It’s hard to find a person who uses the internet but doesn’t enjoy at least one cloud computing service. “Cloud computing” sounds complex, but it’s actually all around you. The term encompasses every tool, app, and service that’s delivered via the internet.


The two popular examples are Dropbox and Google Drive. These cloud-based storage spaces allow you to keep your files at arm’s reach and access them in a few clicks. Zoom is also a cloud-based service – it makes communication a breeze.


Cloud computing can be classified into four types: public, private, hybrid, and community. These four types belong to one of the three cloud computing service models: infrastructure as a service, platform as a service, or software as a service.


It’s time to don a detective cap and explore the mystery hidden behind cloud computing.


Cloud Computing Deployment Models


  • Public cloud
  • Private cloud
  • Hybrid cloud
  • Community cloud

Public Cloud


The “public” in public cloud means anyone who wants to use that service can get it. Public clouds are easy to access and usually have a “general” purpose many can benefit from.


It’s important to mention that with public clouds, the infrastructure is owned by the service provider, not by consumers. This means you can’t “purchase” a public cloud service forever.


Advantages of Public Cloud


  • Cost-effectiveness – Some public clouds are free. Those that aren’t free typically have a reasonable fee.
  • Scalability – Public clouds are accommodating to changing demands. Depending on the cloud’s nature, you can easily add or remove users, upgrade plans, or manipulate storage space.
  • Flexibility – Public clouds are suitable for many things, from storing a few files temporarily to backing up an entire company’s records.

Disadvantages of Public Cloud


  • Security concerns – Since anyone can access public clouds, you can’t be sure your data is 100% safe.
  • Limited customization – While public clouds offer many options, they don’t really allow you to tailor the environment to match your preferences. They’re made to suit broad masses, not particular individuals.

Examples of Public Cloud Providers


  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform

Private Cloud


If you’re looking for the complete opposite of public clouds, you’ve found it. Private clouds aren’t designed to fit general criteria. Instead, they’re made to please a single user. Some of the perks private clouds offer are exclusive access, exceptional security, and unmatched customization.


A private cloud is like a single-tenant building. The tenant owns the building and has complete control to do whatever they want. They can tear down walls, drill holes to hang pictures, paint the rooms, install tiles, and get new furniture. When needs change, the tenant can redecorate, no questions asked.


Advantages of Private Cloud


  • Enhanced security – The company’s IT department oversees private clouds. They’re usually protected by powerful firewalls and protocols that minimize the risk of information breaches.
  • Greater control and customization – Since private clouds are one-on-one environments, you can match them to your needs.
  • Improved performance – Private clouds can have functions that suit your organization to the letter, resulting in high performance.

Disadvantages of Private Cloud


  • Higher costs – The exclusive access and customization come at a cost (literally).
  • Limited scalability – You can scale private clouds, but only up to a certain point.

Examples of Private Cloud Providers


  • VMware
  • IBM Cloud
  • Dell EMC

Hybrid Cloud


Public and private clouds have a few important drawbacks that may be deal-breakers for some people. You may want to use public clouds but aren’t ready to compromise on security. On the other hand, you may want the perks that come with private clouds but aren’t happy with limited scalability.


That’s when hybrid clouds come into play because they let you get the best of both worlds. They’re the perfect mix of public and private clouds and offer their best features. You can get the affordability of public clouds and the security of private clouds.


Advantages of Hybrid Cloud


  • Flexibility and scalability – Hybrid clouds are personalized environments, meaning you can adjust them to meet your specific needs. If your needs change, hybrid clouds can keep up.
  • Security and compliance – You don’t have to worry about data breaches or intruders with hybrid clouds. They use state-of-the-art measures to guarantee safety, privacy, and security.
  • Cost optimization – Hybrid clouds are much more affordable than private ones. You’ll need to pay extra only if you want special features.

Disadvantages of Hybrid Cloud


  • Complexity in management – Since they combine public and private clouds, hybrid clouds are complex systems that aren’t really easy to manage.
  • Potential security risks – Hybrid clouds aren’t as secure as private clouds.

Examples of Hybrid Cloud Providers


  • Microsoft Azure Stack
  • AWS Outputs
  • Google Anthos

Community Cloud


Community clouds are shared by more than one organization. The organizations themselves manage them or a third party. In terms of security, community clouds fall somewhere between private and public clouds. The same goes for their price.


Advantages of Community Cloud


  • Shared resources and costs – A community cloud is like a common virtual space for several organizations. By sharing the space, the organizations also share costs and resources.
  • Enhanced security and compliance – Community clouds are more secure than public clouds.
  • Collaboration opportunities – Cloud sharing often encourages organizations to collaborate on different projects.

Disadvantages of Community Cloud


  • Limited scalability – Community clouds are scalable, but only to a certain point.
  • Dependency on other organizations – As much as sharing a cloud with another organization(s) sounds exciting (and cost-effective), it means you’ll depend on them.

Examples of Community Cloud Providers


  • Salesforce Community Cloud
  • Rackspace
  • IBM Cloud for Government

Cloud Computing Service Models


There are three types of cloud computing service models:


  • Infrastructure as a Service (IaaS)
  • Platform as a Service (PaaS)
  • Software as a Service (SaaS)

IaaS


IaaS is a type of pay-as-you-go, third-party service. In this case, the provider gives you an opportunity to enjoy infrastructure services for your networking equipment, databases, devices, etc. You can get services like virtualization and storage and build a strong IT platform with exceptional security.


IaaS models give you the flexibility to create an environment that suits your organization. Plus, they allow remote access and cost-effectiveness.


What about their drawbacks? The biggest issue could be security, especially in multi-tenant ecosystems. You can mitigate security risks by opting for a reputable provider like AWS or Microsoft (Azure).


PaaS


Here, the provider doesn’t deliver the entire infrastructure to a user. Instead, it hosts software and hardware on its own infrastructure, delivering only the “finished product.” The user enjoys this through a platform, which can exist in the form of a solution stack, integrated solution, or an internet-dependent service.


Programmers and developers are among the biggest fans of PaaS. This service model enables them to work on apps and programs without dealing with maintaining complex infrastructures. An important advantage of PaaS is accessibility – users can enjoy it through their web browser.


As far as disadvantages go, the lack of customizability may be a big one. Since you don’t have control over the infrastructure, you can’t really make adjustments to suit your needs. Another potential drawback is that PaaS depends on the provider, so if they’re experiencing problems, you could too.


Some examples of PaaS are Heroku and AWS Elastic Beanstalk.


SaaS


Last but not least is SaaS. Thanks to this computing service model, users can access different software apps using the internet. SaaS is the holy grail for small businesses that don’t have the budget, bandwidth, workforce, or will to install and maintain software. Instead, they leave this work to the providers and enjoy only the “fun” parts.


The biggest advantage of SaaS is that it allows easy access to apps from anywhere. You’ll have no trouble using SaaS as long as you have internet. Plus, it saves a lot of money and time.


Nothing’s perfect, and SaaS is no exception. If you want to use SaaS without interruptions, you need to have a stable internet connection. Plus, with SaaS, you don’t have as much control over the software’s performance and security. Therefore, you need to decide on your priorities. SaaS may not be the best option if you want a highly-customizable environment with exceptional security.


The most popular examples of SaaS are Dropbox, Google Apps, and Salesforce.



Sit on the Right Cloud


Are high security and appealing customization features your priority? Or are you on the hunt for a cost-effective solution? Your answers can indicate which cloud deployment model you should choose.


It’s important to understand that models are not divided into “good” and “bad.” Each has unique characteristics that can be beneficial and detrimental at the same time. If you don’t know how to employ a particular model, you won’t be able to reap its benefits.

Related posts

Agenda Digitale: Generative AI in the Enterprise – A Guide to Conscious and Strategic Use
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 31, 2025 6 min read

Source:


By Zorina Alliata, Professor of Responsible Artificial Intelligence e Digital Business & Innovation at OPIT – Open Institute of Technology

Integrating generative AI into your business means innovating, but also managing risks. Here’s how to choose the right approach to get value

The adoption of generative AI in the enterprise is growing rapidly, bringing innovation to decision-making, creativity and operations. However, to fully exploit its potential, it is essential to define clear objectives and adopt strategies that balance benefits and risks.

Over the course of my career, I have been fortunate to experience firsthand some major technological revolutions – from the internet boom to the “renaissance” of artificial intelligence a decade ago with machine learning.

However, I have never seen such a rapid rate of adoption as the one we are experiencing now, thanks to generative AI. Although this type of AI is not yet perfect and presents significant risks – such as so-called “hallucinations” or the possibility of generating toxic content – ​​it fills a real need, both for people and for companies, generating a concrete impact on communication, creativity and decision-making processes.

Defining the Goals of Generative AI in the Enterprise

When we talk about AI, we must first ask ourselves what problems we really want to solve. As a teacher and consultant, I have always supported the importance of starting from the specific context of a company and its concrete objectives, without inventing solutions that are as “smart” as they are useless.

AI is a formidable tool to support different processes: from decision-making to optimizing operations or developing more accurate predictive analyses. But to have a significant impact on the business, you need to choose carefully which task to entrust it with, making sure that the solution also respects the security and privacy needs of your customers .

Understanding Generative AI to Adopt It Effectively

A widespread risk, in fact, is that of being guided by enthusiasm and deploying sophisticated technology where it is not really needed. For example, designing a system of reviews and recommendations for films requires a certain level of attention and consumer protection, but it is very different from an X-ray reading service to diagnose the presence of a tumor. In the second case, there is a huge ethical and medical risk at stake: it is necessary to adapt the design, control measures and governance of the AI ​​to the sensitivity of the context in which it will be used.

The fact that generative AI is spreading so rapidly is a sign of its potential and, at the same time, a call for caution. This technology manages to amaze anyone who tries it: it drafts documents in a few seconds, summarizes or explains complex concepts, manages the processing of extremely complex data. It turns into a trusted assistant that, on the one hand, saves hours of work and, on the other, fosters creativity with unexpected suggestions or solutions.

Yet, it should not be forgotten that these systems can generate “hallucinated” content (i.e., completely incorrect), or show bias or linguistic toxicity where the starting data is not sufficient or adequately “clean”. Furthermore, working with AI models at scale is not at all trivial: many start-ups and entrepreneurs initially try a successful idea, but struggle to implement it on an infrastructure capable of supporting real workloads, with adequate governance measures and risk management strategies. It is crucial to adopt consolidated best practices, structure competent teams, define a solid operating model and a continuous maintenance plan for the system.

The Role of Generative AI in Supporting Business Decisions

One aspect that I find particularly interesting is the support that AI offers to business decisions. Algorithms can analyze a huge amount of data, simulating multiple scenarios and identifying patterns that are elusive to the human eye. This allows to mitigate biases and distortions – typical of exclusively human decision-making processes – and to predict risks and opportunities with greater objectivity.

At the same time, I believe that human intuition must remain key: data and numerical projections offer a starting point, but context, ethics and sensitivity towards collaborators and society remain elements of human relevance. The right balance between algorithmic analysis and strategic vision is the cornerstone of a responsible adoption of AI.

Industries Where Generative AI Is Transforming Business

As a professor of Responsible Artificial Intelligence and Digital Business & Innovation, I often see how some sectors are adopting AI extremely quickly. Many industries are already transforming rapidly. The financial sector, for example, has always been a pioneer in adopting new technologies: risk analysis, fraud prevention, algorithmic trading, and complex document management are areas where generative AI is proving to be very effective.

Healthcare and life sciences are taking advantage of AI advances in drug discovery, advanced diagnostics, and the analysis of large amounts of clinical data. Sectors such as retail, logistics, and education are also adopting AI to improve their processes and offer more personalized experiences. In light of this, I would say that no industry will be completely excluded from the changes: even “humanistic” professions, such as those related to medical care or psychological counseling, will be able to benefit from it as support, without AI completely replacing the relational and care component.

Integrating Generative AI into the Enterprise: Best Practices and Risk Management

A growing trend is the creation of specialized AI services AI-as-a-Service. These are based on large language models but are tailored to specific functionalities (writing, code checking, multimedia content production, research support, etc.). I personally use various AI-as-a-Service tools every day, deriving benefits from them for both teaching and research. I find this model particularly advantageous for small and medium-sized businesses, which can thus adopt AI solutions without having to invest heavily in infrastructure and specialized talent that are difficult to find.

Of course, adopting AI technologies requires companies to adopt a well-structured risk management strategy, covering key areas such as data protection, fairness and lack of bias in algorithms, transparency towards customers, protection of workers, definition of clear responsibilities regarding automated decisions and, last but not least, attention to environmental impact. Each AI model, especially if trained on huge amounts of data, can require significant energy consumption.

Furthermore, when we talk about generative AI and conversational models , we add concerns about possible inappropriate or harmful responses (so-called “hallucinations”), which must be managed by implementing filters, quality control and continuous monitoring processes. In other words, although AI can have disruptive and positive effects, the ultimate responsibility remains with humans and the companies that use it.

Read the full article below (in Italian):

Read the article
Medium: First cohort of students set to graduate from Open Institute of Technology
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 31, 2025 4 min read

Source:

  • Medium, published on March 24th, 2025

By Alexandre Lopez

The first ever cohort will graduate from Open Institute of Technology (OPIT) on 8th March 2025, with 40 students receiving a Master of Science degree in Applied Data Science and AI.

OPIT was launched two years ago by renowned edtech entrepreneur Riccardo Ocleppo and Prof. Francesco Profumo (former minister of education in Italy), who witnessed the growing tech skills gap and wanted to combat it directly through creating a brand-new, accredited academic institution focused on innovative BSc and MSc degrees in the field of Technology.

The higher education institution has grown since its initial launch. Having started with just two degrees on offer — BSc in Modern Computer Science and an MSc in Applied Data Science and Artificial Intelligence — OPIT now offers two bachelor’s and four master’s degrees in a range of areas, such as Computer Science, Digital Business, Artificial Intelligence and Enterprise Cybersecurity.

Students at OPIT can learn from a wide range of professors who combine academic and professional expertise in software engineering, cloud computing, AI, cybersecurity, and much more. The institution operates on a fully remote system, with over 300 students tuning in from 78 countries around the world.

80% of OPIT’s students are already working professionals who are currently employed at top companies across many industries. They are in global tech firms like Accenture, Cisco, and Broadcom and financial companies such as UBS, PwC, Deloitte, and First Bank of Nigeria. Some are leading innovation at Dynatrace and Leonardo, while others focus on sustainability and social impact with Too Good To Go, Caritas, and the Pharo Foundation. From AI and software development to healthcare and international organizations like NATO and the United Nations Mine Action Service (UNMAS), OPIT alumni are making a real difference in the world.

OPIT is working on the development of the expansion of our current academic offerings, new courses, doctoral programs, applied research, and technology transfer initiatives with companies.

Once in the program, students have flexible options to complete their studies faster (by studying during the summer) or extend their studies longer than the standard duration. Every OPIT degree ends with a “capstone project”, providing them with real-life experiences in relevant businesses and industries. Some examples of capstone projects include “AI in Anti-Money Laundering: Leveraging AI to combat financial crime,” or “Predictive Modeling for Climate Disasters: Using AI to anticipate climate-related emergencies.”

The graduation on March 8th marks a pivotal moment for OPIT.

“The success of this first class of graduates marks a significant milestone for OPIT and reinforces our mission: to provide high-quality, globally accessible tech education that meets the ever-evolving demands of the job market,” said Riccardo Ocleppo, founder of OPIT.

“In just two years, we have built a dynamic and highly professional learning environment, attracting students from all over the world and connecting them with leading companies.”

Read the full article below:

Read the article