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OUR BLOG


Month: June 2022

ZiRA, The Dutch Hospital Reference Architecture, is a Tool for Addressing a Global need

Posted on June 30, 2022July 26, 2022 by Marbenz Antonio

A Framework of Reference for Hospitals

The goal of this blog is to introduce one such Dutch healthcare breakthrough, ZiRA, to a large audience of English-speaking architects. In Dutch, a hospital is referred to as a “Ziekenhuis,” so ZiRA is a set of interlocking components (templates, models, and downloadable files) that give architects, managers, and high-level decision-makers tools to a) understand and describe the current state of their hospital and b) transform virtually any aspect of their business to achieve desired states. The ZiRA can assist users in achieving important, mission-critical goals, such as continuously evolving to provide high-quality health services, improve patient outcomes, increase patient experience, and, in general, function efficiently and effectively.

The Impact of Public-Private Partnerships

Nictiz, the Dutch competence center for the electronic exchange of health and care information, developed ZiRA. Nictiz is an autonomous foundation that is pretty exclusively supported by the Ministry of Health, Welfare, and Sport in the Netherlands. Nictiz has been promoting ZiRA adoption for over a decade by encouraging the formation of collaboratives such as iHospital, a group formed of and directed by important stakeholders from hospitals and related stakeholders across the Netherlands.

Introducing ZiRA to a Larger Audience

ZiRA was previously exclusively available in Dutch. It comes to reason that this characteristic alone has limited its widespread acceptance. The Open Group Healthcare Forum (HCF), in partnership with Nictiz and the ZiRA Governance Board, is working on a thorough English translation and clarification. The first of two parts, titled Hospital Reference Architecture, was released on June 23, 2022. The HCF addresses how Enterprise Architecture can help hospitals provide more value to patients while also increasing functional efficiency in the Preface to this White Paper.

Relating ZiRA to The Open Group Healthcare Enterprise Reference Architecture

The Open Group O-HERA™ standard, a healthcare reference architecture industry standard, provides a high-level conceptual framework relevant to all major stakeholders across all healthcare disciplines. As a result, the O-HERA standard is provided at a higher degree of abstraction, whereas ZiRA is adjusted to fit individual hospital needs and objectives. The O-HERA standard enables the creation of a crosswalk between the concepts and objects defined in ZiRA (mainly the Architecture Model) and a variety of other emerging and potentially less developed healthcare reference models around the world.

10,000 Foot View: Applying Reference Architectures to the Health Enterprise Level

The Open Group published the O-HERA Snapshot in 2018. This resource includes a cognitive map and conceptual roadmap to assist healthcare professionals in consistently defining their enterprise architectures to effectively align information technology and other resources to solve business problems.

The O-HERA is built on the traditional “plan-build-run” methods that have been used profitably by numerous sectors for decades, as seen in Figure 1. The company concentrates on vision, mission, strategy, capability, and transformational outcomes during the “PLAN” phase (or “management model”). The organization handles procedures, information, applications, and technology during the “BUILD” phase (or “management model”). Finally, the “RUN” phase stresses operations, measurement, analysis, and evolution (consistent with an “operations model”). Security, which is important to efficiently transmit healthcare data, pervades the entire model. The O-HERA standard, as shown in the center of the diagram, is built on agility, a person-centric focus, and a strong preference for modular solutions.

Figure 1. The Open Group Healthcare Enterprise Reference Architecture – O-HERA™

The Vital Importance of Industry Standards

The country’s establishment and application of standards as a strategic approach to ensuring that the best interests of its inhabitants are served have been a critical success factor for ZiRA’s adoption in The Netherlands. Nictiz actively contributes to the creation of standards and the dissemination of best practices knowledge. ZiRA was created over a decade ago with The Open Group ArchiMate® modeling language.

ArchiMate allows you to generate diagrams or illustrations that describe the relationships between concepts, which improves communication and hence understanding of complicated ideas connected to business architecture, in this example the hospital organization.

Effective standards are required for the establishment of information exchange in healthcare, which in turn is required to enhance healthcare delivery and outcomes. When each hospital uses its own chosen vocabulary and proprietary method to characterize the systems that enable clinical care, considerable obstacles to successful health information sharing arise. This topic is further upon at the end of this blog in the context of a health care interoperability use case.

Without information flow, elaborate and costly crosswalks and mapping operations are required just to connect as simple yet critical data as individual patient identification. Data sharing agreements are similarly expensive and difficult to implement since essential concepts and vocabulary must be exhaustively specified to achieve complete mutual understanding between parties. Extensive reliance on such efforts at translation across proprietary systems is also brittle and time-consuming to maintain.

How A Reference Architecture Benefits Communication

When a Hospital Reference Architecture, such as ZiRA, is implemented, a foundation is built to assist hospital organizations in bridging communication issues between diverse internal and external systems. Nictiz laid the groundwork for this shared knowledge by creating a “Five-Layer Interoperability Model,” as seen in Figure 2. The definition of common language and explicitly associated concepts aids in the advancement of common understanding within and between hospitals. For example, agreement on the meaning of terms such as “Business Functions,” “Services,” “Business Processes,” and “Business Activities” reduces the possibility of ambiguity or misinterpretation.

Figure 2.  Nictiz Five-Layer Interoperability Model

ZiRA expands on the standard notions expressed by Nictiz in the metamodel shown in Figure 3. In this case, dependence on The Open Group ArchiMate® modeling language, an international standard, is a critical strategic success factor for assuring ZiRA’s performance.

The ZiRA demonstrates, using rich context from the healthcare industry, how the adoption of The Open Group standards helps ensure that a reference architecture is immediately consumable by Enterprise Architecture practitioners across all industry verticals and domains.

Using the same concepts from the ArchiMate standard across hospitals facilitates a common understanding and makes comparing differences easier when, for example, a merger is being explored or systems must collaborate to support care shared across the healthcare continuum.

Figure 3.  ZiRA Metamodel

A ZIRA Use Case: Interoperability

ZiRA provides a conceptual and practical framework for achieving a wide range of hospital improvement goals. It uses the ArchiMate standard to give a shared frame of reference and a uniform modeling language. It encourages collaboration among participating hospitals through standardization, the sharing of best practices, and the acceleration of architecture and agile development processes. The goal of expanding interoperability in the healthcare chain between and among hospitals, health information networks (HINs), and a variety of other providers is particularly noteworthy.

Interoperability, or rather its lack, is a global issue, especially involving challenges in creating data sharing agreements and resolving data ownership and translation barriers between and even inside healthcare organizations. In the United States, “information blocking” has become such a problem that legal mandates such as the US Office of National Coordinator of Health IT’s the 21st Century Cures Act, which requires covered businesses to support interoperability, have been created. Similar rules and regulations have been enacted in other nations. In such an environment, a ZiRA success story built on more effective collaboration provides vital insights from which other countries and health systems can benefit.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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IBM Cloud Pak for Linux on Z and LinuxONE for Business Automation

Posted on June 23, 2022July 26, 2022 by Marbenz Antonio

BLOG: IBM Cloud Infrastructure Center for IBM Z and LinuxONE - Mainline

We all saw the world alter right in front of our eyes. As a result, businesses have to adapt their business practices to rely more on automation. As we adjust to the new normal, we will be well prepared to support your ongoing journey through automation in 2022.

When you combine app modernization, co-location, and sustainability, you have the right mix to help your business model evolve. The Covid-19 epidemic, as well as the Great Resignation, have rendered the IBM Cloud Pak for Business Automation on Linux on Z and LinuxONE vital to overcoming day-to-day business issues. Company automation helps to achieve and maintain faster and more consistent business results.

IBM Cloud Pak for Business Automation accelerates application modernization by providing a set of services and capabilities designed to identify best practices, identify obstacles, and identify inefficient procedures. These business difficulties are addressed by automating and simplifying procedures to increase productivity and reduce errors. IBM Z has a twenty-four-year track record of increased energy efficiency. The IBM Z’s capacity to pivot and improve energy efficiency, power conversion efficiency, and cooling efficiency is important to your business model. IBM Z and LinuxONE offer our clients an affordable and long-term path to running on a cloud-native platform with flexible computing to run on IBM Cloud Paks for Business Automation.

The following IBM Cloud Paks for Business Automation features are supplied as containers running on Red Hat OpenShift on the IBM Z platform:

Content unstructured or semi-structured data, including documents, text, photos, audio, and video Material services secure the entire lifecycle of content.

  • FileNet Content Manager
  • Business Automation Navigator
  • IBM Enterprise Records

Decision allows you to gather, organize, execute, and monitor decisions by providing repeatable rules and policies for day-to-day company activities.

  • Operational Decision Manager
  • Automation Decision Services

Workflow explains how work is completed through a series of actions carried out by humans and systems Workflow management is the process of designing, executing, and monitoring workflows.

  • Business Automation Workflow
  • Automation Workstream Services

Operational Intellegence By capturing and analyzing data created by operational systems, business automation insights provide a thorough understanding of corporate operations. The information is displayed in dashboards and made available to data scientists for analysis utilizing AI and machine learning.

  • Business Automation Insights
  • Business Performance Center

Low-code Automation is a visual method of application development that employs drag-and-drop components. Low-code tools allow business users and developers to build apps without writing code.

  • Business Automation Studio
  • Business Automation Application Designer
  • Business Automation Application runtime

With so many options available for Cloud Paks for Business Automation, it’s critical to have a dependable platform that enables scalability, robustness, and sustainability. Running Cloud Paks for Business Automation on Red Hat OpenShift on IBM Z and LinuxONE allows you to easily automate.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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Four ways digital transformation might help achieve sustainability goals

Posted on June 23, 2022July 26, 2022 by Marbenz Antonio

10 Reasons Sustainability Needs To Be Part Of Your Digital Transformation Strategy

People are reconsidering their sustainability objectives as a result of the pandemic-related events of the last two years. Regulatory standards are being issued by governments. Sustainability criteria are being incorporated into investment decisions by investors and financial managers. Customers and employees are also becoming more environmentally conscious, looking for companies and workplaces that share their values. These forces are forming a new corporate agenda. Sustainability has rightfully taken center stage in the boardroom and operational management discussions.

Despite this growing influence, a new analysis from IBM’s Institute for Business Value, “Sustainability as a transformation catalyst: Trailblazers turn desire into action,” finds that only 35% of organizations have implemented a sustainability plan. Fewer than four out of ten businesses have identified either actions to close their sustainability gaps or sustainability motivations for change. Only one-third of businesses have integrated sustainability targets and KPIs into their business processes.

To achieve their sustainability goals, businesses require actionable environmental insights. However, present methods are usually time-consuming and complex, necessitating much human work, climate and data science expertise, and computational power to fully exploit their data.

The good news is that digital transformation may assist businesses in being resilient, adaptive, and profitable in this new era. Here are four ways a comprehensive data and AI strategy might help reshape business operations to focus on sustainability.

Creating a more resilient infrastructure

Climate change and decreasing natural resources necessitate businesses to extend the life of their buildings, bridges, and water connections. Companies can discover new opportunities to streamline their operations, save costs, eliminate waste, attract new customers, increase brand loyalty, and embrace new business models by starting on digital transformation to achieve sustainability obligations.

AI-powered remote monitoring and computer vision assist enterprises in detecting, forecasting, and preventing problems. In addition, they can undertake condition-based maintenance based on operational data and analytics to reduce downtime and maintenance costs. Improved asset management can assist businesses in reducing their spare parts inventories. A corporation can also save energy by identifying a tiny problem before it grows into a larger, more energy-consuming problem.

Building a transparent, trusted supply chain

Supply chain executives require visibility. When they are unable to track the exact amount and location of their goods, they may over-order, tying up too much working capital. And if supply chain leaders lack openness and data exchange with their deep-tier suppliers, tracking products from point of origination through delivery in a trusted and controlled manner becomes extremely challenging. This makes identifying supplier risk and protecting the brand more difficult.

Reaching supply chain sustainability goals necessitates a worldwide, accurate, real-time inventory picture, as well as the capacity to communicate data across the supply chain ecosystem in a trustworthy manner. AI assists businesses in avoiding obsolete and unsold inventory, lowering carbon emissions from logistical activities, optimizing fulfillment decision-making, and minimizing waste across raw materials, completed items, and spare parts inventories.

Deriving business insights from environmental intelligence

Companies that are vulnerable to a wide range of external influences require particularly advanced prediction systems. Unilever and other consumer products corporations want data to help them estimate the environmental effect and make sustainable decisions. Insurance businesses like Desjardins Insurance in Canada want to better foresee disruption to policyholders — for example, earlier warning of impending hailstorms might let its clients take steps to avoid harm. With AI-driven forecasts derived from a combination of proprietary and third-party geospatial, weather, and IoT data, environmental intelligence capabilities assist businesses in planning for and responding to weather occurrences. This streamlines and automates environmental risk management and operationalizes underlying processes, such as carbon accounting and reduction, to achieve environmental goals.

Decarbonizing the global economy

Utilities will continue to play a critical role in the energy transition in the coming years, speeding global decarbonization through clean electrification – the process of replacing fossil fuels with electricity generated from renewable sources such as wind, solar, and hydro. They will also require a thorough asset management strategy for these renewable energy plants’ operations, maintenance, and lifetime. Digital transformation will be important to decarbonization, allowing power ecosystems to deliver clean energy to connected consumers safely and dependably.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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Overcome these six data consumption barriers to become a more data-driven organization

Posted on June 23, 2022July 26, 2022 by Marbenz Antonio

Data-Driven Marketing: 6 Steps to Success | CircleBack

By seeing data as a crucial asset that gives insights for better and more informed decision-making, implementing the correct data strategy supports innovation and excellent business outcomes. Enterprises may shape business decisions, reduce the risk for stakeholders, and gain a competitive advantage by leveraging data. However, a foundational step toward becoming a data-driven business requires trusted, widely available, and easily accessible data for internal users; hence, a strong data governance program is important.

Many organizations struggle to ensure data quality and access within their organizations while also developing and maintaining proper governance mechanisms. Here are a few examples of common data management issues:

  1. Regulatory compliance on data useWhether put in place by governments or specific industries, data protection standards such as GDPR, CCPA, HIPAA, and others go beyond sensitive data to detail how firms should allow their employees to access enterprise data in general.
  2. Proper levels of data protection and data securityCertain data pieces are a real competitive advantage and business uniqueness; as a result, those data assets must be protected against data breaches, with only authorized individuals having data access.
  3. Data quality
    Data must be thorough, accurate, and well understood to be trusted. This necessitates data stewardship and data engineering processes to manage data standards and track data history, hence enhancing data value. AI and analytics are only as good as the data utilized to power them.
  4. Data silosA typical organization’s data landscape includes many data stores spread across workflows, business processes, and business units, such as data warehouses, data marts, data lakes, ODS, cloud data stores, and CRM databases. Data integration across this hybrid environment can be time-consuming and costly.
  5. The volume of data assetsThe quantity of data assets and data components stored by the average firm continues to expand. This massive amount of enterprise data, which consists of thousands of databases and millions of tables and columns, make it difficult or impossible for users to identify, access and use the information they require.
  6. Lack of a common data catalog across data assetsThe absence of a standard business vocabulary throughout your organization’s data, as well as the inability to connect those categories to current data, leads to inconsistency in business metrics and data analytics, as well as making it difficult for users to discover and comprehend the data.

Why you should automate data governance and how a data fabric architecture helps

The aforementioned difficulties necessitate a data strategy that includes governance and privacy structure. Furthermore, the framework must be automated to scale across the organization.

An architecture that facilitates the design, development, and execution of automated governance across the company is required to help avoid vulnerability and inability to innovate caused by a lack of adequate data governance. This is especially true for businesses that operate in hybrid and multi-cloud settings.

A data fabric is an architectural technique that is used to ease data access in an organization. To enable self-service data consumption, this architecture makes use of automated governance and privacy. Self-service data consumption is important because it improves data users’ ability to find and use the right governed data at the right time, no matter where it resides, by utilizing foundational data governance technologies such as data cataloging, automated metadata generation, automated governance of data access and lineage, data virtualization, and reporting and auditing.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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The Importance of RegTech in AI Governance

Posted on June 23, 2022July 26, 2022 by Marbenz Antonio

Regtech: What it is and How it Solves Business Problems - Tookitaki : Tookitaki

Artificial intelligence (AI) is now widely used throughout society. The value of AI and the efficiency gains it generates promote its adoption. Every day, most of us rely on AI to do things like autocomplete our text messages, navigate us to a new area, and recommend what movie to watch next. Aside from these widespread uses of AI, authorities are beginning to identify areas where there may be a larger risk. According to the European Commission’s Digital Strategy website, these higher-risk domains can include the application of AI in employment, finance, law enforcement, and healthcare settings, as well as other areas where the outcomes might have a substantial influence on individuals and society. As AI adoption grows, there is a growing realization that enabling trustworthy AI is critical, with 85% of customers and 75% of CEOs now acknowledging its significance. Establishing guidelines, such as IBM’s trust and transparency principles, is critical for guiding the development and usage of trustworthy AI. The establishment of proper governance mechanisms for AI systems is important to put these concepts into practice.

AI governance will require an agile approach

AI governance is the act of governing an organization through its corporate instructions, staff, processes, and systems to direct, evaluate, monitor, and take corrective action throughout the AI lifecycle to ensure that the AI system operates as the organization intends, as its stakeholders expect, and as required by relevant regulation. We anticipate that regulations governing AI systems will evolve quickly and that operators and developers of AI systems will need to adapt quickly when policy initiatives and new regulations are implemented. Agile techniques, which were first promoted in the context of software development, are built on ideals such as collaboration and responding to quick change. Governments throughout the world are now using agile governance models to respond fast as technology evolves and to encourage innovation in new technology fields such as blockchain, driverless vehicles, and AI. The adoption of an agile strategy in AI governance can assist AI adopters in determining if changes in governance and regulatory requirements are appropriately and timely incorporated.

Integrating RegTech into the broader AI governance process

To satisfy the predicted legal requirements for AI systems, an agile approach to AI governance can benefit from the deployment of RegTech. RegTech, as defined in the World Economic Forum white paper “Regulatory Technology for the Twenty-First Century,” is “the application of various new technological solutions that assist highly regulated industry stakeholders, including regulators, in setting, effectuating, and meeting regulatory governance, reporting, compliance, and risk management obligations.” Chatbots that can provide regulatory advice, cloud-based platforms for regulatory and compliance data management, and computer code that enables more automated processing of regulatory data are all examples of RegTech. These RegTech solutions can function as part of a larger AI governance process and be integrated as components of larger AI governance processes, which may include non-tech components such as an advisory board, use case reviews, and feedback systems. Strong stakeholder buy-in and starting with essentials like a clear definition of AI, internal rules, and clarification on current regulatory requirements can help with integration into existing processes.

Case studies on OpenPages: Using RegTech for AI governance

IBM OpenPages with Watson is a RegTech solution that can assist adopters in navigating a quickly changing regulatory and compliance environment. IBM has assisted companies like Citi, Aviva, General Motors, and SCOR SE in using RegTech to satisfy governance requirements, minimize risks, and manage compliance. IBM OpenPages with Watson is also used as a basic RegTech component in its internal end-to-end AI governance process. IBM OpenPages with Watson can assist in the collecting of compliance data on AI systems in order to assess compliance against business policy and regulatory standards. The use of RegTech for AI governance from the beginning of regulatory requirements for AI systems can help in the construction of a centralized regulatory library to assist in data collecting and tracking when data would otherwise exist in silos throughout the business. The business can possibly benefit from efficiencies in the processes and resources that enable these solutions by adopting a consolidated RegTech solution.

Looking forward: RegTech is expected to play a central role in AI governance practices

We believe that in 2022 and beyond, RegTech will play a critical role in AI governance procedures. We anticipate that RegTech solutions will continue to evolve to address the demands of businesses affected by new rules, standards, and AI governance requirements. AI is also likely to drive new requirements for specific RegTech functionality such as bias assessments (which could include specific metrics such as disparate impact ratio), automated evidence to monitor for drift in AI models, and other functionality related to the transparency and explainability of AI systems.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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What Is the Difference Between LAMP and MEAN?

Posted on June 23, 2022July 26, 2022 by Marbenz Antonio

MEAN Vs LAMP Stack - Key Differences You Need To Know

Discover the differences between the LAMP and MEAN stacks and their benefits and advantages for web app development.

LAMP and MEAN are popular open-source web stacks for building high-performance, enterprise-grade web, and mobile applications. They, like other web stacks, incorporate technology (operating systems, programming languages, databases, libraries, and application frameworks) that developers may utilize to easily and reliably construct, launch, and manage a fully complete web app via stack development.

LAMP and MEAN differ in that they offer different layers — or “stacks” — of technologies that a web project requires to perform across all frontend interface, network, and backend server operations. A web-based banking application, for example, might use either the LAMP stack or the MEAN stack to read a user’s request to view financial activities, retrieve the relevant data, and present it in a user interface.

What is the LAMP stack?

LAMP stands for the following stacked technologies:

  • L: Linux (operating system)
  • A: Apache (webserver)
  • M: MySQL (a relational database management system, or RDBMS, that uses SQL)
  • P: PHP (programming/scripting language)

The Linux operating system allows the full web program to work properly on a given piece of hardware. The Apache web server interprets a user’s request before retrieving and “serving” information to the user through HTTP (Hypertext Transfer Protocol). The MySQL database (a relational database management system) contains the data that the web server can obtain and offer based on the user’s request (e.g., bank statement archives, financial activity, image files, CSS stylesheets). PHP collaborates with Apache to extract dynamic content from the MySQL database and deliver it to the user. While HTML can display static information (for example, a headline that remains on the screen regardless of data), PHP is used to display dynamic material that changes dependent on user input. The PERL and Python programming languages can also be utilized in the LAMP stack. In a 1998 article for a German computer magazine, writer Michael Kunze used the acronym LAMP stack for the first time.

Figure 1 shows a high-level illustration of how a web app responds to a user request across its LAMP stack. This request may involve user actions such as accessing the program, logging in, and searching within the application:

Figure 1: How a user request is processed across the LAMP stack.

What is the MEAN stack?

MEAN stands for the following stacked technologies:

  • M: MongoDB (non-RDBMS NoSQL database)
  • E: Express.js (backend web framework)
  • A: AngularJS (frontend framework that builds user interfaces)
  • N: Node.js (open-source backend runtime environment)

An incoming user request is processed by the AngularJS framework. The request is then analyzed by Node.js and translated into inputs that the web app can comprehend. These translated inputs are used by Express.js to select which requests to make to MongoDB, a non-relational NoSQL database. Once MongoDB has provided the required information, Express.js delivers the data back to Node.js, which then transmits it to the AngularJS framework, which displays the desired information in the user interface.

While other frontend frameworks, such as React.js, can be used in place of AngularJS, the Node.js environment is fundamental to the MEAN stack and cannot be replaced. This is because Node.js supports full-stack JavaScript development, which is a significant advantage that makes developing and managing applications using the MEAN stack extremely efficient. The stack is referred to as MERN when the AngularJS framework is replaced with React.js. Valeri Karpov, a MongoDB developer, coined the phrase “MEAN stack” in 2013.

Figure 2 shows a high-level example of how a web app replies across its MEAN stack to a user’s information request:

Figure 2: How a web app responds across the MEAN stack to fulfill a request.

What are the advantages and disadvantages of LAMP stack development?

Advantages of LAMP

Some advantages of utilizing LAMP to design, deploy, and maintain web applications are as follows:

  • Widespread support and trust: Because LAMP technologies have been utilized in numerous types of software development since the 1990s, they are universally trusted and supported by the open-source community. Many hosting services, for example, support PHP and MySQL.
  • Open-source technology: LAMP technologies are open source, which means they are freely available to developers. Because of its open-source technology, LAMP is also highly adaptable, allowing developers to choose the components that make the most sense for a given web app. PHP, for example, can employ a variety of compiler runtime engines, such as Zend or Laravel. LAMP can also take advantage of open-source databases like PostgreSQL.
  • Apache: The Apache web server is well-known for its dependability, speed, and security. It is also modular, making it extremely customizable.
  • Security: The LAMP stack has enterprise-grade security and encryption.
  • Efficiency: Because of its ease of modification, the LAMP stack can reduce app development time. For example, rather than writing code from scratch, programmers can start with an Apache module and modify it as needed.
  • Scalability: Because of its non-blocking structure, web apps designed, deployed, and managed with the LAMP stack are highly scalable and quick to develop.
  • Low maintenance: The LAMP stack ecosystem is reliable and requires little maintenance.
  • Comprehension: LAMP stack development is a fantastic alternative for novices because PHP and MySQL are reasonably simple to learn.

Disadvantages of LAMP

The following are some of the disadvantages of utilizing LAMP to design, deploy, and manage web applications:

  • Multiple languages: Because it necessitates the usage of various languages, LAMP is not termed “full-stack.” While PHP is used for server-side programming, JavaScript is utilized for client-side development. This indicates that a full-stack developer or many developers are needed.
  • Limited OS support: Only the Linux operating system and its derivatives, such as Oracle Linux, are supported by LAMP.
  • Monolithic architecture: While it is probably more secure than the cloud, LAMP systems are more monolithic than cloud-based architectures (cloud architectures are more scalable and affordable and return data quicker via APIs).

What are the advantages and disadvantages of MEAN stack development?

Advantages of MEAN

The following are some of the advantages of using MEAN to design, deploy, and manage web applications:

  • The use of a single language: MEAN is a “full-stack” application because it solely requires JavaScript. Switching between client-side and server-side code is now simple and efficient. A single JavaScript developer, for example, could theoretically create a whole web program.
  • Real-time updates and demonstrations: The technologies in the MEAN stack enable real-time upgrades to deployed web apps. Web app developers can also easily show the functionality of their creations.
  • Cloud compatibility: MEAN stack technologies can interact with cloud-based capabilities prevalent in current online services (such as calling on an API for data retrieval).
  • JSON files: MEAN lets users save papers as JSON files, which are optimized for quick data interchange across networks.
  • Efficiency: Developers can cut development time by using resources from public repositories and libraries. As a result, MEAN stack development is a low-cost solution that startups may find intriguing.
  • A fast runtime environment and ease of maintenance: The Node.js runtime is quick and responsive, while the Angular.js framework is simple to manage and test.
  • Cross-platform support: MEAN is a cross-platform stack, which means that its web applications may run on a variety of operating systems.

Disadvantages of MEAN

The following are some disadvantages of utilizing MEAN to design, deploy, and manage web applications:

  • Potential data loss: Because MongoDB requires a lot of memory for data storage, large-scale applications may face data loss. MongoDB also does not provide transactional functions.
  • Load times and incompatibility: On some devices, particularly older or low-end devices, JavaScript may cause websites or programs to load slowly. If JavaScript is disabled on a device, web apps may become unusable. Also, because older apps are unlikely to employ JavaScript, MEAN can be difficult to deploy in existing infrastructures.
  • High maintenance: Because the MEAN stack’s technologies are usually updated, web apps must be maintained regularly.

MEAN vs LAMP: Which is better?

Neither stack is superior to the other. However, the LAMP stack or MEAN stack may be more appropriate for a specific web development use case.

In general, the LAMP stack is the preferred option for online applications or sites that have the following characteristics:

  • Are broad in scope, static (needing no real-time updates), and will undergo high workflows with traffic surges.
  • Have a limited lifespan
  • Are they server-side?
  • Use a content management system (CMS) such as WordPress.

MEAN stack, on the other hand, is a better solution for web apps or sites like these:

  • Utilize current cloud technologies like APIs and microservices.
  • Have a lengthy life expectancy
  • Are more limited in focus and have regularly predictable traffic (decreasing the likelihood of data loss)
  • Require a significant amount of reasoning on the client-side

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

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5 Intelligent Automation Strategies to Address IT Skill Shortages

Posted on June 23, 2022July 26, 2022 by Marbenz Antonio

Automation: the Key to Future Business Efficiency - Velotrade Blog

Five strategic recommendations to help top IT talents thrive while also becoming more flexible and effective

IT is suffering from a serious skill shortage. Over 70% of IT executive respondents surveyed by IDC in Q1 2022 indicate that a lack of talent is a critical concern that is limiting progress toward technology modernization and transformation goals. That shortage isn’t going away anytime soon. According to the Gartner IT Spend Forecast for January 2022, 50% of tech jobs have been available for six months or more, and this trend is anticipated to continue.

Lack of IT staffing combined with high employee turnover rates results in institutional knowledge loss, manual process breakdowns, and unscheduled downtime. This causes new items to be delayed and leads to unhappy customers. Worse, the responsibility of everyday operations falls on existing IT staff, generating burnout and perpetuating the underlying problem.

By improving the employee experience, intelligent automation can help to prevent and mitigate staffing concerns. After all, IT success is about more than just recruiting outstanding people. It’s all about building a culture and an employee experience that keeps your best workers satisfied. Your finest people joined the industry to innovate, not to be dragged down with reactive obligations and operational overhead. Give them the tools they need by implementing IT solutions that automate routine operations, break down silos, and promote cooperation.

These five strategic ideas and related technologies can help to create the environment in which top tech talent thrives, allowing IT talent to be more efficient and scalable.

1. With automated application resource management, you can reduce human allocation and guesswork

Application resource management software is meant to examine every layer of an application’s resource use in real-time to guarantee that applications have what they need to execute when they need it.

How it improves IT employee experience: The traditional method of allocating application resources involves manual, time-consuming number crunching, as well as guessing and over-provisioning. IT teams can reclaim time from planning sessions for implementing revenue-generating functionality by automating many of the often-reactive procedures that burden your team (such as container-sizing and resource decisions).

How it benefits the business: Depending on the solution’s strength, application resource management software can securely lower cloud costs by up to 33% while improving application performance. By connecting your whole IT supply chain, from application to infrastructure, you can break down silos and transition away from manual allocations and guesswork and toward real-time, dynamic, and dependable resourcing across multi-cloud environments.

2. With observability and instant, detailed context, you can quickly understand the impact of code changes

APM and observability software is intended to provide comprehensive visibility into modern distributed applications to facilitate faster, automated problem identification and resolution. The more observable a system, the faster and more precisely you can navigate from an identified performance problem to its fundamental cause, without the need for further testing or code.

How it improves IT employee experience: Performance testing is essential for successful application development, but it usually necessitates significant manual effort on the part of employees, such as measuring the load time for a certain endpoint. Having a solution that can monitor the application ecosystem with continuous real-time discovery enables staff to find and fix issues more quickly, allowing items to reach the market faster. It also improves teamwork. With data-driven context, all teams can obtain visibility into the fundamental cause of an issue, decreasing time spent on debugging and root cause investigation.

How it benefits the business: Finally, the correct observability solution enables a company to bring better products to market faster. And, if you’re bringing more services to market faster than ever before — and deploying additional application components in the process — traditional APM’s once-a-minute data sampling can’t keep up. You can better manage the complexity of modern apps that span hybrid cloud landscapes with an enterprise observability solution, especially as demand for improved customer experiences and more applications influences business and IT operations.

3. Using proactive incident management, you can eliminate fire drills

Incident management is a very important process used by IT teams to respond to network outages or unexpected incidents. Organizations can reliably prioritize and address incidents faster with proactive incident management technologies, providing greater service to users.

How it improves IT employee experience: To effectively prepare for disruptions, IT must quickly assess, correlate, and learn from operational and unforeseen occurrences. However, the time spent confirming false alarms and handling large amounts of data causes staff exhaustion. Proactive incident management software can assist minimize up to 80% of employee time wasted on false positives, allowing teams to reclaim time for proactive problem solutions.

How it benefits the business: By reducing event noise and correlating large amounts of unstructured and structured data in real-time, you can proactively improve service quality, reduce potentially costly downtime, and improve user experience.

4. Optimize uptime and spend safely in real-time utilizing application resource management

Application resource management software ensures that apps have the resources they require to function properly. It can help organizations save money on cloud and infrastructure costs in addition to saving teams from manual provisioning.

How it improves IT employee experience: IT teams may turn their focus to innovation and reclaim time to deliver better customer experiences when apps run on autopilot.

How it benefits the business: Application resource management technologies may ensure performance while saving cloud and infrastructure costs by offering apps what they need when they need it (and nothing more).

5. Using license and resource management solutions, you can automate license compliance (and more)

Software licensing management technologies enable you to track and evaluate how software is handled across the organization to ensure licenses are properly maintained. This optimizes your licensing system and increases revenue.

How it improves IT employee experience: Because of the complexities of hybrid IT environments, software, hardware, and cloud solutions from a range of suppliers are frequently required. Managing these solutions places a burden on limited IT resources by requiring them to correlate insights across platforms, regulate license prices, and optimize resource investments, not to mention maintain license compliance to avoid penalties and eliminate security risks. License and resource management systems automate the manual duties of software license and resource optimization, allowing IT professionals to focus on proactive software portfolio optimization.

How it benefits the business: You can use license and resource management tools to avoid over-allocating resources to support license workloads, avoid end-of-service outages, reduce security vulnerabilities with improved version management, and help mitigate the risk of penalties from software non-compliance to reduce surprise billings.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in IBMTagged IBM Cloud Services, IBM TrainingLeave a Comment on 5 Intelligent Automation Strategies to Address IT Skill Shortages

So you want to be a CISO: Here’s what you need to know about data security

Posted on June 22, 2022July 26, 2022 by Marbenz Antonio

5 key challenges being faced by CISOs right now - Security Risk Management

Any organization’s lifeblood is data. Protecting sensitive corporate data will be your priority, whether you’re a Chief Information Security Officer (CISO) or want to be one. But things aren’t getting any easier. In 2021, the number of data breaches surged by 68% to 1,862, costing an average of USD4.24 million each. The damage from a breach affects everyone, creating lower brand equity and consumer trust, decreased shareholder confidence, failed audits, and greater regulatory attention.

It’s easy to become so focused on preventing the next ransomware attack that you ignore risks within your own business. Insider data leaks, intellectual property (IP) theft, fraud, and regulatory violations—any of these may bring a firm (and your career) crashing down as swiftly as a headline-grabbing breach. Given the scope of today’s digital estate—on-premises, in the cloud, and at the edge—Microsoft Purview provides the inside-out, integrated strategy that an effective CISO requires to prevent internal and external data breaches. Here are some things to think about when setting priorities for yourself and communicating with your board of directors.

Mind your own house—insider threats

As the “Great Resignation” or “Great Reshuffle” continues, organizations around the world are dealing with increasing numbers of people attempting to flee climbing aboard. According to Microsoft’s most recent Work Trend Index, 43% of employees are likely to explore changing employment in the coming year. This major movement in employment status has been accompanied by the “Great Exfiltration,” in which many transitional employees may leave with sensitive data stored on personal devices or accessed through a third-party cloud, whether purposefully or unintentionally. In 2021, 15% of workers uploaded more corporate data to personal cloud apps than in 2020. Worryingly, in 2021, 8% of departing employees uploaded more than 100 times their average data volume.

As a CISO, you are in charge of data that is scattered across multiple platforms, devices, and workloads. You must consider how that technology interacts with the business processes of your corporation. This includes putting procedures in place to prevent data exfiltration, which is especially important if you work in a regulated field like finance or healthcare. It begins with the question, “Who has access to the data?” Where should the data be stored (or not stored)? How may the information be used? How can we avoid oversharing? A cloud-native and complete data loss prevention (DLP) solution allows you to centrally manage all of your DLP policies across cloud services, devices, and on-premises file shares. Even better, no new infrastructure or agents are required for this form of unified DLP solution, which helps to keep costs down. Even in an era of rapid change, today’s workplace necessitates the freedom of employees to produce, manage and exchange data across platforms and services. However, when it comes to mitigating user threats, the businesses for which they work are frequently bound by limited resources and rigorous privacy regulations. As a result, you’ll require technologies capable of analyzing insider threats and providing integrated detection and investigation capabilities. Insider dangers will be best addressed by:

  • Transparent – using privacy-by-design architecture, you may balance user privacy with organizational risk.
  • Configurable – regulations that are enabled based on your industry, geographical location, and business groups
  • Integrated – maintaining a workflow that is connected throughout all of your data, regardless of where it resides
  • Actionable – enabling reviewer notifications, data investigations, and user investigations

Insider threat protection should comprise templates and policy requirements that determine which triggering events and risk indicators require investigation. As a result, your insider-risk solution should be able to identify potential risk trends across the business and analyze problematic behavior using end-to-end workflows. Furthermore, a solution that aids in the detection of code of conduct violations (harassing or threatening language, adult content, and the sharing of sensitive information) can be a solid indicator of potential insider threats. Machine learning will assist in providing more context surrounding specific words or key phrases, allowing investigators to expedite remediation.

Automate and integrate your data strategy

Because many organizations are afraid to commit to a single provider, most CISOs must deal with data spread over a patchwork of on-premises and cloud storage. Legacy data silos are an unfortunate part of life. If massive quantities of “dark data” are not accurately identified as sensitive, protecting personally identifiable information (PII) or sensitive company IP and implementing data loss prevention strategies becomes challenging. A frugal CISO should simplify wherever possible, relying on a complete solution to protect the entire digital estate. A good data management solution should allow users to manually classify their documents while also allowing system administrators to use auto-labeling and machine learning-trainable classifiers.

  • Data discovery: It is not uncommon for an employee to unintentionally store a customer’s Social Security Number (SSN) on an unsecured site or a third-party cloud. That is why you will need a data management solution, such as PII, that automatically identifies sensitive data using built-in sensitive information types and regulatory policy templates, such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act of 1996. (HIPAA). Because sensitive data might end up everywhere, the proper solution must employ automation to cast a wide net over on-premises, multi-cloud, operational, and software as a service (SaaS) data.
  • Data classification: Look for consistent built-in labeling that is already integrated with widely used applications and services, allowing users to further customize sensitivity levels for their requirements. The ideal system should also support automatic labeling and policy enforcement across an organization, allowing for speedier classification and data loss prevention deployment at the enterprise scale. Also, look for unified data management systems that detect and classify sensitive data located on-premises, in multi-cloud, and in SaaS to develop a holistic map of your entire data estate.
  • Data governance: You want your organization’s data to be discoverable, trustworthy, and stored in a secure location. Keeping data for longer than necessary raises your risk of exposure in the event of a breach. On the other hand, removing data too quickly can expose your company to regulatory penalties. Data retention, records management, and machine learning technologies help you control risk and liability by classifying data and automatically applying lifecycle policies, allowing you to store only the data you need and delete what you don’t.

Make data protection a team effort

A primary role of any CISO is to secure the organization’s intellectual property (IP), which includes software source code, patented designs, creative works, and anything else that offers the company a competitive advantage. However, as big data grows and legal standards change, CISOs are expected to protect user data such as PII, personal health information (PHI), and payment card industry (PCI) data. Privacy regulations are also tightening constraints on how user data is used, kept, and stored, both internally and with third-party providers.

Additionally, hybrid and multi-cloud services introduce new issues by dispersing data’s geographic origins, storage location, and user access points. Today’s CISO must collaborate with colleagues in data protection, privacy, information technology, human resources, legal, and compliance, which means you may share responsibilities with a Chief Data Officer (CDO), Chief Risk Officer (CRO), Chief Compliance Officer (CCO), and Chief Information Officer (CIO). That is a lot of acronyms on one table. Rather than duplicating efforts or competing for territory, a good CISO should implement a single data protection solution that eliminates potential redundancies and keeps your whole security team on the same page.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in MicrosoftTagged Microsoft1 Comment on So you want to be a CISO: Here’s what you need to know about data security

An introduction to post-quantum cryptography

Posted on June 22, 2022July 26, 2022 by Marbenz Antonio

Explainer: What is post-quantum cryptography? | MIT Technology Review

What is post-quantum cryptography?

Many of our present cryptographic techniques can be broken by a new sort of computer that is being created. As a result, we must create new algorithms that are secure against such machines while yet running on our present systems. This is known as “post-quantum cryptography.”

What is a quantum computer?

Richard Feynman proposed a new way of analyzing quantum interactions in complicated systems in 1981. When modeling these interactions, however, there is a challenge in that we must represent each connected particle as a set of probabilities. These arrays increase exponentially as we add particles. Existing computers can no longer match the storage and time needs of any sufficiently large system.

Feynman’s solution is straightforward: construct a computer that uses entangled quantum particles to mimic the physical item of interest. A computer of this type might efficiently perform a variety of tasks, including determining how to take advantage of changing entangled quantum states.

What is a qubit?

The concept behind a quantum computer is to replace traditional bits with “qubits.” Classical bits may only be 0 or 1, whereas a qubit has a chance of being 1 or 0, which is commonly represented as a unit vector in three-dimensional space. The qubit’s power comes from many bits that are entangled with one another. You can force these bits to take on the state of your answer quickly if you can create an algorithm in which these qubits interfere with each other in the solution to your problem.

What do quantum computers have to do with cryptography?

When Feynman suggested quantum computers, such a machine was beyond anyone’s abilities to create, but researchers looked into not just how such a computer could be built, but also how it could be used.

Peter Shor discovered an algorithm in 1994 that might be used with a quantum computer to defeat the RSA and Diffie Hellman encryption systems. Shor’s approach was later modified to defeat ECC (Elliptic Curve Cryptography). These algorithms serve as the foundation for all of our public key exchange and digital signature algorithms. We understood from then on that our major public-key systems were only secure until someone created a sufficiently massive, functional quantum computer.

With current classical algorithms possibly compromised, we will require new algorithms based on challenges that are difficult to solve with quantum computers, which is where post-quantum cryptography comes in. These algorithms operate on conventional computers and are based on issues that neither a classical nor a quantum computer can solve.

Why should you be interested in post-quantum cryptography?

Cryptography is common in today’s environment. When you input your credit card number on the web, it is protected by an encrypted channel that depends on both a digital signature (to ensure that you are sending the credit card to the proper vendor) and a public key exchange (to agree on a set of keys used between client and server to encrypt your communication). If a sufficiently massive quantum computer is created, none of the security guarantees provided by Transport Layer Security (TLS) can be relied on. Some disk encryption methods additionally employ public keys to enable recovery solutions if your users forget their passwords.

One of the most important implications for the common individual is that they must recognize the systems they utilize that may be susceptible. This is very important in business IT.

When do you need to care?

Every post-quantum cryptography presentation and publication addresses this question with Mosca’s Theorem:

Post-quantum cryptography - Mosca's Theorem

If the total the time required to migrate to the new method (y) and the time required to keep the secret (x) exceeds the time remaining before we have a quantum computer capable of breaking our public key algorithm (z), your data will be compromised before its usefulness expires. The issue is that many of these figures are subject to doubt.

The duration required to maintain the secret (x) is generally determined by the application. For your credit card on the internet, for example, this may be two or three years, depending on the expiration date of your card. In the case of medical data, though, it may take decades.

This is complicated further by the fact that certain organizations (both public and private) have begun recording TLS sessions, so even if the TLS session is brief, the data in that connection may be retained and decrypted in the future. So, if you’re conducting assistance work in an authoritarian nation and dealing with people who may be incarcerated for cooperating with you, you probably don’t want to trust sending their names or other identifying information through a VPN or TLS connection. You have control over this time value, but you must consider how long you need to keep specific data hidden and from what kind of entities.

The deployment process can be time-consuming (y), beginning with standards and progressing to actual deployment. It might be decades in certain cases. For years, the cryptography community has been working on new standards proposals, which are only now expected to be standardized. The only control you have here is deciding how soon to implement algorithms and protocols on your systems once they are ready.

The greatest uncertainty at this moment is when we will have quantum computers capable of breaking our present algorithms (z). In 2015, Michael Mosca, a quantum computing researcher at the University of Waterloo, calculated that 2048-bit RSA will be susceptible by 2026, with a 50% chance of being vulnerable by 2031. In 2017, he revised it to a 1/6 probability that 2048 will be compromised by 2027. The development of quantum computers has accelerated, with firms such as IBM and Google creating tiny, experimental quantum computers to help address some of the most difficult challenges that they and their customers have.

The bottom line is that there are some things you should be concerned about right now, but others you shouldn’t until we have post-quantum algorithms in place.

Why aren’t post-quantum algorithms deployed already?

The cryptographic community has been aware of these concerns for some time. The good news is that various new algorithms are available to replace our present key exchange and signature methods. The bad news is that all well-studied methods have significant deployment hurdles, particularly big key sizes or encrypted data/signature sizes, or both (In some cases megabits large). The community has spent the last decade investigating some of the more promising new algorithms that do not rely on huge keys and data blobs. In future postings, I’ll go into these families in greater detail, but for now, just a few facts.

The National Institute of Standards and Technology (NIST) launched the Post-Quantum Cryptography Standardization process in 2016 to gather and assess possible algorithms. They got 82 entries, with 69 deemed complete by the end of 2017. These were reviewed in 2018, and 30 algorithms were chosen at the start of this year for further improvement and assessment through 2019.

In that time frame, some of the other initial 69 algorithms were broken, and 26 of the original 69 algorithms were chosen for round two. NIST chose seven finalists and eight alternates for 2020. Three of these 15 algorithms have since been broken. The number of faulty algorithms demonstrates the value of moving slowly.

We anticipate that NIST will reach a final decision in 2022 and will then begin the standardization process. After that, protocols such as TLS may pick them up and suppliers can begin to install them.

What should I do?

You should first identify any current use of possibly flawed algorithms and verify whether they are protecting long-term data. This suggests you should reconsider your usage of:

  • RSA, DSA, ECC, and DH – an actually vulnerable algorithms
  • TLS, SSH, S/MIME, PGP, IPSEC – protocols that depend on these risky algorithms
  • VPNs, Kerberos – protocols that may depend on these vulnerable algorithms
  • Browsers, encrypted messaging, disk encryption, authentication schemes – applications that may (or may not) use these protocols or risky algorithms

You want to:

  1. Ensure that users are not trying to protect long-term data.
  2. Make a strategy for replacing risky algorithms with post-quantum algorithms when they become available. Prioritize the systems that hold or transmit your most sensitive information. This will almost certainly necessitate upgrading your previous operating systems, as well as maybe your old hardware.
  3. Identify systems over which you have no control (third-party websites, for example) and devise a strategy for reducing your exposure to their systems.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in Red HatTagged Red HatLeave a Comment on An introduction to post-quantum cryptography

On-demand: Intel and Azure are creating a much-protected cloud

Posted on June 22, 2022July 26, 2022 by Marbenz Antonio

Infonuagique – Infonuagique et technologie

Intel webinar overview

Intel and Microsoft Azure building a more secure cloud

Cloud-to-edge solutions from Intel and Microsoft use the power of Intel technology and the Microsoft Azure cloud.

Together, Intel and Microsoft Azure are advancing cloud adoption by providing feature-rich, easy-to-deploy, secure, cloud solutions to market.

To discover more about the Microsoft Azure and Intel cooperation, watch this webinar.

  • Intel’s value in the cloud
  • Intel and Azure cloud partnership
  • Specific features and instances that bring value to your customers
  • Q&A

Intel and Microsoft Azure have formed a relationship that empowers customers, partners, and sellers at every level of the cloud solution lifecycle.

Why Intel?

  • Security for multitenancy: Securing business data is a primary goal for the Azure cloud, and Intel contributes to secure environments by enabling hardware-enabled features that offer a foundation of trust and support private computing.
  • Performance per cost: Intel and Azure Cloud collaborate to provide cutting-edge technologies, toolkits, and optimizations to help guarantee that cloud infrastructure operates at peak efficiency. Your customers will benefit from quick results and inexpensive rental prices for high-performance virtual computers.
  • Access the latest technology: Businesses of all sizes may leverage limited operational resources to gain access to a wide range of Azure cloud virtual machines allowed by high-end SKUs. This implies that your customers may take advantage of the most recent Intel® Xeon® Scalable CPU platforms and other Intel technologies without making a large capital commitment.

 


Here at CourseMonster, we know how hard it may be to find the right time and funds for training. We provide effective training programs that enable you to select the training option that best meets the demands of your company.

For more information, please get in touch with one of our course advisers today or contact us at training@coursemonster.com

Posted in MicrosoftTagged Microsoft, Microsoft Azure1 Comment on On-demand: Intel and Azure are creating a much-protected cloud

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