it to the cloud when the connection is restored.
    • Lower data storage costs. Cloud providers usually charge the clients for the number of connected devices and connections, amount of data sent, selected services in the cloud, and the frequency of computing usage. Therefore, the system and the architecture must be adjusted to optimize these costs, which can be easily done with the help of edge computing.

    At that, Crosser is successfully meeting the objective of taking advantage of the above features applying the full edge computing solution for the benefit of its clients.

How to Overcome Entity Framework Issues?

An object-relational mapper (ORM) is an essential part of any project that includes a database. It simplifies the maintenance and processing of data, allowing developers to focus on code. But each ORM framework has its pitfalls that you have to be aware of before implementing it.


In this article, one of our Apriorit experts discusses key issues we faced with Entity Framework in one of our .NET projects. He explains how to speed up materialization and SELECT, INSERT, UPDATE, and DELETE statements in Entity. This article will be useful for developers who are looking for a library for their .NET projects or who are already working with Entity Framework.

What is an ORM?

An object-relational mapper (ORM) is software responsible for mapping between databases and object-oriented programming languages. An ORM creates a virtual database scheme and allows a developer to manipulate data at the object level. A mapping shows how an object and its properties are associated with data in database tables. The ORM uses this information to manage the transformation of data between databases and objects.

Using an ORM saves a developer a lot of time because it:

  • Automates the processes of inserting, updating, and deleting data according to commands from an application
  • Creates SQL queries automatically
  • Simplifies updating, maintaining, and reusing code
  • Enforces a Model–View–Controller pattern to structure code

On the negative side, ORM frameworks aren’t easy to learn. If you’re working with an extensive database, processing queries and editing data can take some time. Also, an abstract database can be a trap for inexperienced developers. Without knowledge of database operations, they may write optimized statements that slow down the database.

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Entity Framework — a complex ORM library

Entity Framework is an ORM library that allows for working with databases using .NET objects. It was originally created in 2008 as a way to realize custom repository patterns (DbConnection, DbCommand, etc.) for ADO.NET. Entity Framework is mainly used by websites written in .NET.

Issues we’ve faced using Entity Framework

At Apriorit, we have developed and supported several complex .NET projects using Entity Framework. It’s an efficient tool for database management, but over the years we’ve identified several critical issues with this library:

  • Slow processing of SELECT statements
  • Poor data materialization
  • Slow INSERT/UPDATE query processing with large volumes of data
  • Issues with executing the DELETE statement

Let’s take a closer look at why these issues occur. In the third part of the article, I’ll talk about third-party libraries we’ve used to improve Entity Framework performance.

Slow SELECT statement processing

The Entity Framework API is built on Language Integrated Query (LINQ), with a very small difference between client code and the SQL-translated code executed by the DBMS. Because of this, it has difficulties with processing the SELECT statement. For example, there’s a common performance issue with SELECT N+1 queries.

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Third-party libraries for Entity Framework

Despite the issues we’ve discussed, Entity Framework is a very useful library for .NET projects. At Apriorit, we use third-party libraries to improve its performance.

Developers all over the world have created lots of additional libraries and workarounds for Entity Framework. We’ve chosen the Entity Framework.Utilities and RefactorThis.GraphDiff libraries for our projects because they’re easy and fast to implement. We’ve also examined the possibility of using NHibernate and Dapper. However, NHibernate looks overengineered because of the Hibernate Query Language and drivers, and Dapper doesn’t create SQL queries, and our projects have used a DBMS and SQL dialects.

Let’s see how to use Entity Framework.Utilities and RefactorThis.GraphDiff to speed up the performance of Entity Framework.


In this article, we’ve discussed what Entity Framework is and dived deep into common issues with materialization and SELECT, INSERT, UPDATE, and DELETE statements. These operations can significantly slow down work with Entity Framework, especially when dealing with an extensive database. We’ve also shown you a way to speed up this library using third-party libraries.