Data centers face significant challenges in cooling server rooms, primarily due to the facilities’ increased power and energy density. For many experts, the solution lies in the different liquid cooling technologies, including direct liquid cooling (DLC), which dissipates heat through a liquid that comes into contact with thermal transfer devices or by immersing the equipment in the fluid.

This cooling approach is much more powerful and efficient than air cooling. Still, until relatively recently, it has been used primarily on some high-performance computing (HPC) platforms, where IT density is much higher than conventional. And there are only a few examples of data center operators that have applied this technology at scale, such as OVH Cloud.

According to a survey conducted by the Uptime Institute in the first quarter of 2022, one in six operators is already using DLC ​​. Still, experts anticipate this technology will expand, gradually replacing other cooling systems in many data centers. They have found that the liquid cooling market is beginning to concentrate on DLC solutions in anticipation of future demand. There are now many more options available than a few years ago.

On the one hand, applications that require high-density IT, such as high-performance technical computing, big data analytics, or deep neural networks, are expanding. In addition, operators are under increasing pressure to increase their efficiency and reduce their energy consumption and environmental impact. According to experts, this will speed up the transition from air cooling to liquid cooling, especially DLC.

Although the Uptime Institute researchers believe that the main driver of this change will be the evolution of IT infrastructures in data centers towards higher computing density, the new server processors are more powerful and run hotter, so they will require much more efficient solutions to continue increasing computing capacity without skyrocketing consumption. Therefore, experts anticipate that air cooling will become impractical by the middle of this decade, and DLC may be the best alternative.

But while the arguments for the move to DLC cooling seem strong, this transition involves several technical and business challenges that cannot be ignored. The first problem is the lack of standardization on DLC systems, an area where there are no standards when it comes to coolants or the mechanical systems used to move them through piping circuits. Organizations like the Open Compute Project and big companies like Intel are already working on this problem. However, they are still years away from developing standardized DLC products that can reach the mass market.

Meanwhile, data center operators will opt for the solutions that suit them best in terms of performance, cost, and ease of implementation. Manufacturers of these systems have come a long way in this field and now offer solutions that are easier to install and operate. Although reasonable standards for the industry are being developed, they must resolve logical doubts about issues such as performance metrics, among others.

Currently, analysts at the Uptime Institute recognize six categories of commercial DLC systems, although they believe that more will emerge in the future. These are cold water plates, single phase dielectric cold plates, two-phase dielectric cold plates, chassis immersion, single phase immersion, and two-phase immersion. There are currently more than a dozen specialty providers, usually focusing on one of these categories.

For their part, as the results of this survey indicate, most companies are open to switching to DLC and plan significant adoption of this technology in the coming years. But at the moment, many are unclear about which option they will choose or if they will take different forms of DLC, and this generates some uncertainty about the behavior of the DLC system market in the future.

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The Five Benefits Of Cloud Computing

For companies, regardless of their size, it is vital to know the main benefits of virtualizing their operations. Cloud computing offers many benefits for all types of businesses, regardless of their size, so we have focused on the top 5.

Fewer Costs

Suppose there is one thing that concerns any company, production costs and their reduction to maximize profits. Investing in cloud computing requires an initial investment, so we must emphasize the importance of ROI (Return on Investment).

First of all, accessing our company’s data quickly and easily allows us to save time; and that time is money. Investing in the cloud is efficient because we will choose the plan that best suits our needs, paying only for what we will use. Many studies show that the final consequence is a lower cost and a higher return, thanks to cloud-based applications.

More Security

As times progress, cybersecurity is more important in companies. Numerous ransomware attacks are taking place, so investing in cloud computing is one of the safest options. Protecting our files, databases, web pages, and storage is the smartest bet.

How do you get that security boost? Migrating our entire business to the cloud allows all our information to be monitored in real-time to prevent intrusions or illegitimate access to our databases. Not all companies have the necessary budget to create a cybersecurity area, hire specialists and keep their organizations safe.

Therefore, contrary to what one might think, investing in the cloud is a safe bet to prevent data theft perpetrated by cybercriminals. Several studies show that personal information thefts can occur by the same company employees when we have the information stored locally. This was the case with Dr. Varun Gupta, a former Intel employee who stole confidential information through a flash drive.

Greater Flexibility

Each company has specific needs, so it is essential that cloud computing offers flexibility to convince about its benefits. We talk about flexibility if we compare it with local hosting. A server established in the cloud can satisfy the demands in real-time instead of having to establish a very expensive local infrastructure.

We get that flexibility because companies have different plans to choose from that cater to different needs. In addition, we can choose how to build on cloud computing: public, private, or hybrid clouds. In this way, we will not spend more than we need, but more importantly: our business can grow, demand more resources and, for this, we can change to another more suitable plan. For this reason, it is said that the cloud accompanies the company’s progress, offering “scalability.”

Remote Work

In many companies teleworking or the hybrid modality is here to stay. There is no better way to make remote work viable than with the entire organization based on the cloud. Not only for employees who work from home but to access all company information from the phone.

Cloud computing adapts to current needs, so it offers the possibility of accessing our company’s information from anywhere in the world, as long as it is hosted in the cloud. One of the benefits of cloud computing is this remote access system, which allows us to obtain real-time control of what happens in the company and achieve that work-personal life balance.

Maximum Performance

Finally, one of the most attractive benefits of cloud computing is enjoying infrastructures powered by the latest hardware on the market. If we bought a local server for our company, we would have to change it after five years, which means keeping accounting on amortization or having to invest in fixed assets. Betting on the cloud means accessing machines and servers maintained by specialized personnel and updated with the latest technologies and market standards.

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Data governs both the organization of companies and their activity. They are also of different natures:

• Structure Data: These define the organization, whether it is the structure of the company’s services, information on employees, or an accounting organization.
• Product Data: This data concerns the commercial and technical characteristics of the products and the manufacturing and sales information.
• Third-Party Data: It concerns customers, prospects, suppliers, and business partners, as well as marketing sites.
• Resource Data: This is information relating to equipment, service providers, sites, and any other tool is allowing the implementation of the activity.

This wealth of data makes their management (called Master Data Management) a strategic subject for IS. All business processes are based on their proper implementation. Operations that must be fed quickly, with a high degree of confidence in the compliance and correctness of the data.

Suppose the final objective of Master Data Management is to circulate reliable, available, and exhaustive data throughout the IS. In that case, it is necessary to address a certain number of issues to achieve this objective:

• Fluid sharing of reference data between all IS applications
• The best data entry, without errors or duplicates
• Improving the user/employee experience
• The compliance with regulations such as RGPD
• Limitation of maintenance operations and other time-consuming tasks

The weight of each of these issues on data architecture differs from one company to another. Therefore, it calls for a personalized organization, which will take into account business needs and guarantee the best possible circulation of data on a technical level.

Also Read: How To Build Big Data Applications With A Low-Code Platform

What Architectures Exist Around MDM?

The architecture chosen to exchange reference data across the entire IS has a strong impact on the organization. It conditions the resources used and the speed of information processing. Each type of architecture will correspond to a particular mode of consultation of the data.

Among the most common architectures, there are four main solutions:

Centralized Architecture

This first type of architecture is organized around a central tool, the MDM software which will collect and unify information. The software tools dedicated to MDM are based on deduplication, data tracing, and monitoring functions throughout the life cycle. As soon as it is collected, the data is structured according to the company’s business rules, thus establishing a unique version of the data.

This is how it will provide the greatest added value and the greatest possible efficiency to the processes.MDM makes it possible to establish precise control over the entire data lifecycle. With regulations and data integrity taking precedence in many industries, this control is often the predominant criterion for successful architecture.

Distributed or Distributed Architecture

This architecture is based on the current concept of microservices: classified into a certain number of services, business applications themselves take charge of the data that concerns them. With this model, the reference data is therefore delocalized for each application and not centralized. Any other instance wishing to consult the data will have to retrieve it from the master application. This architecture makes it possible to guarantee true business data integrity. These do not undergo standardization, as would be the case with a single tool. 

Their quality is better preserved. However, the distributed model creates a complex organization, which requires knowing the location of the data well and keeping the system synchronized in the event of modification thereof. The distributed architecture also raises an important application availability challenge. A significant part of the process then depends on the performance of the information transfer.

Virtual Architecture

This model attempts to reconcile centralized and distributed architectures. The data, still managed individually by the applications, is easier to locate: a virtual repository acts as an information mediator, communicating the location of the data to the applications that consult it. Here again, the question of the availability and the freshness of the data is complex. The virtual model creates opacity as to which applications manage the data.

Also Read: DNA Inspired Encryption To Protect Data In The Cloud

How To Choose The Right Architecture For Your Reference Data?

The management of master data is a real fundamental subject: it calls for a strategic reflection around how the company’s processes, the main users of the data, are organized.

• On the one hand, data is shared by so-called vertical applications ( ERP, PLM, WMS, PIM, etc.), which enrich it throughout the life cycle of products or services.
• But cross-functional processes and the applications that employ them (BI, project portfolio management, etc.) are also important in making data more useful and breaking down barriers.
• Finally, the regulatory framework and the sensitivity of certain data play a strong role in the chosen architecture.
• For the company, it is, therefore, necessary to organize the reference data according to its priorities after having identified them.

Reference data must now support the customer-centric strategy of companies: customer data must be quickly collected and cross-checked to offer a high-performance user experience. But the need for quality and traceability continues to prevail, especially in highly regulated sectors. To make the right choice, it is necessary to identify the purpose of the data and their level of sensitivity and anticipate the volumes of data and the applications that will use it.

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Before the pandemic, more and more organizations whose IT upgrade strategies prioritized the jump to the Cloud of, if not all, of their technological resources. Covid 19 has convinced them more and increased the number of companies that direct their IT investments towards the Cloud.

Its benefits to facilitate multi-device access, flexibility in resource provisioning, scalability, pay-per-use and subscription models, etc., are very attractive. But the transition to the cloud poses many challenges when it comes to handling legacy systems and data and their consistency and integrity.

Also Read: DNA Inspired Encryption To Protect Data In The Cloud

Migrate The Legacy To The Cloud

In recent years, organizations have had to deal with a data explosion, Big Data, which has overtaken their traditional storage systems. They have been incorporating new resources of different profiles depending on the criticality of access to the data. A Backup is not the same as intensive access to data through ERP, CRM, and BPM business solutions or real-time provisioning for business analytics.

The challenge is to bring these different types of data uploads to the Cloud. Because yes, once they are in the Cloud, all are advantages, but migrating them is a very complex task, radically far from plug & play. The goal is to move hundreds of data without damaging or losing it and in the shortest time so as not to harm business continuity. The size of the project advises partnering with a company specialized in cloud migrations that, in collaboration with the company, designs and executes a safe, efficient and profitable cloud migration plan.

Steps To Simplify And Secure Data Uploads To The Cloud

When planning the transition to the Cloud, it is necessary to clarify many points. Each project is unique, and there is no standard to apply. We note some key questions:

1- What part of the IT infrastructure goes to the Cloud and what part remains. Depending on the business structure’s type of business and characteristics, the local-Cloud correlation will be determined. In this decision, it is crucial to ensure optimal connectivity and integration between all resources regardless of where they are housed.

2- Private Cloud or Public Cloud? When talking about IT and the Cloud, one usually thinks of the large Cloud providers in the Cloud, mainly AWS, MS Azure, and Google. However, the criticality of data in sectors such as banking, health. Compliance with sectoral regulations or compliance with corporate security plans makes it better to choose to deploy a private Cloud, typical of that organization, that provides the same functionality advantages as those of public offerings.

3- How to choose the best cloud provider? In this decision, it is essential to rely on an expert partner in business technology and migration to the Cloud to know the pros and cons of each one and avoid dependence on suppliers ( vendor lock-in ). We must assess the accreditations and certifications of their services, compliance with standards related to security, access management, data protection, and good practices, SLAs, types of monitoring of services, and their billing models and how they fit into the corporate budgets.

4- Detection of vulnerabilities and contingency plan. An analysis is necessary to identify potential security flaws in existing corporate systems that would abort a safe and efficient cloud migration. Simultaneously, it is essential to design a plan that covers any eventuality and ensures that applications and data remain available and daily operations are not interrupted. Business continuity during migration is critical.

5- Coexistence between the previous environment and the Cloud. Both worlds must coexist during migration. This cannot be executed at once; it is necessary to carry out tests to validate everything is transferred continuously. And not only to check that the applications work and integrate with the rest of the infrastructures locally, but also to protect them from cyberattacks thanks to secure protocols and data encryption.

6- Maximum collaboration between multidisciplinary teams. The migration of business technology to the Cloud is not just for the IT department. It is not a purely technical question. It is necessary to consider the business, security, and legal issues that appeal to a joint work of different profiles. In this sense, from the first moment, it is key to determine who will participate and establish optimal communication channels so that everyone is informed of the details of the transition to the Cloud.

Also Read: Data Protection Plan Requirements And Guideline

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Data must be safe in the cloud, which is why security experts are developing new ways to improve protection, which are generally based on encryption schemes specifically designed for these environments. Because conventional strategies reduce performance in accessing information, cloud customers demand more agility without less protection for their data, especially in distributed cloud architectures.

Seeking a new approach to improve the balance between protection and performance in a distributed cloud, a team of researchers from various academic institutions in India has developed an innovative encryption scheme. His idea is to employ a deoxyribonucleic acid (DNA) -based encryption key to provide an inviolable security framework. Thus, they claim to guarantee that data is protected in distributed cloud environments while providing great performance.

In their work published in the journal Frontiers of Computer Science, the scientists explain that in recent years the need for a cloud environment with the ability to detect illegal behavior has increased greatly as the need for a cloud environment has grown. Data storage capacity and the need for greater security. To address this, they present this novel approach, which provides an encryption technique “inspired by the biological characteristics of DNA and the mechanism of protein synthesis.”

They claim that their model also offers the added benefit of deciding on selecting the most suitable storage servers within the existing infrastructure, allowing you to optimize resources and have greater control over security. To do this, they have used a technique that allows establishing a preference for similarity with the ideal solution multicriteria decision-making model (MCDM) (TOPSIS).

Thanks to the possibility of choosing the physical location of the data, the scientists ensure that the execution time can be reduced and a higher level of security can be maintained than before. Likewise, they have investigated other possibilities that this approach will offer for the different cloud environments, which will allow improving security, taking into account some standard criteria, such as the avalanche effect, the correlation coefficient, the entropy of the information, the probability linear or differential probability, among others. Their tests indicate that the average change in the ciphertext is 51.85%, and a more exhaustive analysis of security, sensitivity, and functionality reveals that this scheme guarantees high security with very robust encryption.

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Today this information can be found in any communication channel, such as social networks, so much so that regulations have emerged to limit the processing of this information, such as the General Regulation on the Protection of Personal Data, which regulates the treatment of data so that companies do not treat them abusively or without the consent of users. From this exaggerated volume of information, we call Big Data, which is about exploiting large amounts of data for companies to use in their favor in developing their business.

That is why what we are coming to talk about today is the 5V that make up the concept of Big Data :

Volume

Considering what has been explained above, the volume of data would be a characteristic of this concept. We are talking about innumerable amounts of data that are sometimes lost in the networks because it cannot be managed and classified correctly. However, today some tools allow extracting this data and storing and organizing it properly.

Speed

As there is such an exaggerated volume of data, their life cycle is concise, therefore –as we explained above-, we must use innovative and efficient technologies to be able to extract that information, which by having a life cycle so short, it forces us to do it at the highest possible speed, and continuously, to always have up-to-date and truthful data on users available.

Variety

Obviously, in a world where there is so much information, and thousands of different channels to disseminate it, in each track you can find information of various types, thus obtaining an exaggerated variety of data, present in other formats – since, just as we can extract written word, we can find it through images or videos, of which you have to know how to highlight the useful ones for your company. This creates a challenge for Big Data applications, which must also recognize it in different formats and store and order information.

Veracity

Due to the immense amount of data in the networks, not all are always reliable, so information must be filtered, classifying and separating the information that may be false, from the true and useful for making decisions for your company.

Value

This is probably the essential feature of Big Data since if the Big Data tool meets the four previous characteristics, and the information will be abundant and truthful, it will be up-to-date. It can be presented in a multitude of formats that will favor decision-making in your business. That is why it is valuable information, and you have to know how to use it properly to get the most out of all this data about your customers and potential customers.

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