#Datacenter Management

[pulsaris]

O alojamento de Internet adequado para o seu projecto.

Os nossos planos de "Managed Web Hosting" estão disponíveis a partir de 12,50€ por mês (+ IVA) e nas versões mais básicas incluem a gestão integrada dos recursos que estão directamente afectos à solução de alojamento. Face a soluções concorrentes, esta característica distinta é, por si só, a opção acertada para clientes que procuram assegurar a sustentabilidade dos seus projectos e optimizar uma grande parte do seu investimento neste género de serviços e de infra-estruturas tecnológicas.

Informação detalhada disponível em: https://www.pulsaris.pt/alojamento-de-internet/index.html

[govindhtech]

Public Sector Cloud Computing Challenges and Opportunities

The difficulties and possibilities of using cloud computing to public sector

Government cloud computing usage is driven by the epidemic. As cloud computing grows increasingly widespread, government, educational, and healthcare institutions will undergo a major transformation. The recent and revolutionary transition to cloud computing, which has both and cons, may reduce public sector efficiency.

How is the public sector using cloud computing?

Cloud computing reduces costs, improves service delivery, and boosts efficiency in the public sector. In addition to personal information, they manage and preserve a large amount of research data. Solutions for cloud storage provide scalable and efficient data management.

Infrastructure as a Service (IaaS)

The government offers online citizen services, online tax filing, online benefit applications, and online permit issuance.Citizens may use these services anytime, anywhere.It no longer requires expensive on-site data centers and infrastructure. Because cloud computing is more agile, scalable, and affordable, the public sector can better meet citizen and government demands.

It becomes clear that the cutting-edge technology known as cloud computing has a big influence on the public sector. This article examines the promise and issues of cloud computing to help readers better understand how it is transforming the public sector.

Cloud Computing’s Challenges for the Public Sector

Cloud Security

This is the main barrier preventing the public sector from adopting cloud computing. Since they handle sensitive data, government agencies are vulnerable to severe security breaches. To protect sensitive data, public sector enterprises must ensure that cloud service providers use data encryption, access limits, and periodic security audits.

Public Cloud Services

Platforms for cloud computing could be difficult to integrate with legacy systems that the public sector often uses. Integrated systems may be challenging and time-consuming. Planning is required for data transfer, system integration, and migration techniques in order to prevent interruptions and ensure smooth operations.

Cost Management

Staff training and the switch to cloud-based solutions might have short-term financial expenses, but using cloud-based solutions could result in long-term cost savings.

Platform as a Service (PaaS)

Vendor lock-in is a risk while using the infrastructure and services of a single cloud provider. To avoid over-reliance, public sector organizations must be cautious when choosing a supplier.

A variety of legal and regulatory issues might arise from the usage of cloud computing in the public sector. It becomes essential to follow laws pertaining to data residency, privacy, and industry-specific requirements. Public sector companies need to thoroughly assess cloud providers to make sure they follow the necessary compliance criteria.

Prospects for Cloud Computing in the Public Sector

1. The ability to climb

Cloud services help government organizations adapt quickly to changing workloads, particularly in times of crisis or increased demand.

2. Reduced Outlays

There are many ways that cloud computing may be used by the public sector to save IT expenses. For example, cloud companies may provide economies of scale by dividing the cost of infrastructure across several clients. Cloud service providers often provide more economical and efficient means of delivering IT services.

3. Enhanced Safety

Public sector organizations utilize cloud computing to strengthen their security protocols since it has several features that assist safeguard data and systems. Cloud service providers may provide services like data encryption, access control, and disaster recovery.

4. Government Cloud Initiatives

Cloud services were crucial during the COVID-19 pandemic because they allowed users to access vital apps and data from a distance. This enables improved provision of government services to personnel and clients from any place.

5. Disaster Recovery

The reliable disaster recovery solutions offered by cloud-based services enable the fast restoration of government data and services in the event of an emergency or outage.

The public sector has completely modernized thanks to cloud computing, which has altered how government organizations run and communicate with the general public. The significant potential of cloud computing may assist public sector organizations make data-driven decisions, optimize operations, and enhance service delivery.

Data Privacy

Many opportunities, but also unique obstacles. Due to vendor lock-in, pricing limits, data security and privacy, and regulatory compliance, strategic planning is essential. Public sector enterprises must establish a balance between these complicated issues and cloud computing.

FAQS

What is public cloud advantages and disadvantages?

Less expensive: The primary benefit of choosing third-party public cloud providers is that you can avoid managing services internally or having to buy your own servers. This lowers overhead and expenses related to IT. The cloud provider you are utilizing will update and manage your servers, so you won’t need to do that anymore.

What are the benefits and challenges of cloud computing?

1.Cloud Computing’s Scalability and Flexibility Benefits 2.Economy of Cost 3.Enhanced Cooperation and Availability 4.Strengthened Security and Resilience to Disasters 5.Service dependability, vendor lock-in, and data security and privacy 6.Limitations on Data Transfer and Bandwidth 7.Compliance to Guidelines

What are the benefits of public cloud cost?

Indeed, according to 39% of businesses, using the cloud allowed them to completely save costs. Access to pre-built infrastructure reduces redundancy and saves time, which lowers labor and operational expenses.

Read more on Govindhtech.com

[kremlin]

it is really, really funny to see these bush-league never-was dumbfuck crypto losers go out and spend $300k of borrowed money on gray market A100s in an attempt to mine cryptocurrency (which they will have no success with) just solely on the premise that those things are called "GPUs"

i was reading one account of a guy on reddit with a throwaway account freaking out because he bought SXM socket A100s which, like, it was pretty clear his thinking was that because he could manage to put together a embarrassing gamer PC, he would have no trouble with this. even experienced datacenter techs will avoid SXM if they possibly can, that shit is meant to be installed by the vendor, doing it yourself (especially on 300% marked up gray market hardware) is completely bonkers:

if you ever had an AMD cpu back in the day (i remember way back when i had a top of the line phenom 2 lol) you might remember pin sockets:

you had to align all of these incredibly fucking fragile gold pins right above their corresponding hole on the socket, you had to drop it in just perfectly and if you didn't, you absolutely could not nudge it in place otherwise you'd bend a pin and the whole thing is fucked

(i remember fucking one up & freaking out, i had worked at a grocery store all through summer in middle school to buy it, i took it to a jeweler who couldn't fix it, eventually found the pinout, and the pin i bent was unused, by the grace of god)

anyways, SXM is this but a billion times worse. the vendors that sell the server packages have special jigs they use to align them properly, trying to install freehand is just, rofl

and that isn't even the end of the story, if homeboy gets past seating it without fucking a pin up, he'll 100% not torque the cooler down properly, it won't be flush, and the thing will cook itself the moment its powered on

not that any of this matters though, even if all done correctly, the core concept would not work. if you try and run vertex CUDA mining routines on these ""GPUs"", it'll be like trying to make pesto with your garbage disposal. that is how little foresight these people have. lmfao.

[chappydev]

Future of LLMs (or, "AI", as it is improperly called)

Posted a thread on bluesky and wanted to share it and expand on it here. I'm tangentially connected to the industry as someone who has worked in game dev, but I know people who work at more enterprise focused companies like Microsoft, Oracle, etc. I'm a developer who is highly AI-critical, but I'm also aware of where it stands in the tech world and thus I think I can share my perspective. I am by no means an expert, mind you, so take it all with a grain of salt, but I think that since so many creatives and artists are on this platform, it would be of interest here. Or maybe I'm just rambling, idk.

LLM art models ("AI art") will eventually crash and burn. Even if they win their legal battles (which if they do win, it will only be at great cost), AI art is a bad word almost universally. Even more than that, the business model hemmoraghes money. Every time someone generates art, the company loses money -- it's a very high energy process, and there's simply no way to monetize it without charging like a thousand dollars per generation. It's environmentally awful, but it's also expensive, and the sheer cost will mean they won't last without somehow bringing energy costs down. Maybe this could be doable if they weren't also being sued from every angle, but they just don't have infinite money.

Companies that are investing in "ai research" to find a use for LLMs in their company will, after years of research, come up with nothing. They will blame their devs and lay them off. The devs, worth noting, aren't necessarily to blame. I know an AI developer at meta (LLM, really, because again AI is not real), and the morale of that team is at an all time low. Their entire job is explaining patiently to product managers that no, what you're asking for isn't possible, nothing you want me to make can exist, we do not need to pivot to LLMs. The product managers tell them to try anyway. They write an LLM. It is unable to do what was asked for. "Hm let's try again" the product manager says. This cannot go on forever, not even for Meta. Worst part is, the dev who was more or less trying to fight against this will get the blame, while the product manager moves on to the next thing. Think like how NFTs suddenly disappeared, but then every company moved to AI. It will be annoying and people will lose jobs, but not the people responsible.

ChatGPT will probably go away as something public facing as the OpenAI foundation continues to be mismanaged. However, while ChatGPT as something people use to like, write scripts and stuff, will become less frequent as the public facing chatGPT becomes unmaintainable, internal chatGPT based LLMs will continue to exist.

This is the only sort of LLM that actually has any real practical use case. Basically, companies like Oracle, Microsoft, Meta etc license an AI company's model, usually ChatGPT.They are given more or less a version of ChatGPT they can then customize and train on their own internal data. These internal LLMs are then used by developers and others to assist with work. Not in the "write this for me" kind of way but in the "Find me this data" kind of way, or asking it how a piece of code works. "How does X software that Oracle makes do Y function, take me to that function" and things like that. Also asking it to write SQL queries and RegExes. Everyone I talk to who uses these intrernal LLMs talks about how that's like, the biggest thign they ask it to do, lol.

This still has some ethical problems. It's bad for the enivronment, but it's not being done in some datacenter in god knows where and vampiring off of a power grid -- it's running on the existing servers of these companies. Their power costs will go up, contributing to global warming, but it's profitable and actually useful, so companies won't care and only do token things like carbon credits or whatever. Still, it will be less of an impact than now, so there's something. As for training on internal data, I personally don't find this unethical, not in the same way as training off of external data. Training a language model to understand a C++ project and then asking it for help with that project is not quite the same thing as asking a bot that has scanned all of GitHub against the consent of developers and asking it to write an entire project for me, you know? It will still sometimes hallucinate and give bad results, but nowhere near as badly as the massive, public bots do since it's so specialized.

The only one I'm actually unsure and worried about is voice acting models, aka AI voices. It gets far less pushback than AI art (it should get more, but it's not as caustic to a brand as AI art is. I have seen people willing to overlook an AI voice in a youtube video, but will have negative feelings on AI art), as the public is less educated on voice acting as a profession. This has all the same ethical problems that AI art has, but I do not know if it has the same legal problems. It seems legally unclear who owns a voice when they voice act for a company; obviously, if a third party trains on your voice from a product you worked on, that company can sue them, but can you directly? If you own the work, then yes, you definitely can, but if you did a role for Disney and Disney then trains off of that... this is morally horrible, but legally, without stricter laws and contracts, they can get away with it.

In short, AI art does not make money outside of venture capital so it will not last forever. ChatGPT's main income source is selling specialized LLMs to companies, so the public facing ChatGPT is mostly like, a showcase product. As OpenAI the company continues to deathspiral, I see the company shutting down, and new companies (with some of the same people) popping up and pivoting to exclusively catering to enterprises as an enterprise solution. LLM models will become like, idk, SQL servers or whatever. Something the general public doesn't interact with directly but is everywhere in the industry. This will still have environmental implications, but LLMs are actually good at this, and the data theft problem disappears in most cases.

Again, this is just my general feeling, based on things I've heard from people in enterprise software or working on LLMs (often not because they signed up for it, but because the company is pivoting to it so i guess I write shitty LLMs now). I think artists will eventually be safe from AI but only after immense damages, I think writers will be similarly safe, but I'm worried for voice acting.

[chickencourtesan]

Not going to reply directly because this is just one of many posts that are like, super blasé about the normalization of AI that get under my skin. Like most of these posts are like "AI technology is already here, we might as well embrace it", or "the environmental impact of AI is actually way less than reported, it's basically the same as a Google search", etc.

I appreciate OP bringing up the carbon footprint of the Internet, but I wish more people understood the infrastructure needed to support AI is a whole 'nother beast compared to the infrastructure supporting the Internet. A lot of electricity water, and destroyed habitat goes into the datacenters that support the Internet and your favorite apps/websites. That has always been a problem and it's good to talk about it.

But as someone who rubs elbows with the Internet and datacenter industries, the environmental impact of supporting AI is absolutely real. Running an AI takes up more space in a datacenter, uses up more power, and generates more heat (causing the datacenter to use more water to cool the air). I've talked to managers at current, existing datacenters who struggle when a customer moves in and starts running an AI. And most companies that want to run an AI need more power, more space, and more water than existing datacenters can provide.

So they build more, even bigger datacenters. That destroy more habitat, and use up more electricity and more water than the datacenters that house the Internet and your apps and websites.

And the people building these datacenters are building them exclusively with AI in mind. These're companies who made their fortune during the crypto and NFT hype and they are willing to dump billions into making hyperscale datacenters to run AI -- this is a gamble, an investment for them. It will pay off big time if AI truly becomes adopted in everyday life, because those AIs will have to be housed in these huge datacenters.

Like, if you were to destroy a bunch of land to build a state-of-the-art hospital complex; that thing is going to use up a lot of water and electricity, too. But a hyperscale datacenter that exists solely to house AI that pretends to be your girlfriend or writes your fanfiction for you isn't going to benefit people a much as a hospital would, you know?

Again, I appreciate OP at least thinking about the resources being used to run the Internet (because it's not nothing!!) but holy shit AI is in a completely other league.

[hyperloopcloud]

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[allaboutkeyingo]

Windows Server 2025 Standard vs Datacenter 

The Standard and Datacenter editions of Windows Server 2025 differ significantly in features, virtualization support, and pricing. Here are the mainly differences:

1. Virtualization Support

Windows Server 2025 Standard: Each license allows 2 virtual machines (VMs) plus 1 Hyper-V host.

Windows Server 2025 Datacenter: Provides unlimited virtual machines, making it ideal for large-scale virtualization environments.

2. Container Support

Windows Server 2025 Standard: Supports unlimited Windows containers but is limited to 2 Hyper-V containers.

Windows Server 2025 Datacenter: Supports unlimited Windows containers and Hyper-V containers.

3. Storage Features

Windows Server 2025 Standard:

Storage Replica is limited to 1 partnership and 1 volume (up to 2TB).

Does not support Storage Spaces Direct.

Windows Server 2025 Datacenter:

Unlimited Storage Replica partnerships.

Supports Storage Spaces Direct, enabling hyper-converged infrastructure (HCI).

4. Advanced Features

Windows Server 2025 Standard:

No support for Software-Defined Networking (SDN), Network Controller, or Shielded VMs.

No Host Guardian Hyper-V Support.

Windows Server 2025 Datacenter:

Supports SDN, Network Controller, and Shielded VMs, enhancing security and management.

Supports GPU partitioning, useful for AI/GPU-intensive workloads.

5. Pricing

Windows Server 2025 Standard:  

$80.00 (includes 16 core ) at keyingo.com.

Windows Server 2025 Datacenter :

$90.00  (includes 16 core ) at keyingo.com.

Summary:

Windows Server 2025 Standard: Best for small businesses or physical server deployments with low virtualization needs.

Windows Server 2025 Datacenter: Designed for large-scale virtualization, hyper-converged infrastructure, and high-security environments, such as cloud providers and enterprise data centers.

[librarianrafia]

"But there is a yawning gap between "AI tools can be handy for some things" and the kinds of stories AI companies are telling (and the media is uncritically reprinting). And when it comes to the massively harmful ways in which large language models (LLMs) are being developed and trained, the feeble argument that "well, they can sometimes be handy..." doesn't offer much of a justification.

...

When I boil it down, I find my feelings about AI are actually pretty similar to my feelings about blockchains: they do a poor job of much of what people try to do with them, they can't do the things their creators claim they one day might, and many of the things they are well suited to do may not be altogether that beneficial. And while I do think that AI tools are more broadly useful than blockchains, they also come with similarly monstrous costs.

...

But I find one common thread among the things AI tools are particularly suited to doing: do we even want to be doing these things? If all you want out of a meeting is the AI-generated summary, maybe that meeting could've been an email. If you're using AI to write your emails, and your recipient is using AI to read them, could you maybe cut out the whole thing entirely? If mediocre, auto-generated reports are passing muster, is anyone actually reading them? Or is it just middle-management busywork?

...

Costs and benefits

Throughout all this exploration and experimentation I've felt a lingering guilt, and a question: is this even worth it? And is it ethical for me to be using these tools, even just to learn more about them in hopes of later criticizing them more effectively?

The costs of these AI models are huge, and not just in terms of the billions of dollars of VC funds they're burning through at incredible speed. These models are well known to require far more computing power (and thus electricity and water) than a traditional web search or spellcheck. Although AI company datacenters are not intentionally wasting electricity in the same way that bitcoin miners perform millions of useless computations, I'm also not sure that generating a picture of a person with twelve fingers on each hand or text that reads as though written by an endlessly smiling children's television star who's being held hostage is altogether that much more useful than a bitcoin.

There's a huge human cost as well. Artificial intelligence relies heavily upon "ghost labor": work that appears to be performed by a computer, but is actually delegated to often terribly underpaid contractors, working in horrible conditions, with few labor protections and no benefits. There is a huge amount of work that goes into compiling and labeling data to feed into these models, and each new model depends on ever-greater amounts of said data — training data which is well known to be scraped from just about any possible source, regardless of copyright or consent. And some of these workers suffer serious psychological harm as a result of exposure to deeply traumatizing material in the course of sanitizing datasets or training models to perform content moderation tasks.

Then there's the question of opportunity cost to those who are increasingly being edged out of jobs by LLMs,i despite the fact that AI often can't capably perform the work they were doing. Should I really be using AI tools to proofread my newsletters when I could otherwise pay a real person to do that proofreading? Even if I never intended to hire such a person?

Or, more accurately, by managers and executives who believe the marketing hype out of AI companies that proclaim that their tools can replace workers, without seeming to understand at all what those workers do.

Finally, there's the issue of how these tools are being used, and the lack of effort from their creators to limit their abuse. We're seeing them used to generate disinformation via increasingly convincing deepfaked images, audio, or video, and the reckless use of them by previously reputable news outlets and others who publish unedited AI content is also contributing to misinformation. Even where AI isn't being directly used, it's degrading trust so badly that people have to question whether the content they're seeing is generated, or whether the "person" they're interacting with online might just be ChatGPT. Generative AI is being used to harass and sexually abuse. Other AI models are enabling increased surveillance in the workplace and for "security" purposes — where their well-known biases are worsening discrimination by police who are wooed by promises of "predictive policing". The list goes on.

[avariantflaire]

what if they built certain ai on libraries. imagine the amount of factual inaccuracies that would be solved by putting trained information specialists/library scientists on the database administration from which the ai feeds. you know how libraries already have people manually checking and relating book tags (e.g. genre, author, markers)? imagine the planning and control on where a wealth of information can and should be used. imagine a strict librarian telling companies off for their generative bullshit. imagine ai that was tailored more as a tool to facilitate knowledge and aid in information acquisition instead of whatever crap it's spewing out now. imagine if somehow we treated libraries as the sacred datacenters that they are and we somehow managed to implement this over such a course of time that a) the perceived public value of libraries skyrocket as an ai-aided learning hub/resource finder and overall - information exists in books too! maybe ai can help you browse for the right ones! like a superpowered version of what libraries do anyway! and b) the absolute shitshow of an economic and environmental impact ai has could be avoided because of scaled implementation (one library in a city as a pilot project to begin with) and human resource involvement (work is still done by people to make sure that things are done right). a bare bones idea but what if

[hasufin]

Out of sight

About a century ago, the landscape was changing. The very nature of how America was laid out was being changed in ways we still haven't fully reckoned with.

And if you were alive at the time, you wouldn't have noticed.

While America was conceived as an agrarian nation, we made our own manufactured goods just as soon as we could. And the factory wasn't exactly a new concept. Indeed, the previous century had seen them transform from specialized workshops for skilled craftsmen, to mass production.

But something else was changing. And the funny thing is, you'd have a hard time putting your finger on just what. They'd been using running water and beasts of burden for a while, to power various tools. They'd been using less and less skilled labor, with more rigorous guidance on just what a worker should be doing. Complex tasks had been mechanized for a while now.

And yet. Somehow it was different. Somehow everything had a machine to make the work faster. The factories had electric lights, conveyor belts, and electric motors were replacing steam engines. You'd be hard-pressed to point to any one thing which fundamentally changed the process, and yet it was all completely different.

That brought still more changes. The frenetic pace of manufacture meant more workers, more machines, more noise - and with those electric lights, work could happen at all hours, deliveries rumbling past.

Sure, a factory with dozens or hundreds of men working wasn't a quiet thing, but it was no comparison to the constant roar of the industrial beast. Those factories, once found in the heart of cities where the workers lived, were moved further out, where neighbors wouldn't complain. Factory towns grew. An entire way of life developed.

But if you lived in the city, what you'd notice is, factories got bigger, and noisier, and then shuttered and moved away. If you didn't work in them, that was all.

I think about this whenever I drive through Ashburn and Chantilly, and I see another datacenter being built. These huge, windowless buildings that take up acres of land and only have a few dozen people working in them. They're the engines of a new kind of industry. And they're no different in kind from the datacenters we've had for decades. They're just... bigger. And by their being bigger, they somehow manage to be different, just not in a specific way. They're making a different way of life which won't be apparent for decades.

But if you live in the city, if you don't work with those enormous arrays of computing power, you'd not really notice. There's just some big, windowless buildings which didn't used to be there.

[softwareinformationsource]

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[bharathi1908]

Introduction to Real Estate Investment Trusts (REITs)

Overview of REITs

An organization that owns, manages, or finances real estate that generates revenue is known as a real estate investment trust, or REIT. Like mutual funds, REITs offer an investment opportunity that enables regular Americans, not just Wall Street, banks, and hedge funds, to profit from valuable real estate.  It gives investors access to total returns and dividend-based income, and supports the expansion, thriving, and revitalization of local communities.

Anyone can engage in real estate investment trusts (REITs) in the same manner as they can invest in other industries: by buying individual firm shares, through exchange-traded funds (ETFs), or mutual funds. A REIT’s investors receive a portion of the revenue generated without really having to purchase, operate, or finance real estate. Families with 401(k), IRAs, pension plans, and other investment accounts invested in REITs that comprise about 150 million Americans.

Historical Evolution

1960s - REITs were created

When President Eisenhower passes the REIT Act title found in the 1960 Cigar Excise Tax Extension into law, REITs are established. Congress established REITs to provide a means for all investors to participate in sizable, diversified portfolios of real estate that generate income.

1970s - REITs around the world

In 1969 The Netherlands passes the first piece of European REIT legislation. This is when the real estate investment trusts model started to spread over the world; shortly after, in 1971, listed property trusts were introduced in Australia.

1980s - Competing for capital

1980s saw real estate tax-sheltered partnerships expanding at this time, raising billions of dollars through private placements. Because they were and are set up in a way that prevents tax losses from being "passed through" to REIT shareholders, REITs struggle to compete for capital.

1990s - First REIT reaches $1 billion market cap

In December 1991 the New Plan achieves $1 billion in equity market capitalization, becoming the first publicly traded REIT to do so. Centro Properties Group, based in Australia, purchased New Plan in 2007.

2000s - REITs modernization act

President Clinton signed the REIT Modernization Act of 1999's provisions into law in December 1999 as part of the Ticket to Work and Work Incentives Improvement Act of 1999. The capacity of a REIT to establish one or more taxable real estate investment trusts subsidiaries (TRS) that can provide services to third parties and REIT tenants is one of the other things.

The diverse landscape of REIT investments

Real estate investing is a dynamic field with a wide range of options for those wishing to build wealth and diversify their holdings.

Residential REITs: This is an easy way for novices to get started in real estate investing, as single-family houses offer a strong basis. Purchasing duplexes or apartment buildings can result in steady rental income as well as possible capital growth.

Commercial REITs: This covers activities such as office building investments. They provide steady cash flow and long-term leases, especially in desirable business areas. Rental assets such as shopping centers and retail spaces are lucrative prospects and can appreciate value as long as businesses remain successful.

Specialty REITs: These include investments in healthcare-related properties such as assisted living centers or physician offices. Datacenter investments have become more and more common in the digital age because of the growing need for safe data storage.

Job profiles within REITs

Real estate investment jobs have many specifications, including:

Real estate analysts: The job of a real estate analyst is to find chances for purchasing profitable real estate. These analysts will require a strong skill set in financial modeling in addition to a solid understanding of the current markets. These analysts could also be involved in the negotiation of terms related to pricing and real estate transactions.

Asset managers: Opportunities in property trusts are plenty. The higher-level property management choices are made by asset managers. Since asset managers will be evaluating and controlling a property's operating expenses about its potential for income generation, they must possess a greater foundation in finance.

Property managers: REIT employment prospects include property managers. While some real estate investment trusts employ their property managers, others contract with outside businesses to handle their properties. Along with working with renters, property managers handle all daily duties required to keep up the property. 

Essential skills for success in REIT careers

Successful REIT careers require the development of several essential talents, three of which are listed below:

Financial acumen: Jobs in real estate finance involve investors with strong financial acumen who are better equipped to evaluate financing choices, cash flow forecasts, property valuations, and tax consequences. With this thorough insight, investors may make well-informed strategic decisions that optimize profits while also supporting their investing goals.

Market analysis skills: Real estate investors should cultivate an awareness of important market indicators and a keen sense of market conditions. Purchasing and managing profitable rental properties requires an accurate and detailed understanding of a possible market's amenities, dynamics, future potential, and relative risk.

Communication skills: Are a common attribute among successful real estate investors and are often ranked as the most important one. This is because effective interpersonal communication is crucial when investing in real estate. Working directly with a variety of industry professionals, including lenders, agents, property managers, tenants, and many more.

Global perspectives on REITs

International REIT Markets:

The US-based REIT method for real estate investing has been embraced by more than 40 nations and regions, providing access to income-producing real estate assets worldwide for all investors. The simplest and most effective approach for investors to include global listed real estate allocations in their portfolios is through mutual funds and exchange-traded funds.

The listed real estate market is getting more and more international, even if the United States still has the largest market. The allure of the US real estate investment trusts strategy for real estate investing is fueling the expansion. All G7 nations are among the more than forty nations and regions that have REITs today.

Technological innovations in REIT operations

PropTech integration: Real estate investment managers can improve the efficiency of property acquisitions and due diligence procedures, which can lead to more precise assessments, quicker data processing, and better decision-making, all of which improve investment outcomes, by incorporating these PropTech platforms into their workflows.

Data analytics in real estate: Data analytics in real estate enables real estate professionals to make data-driven choices regarding the acquisition, purchase, leasing, or administration of a physical asset. To provide insights that can be put into practice, the process entails compiling all pertinent data from several sources and analyzing it.

Conclusion

REITs have a lot of advantages and disadvantages for professional development. They provide a means of incorporating real estate into an investment portfolio, but they could also produce a bigger dividend than certain other options. Since non-exchange-listed REITs do not trade on stock exchanges, there are certain risks associated with them. Finding the value of a share in a non-traded real estate investment trusts can be challenging, even though the market price of a publicly traded REIT is easily available. Buying shares through a broker allows you to invest in a publicly traded REIT that is listed on a major stock exchange. The bottom line for a REIT is that, in contrast to other real estate firms, it doesn't build properties to resell them.

[haripriya2002]

Azure’s Evolution: What Every IT Pro Should Know About Microsoft’s Cloud

IT professionals need to keep ahead of the curve in the ever changing world of technology today. The cloud has become an integral part of modern IT infrastructure, and one of the leading players in this domain is Microsoft Azure. Azure’s evolution over the years has been nothing short of remarkable, making it essential for IT pros to understand its journey and keep pace with its innovations. In this blog, we’ll take you on a journey through Azure’s transformation, exploring its history, service portfolio, global reach, security measures, and much more. By the end of this article, you’ll have a comprehensive understanding of what every IT pro should know about Microsoft’s cloud platform.

Historical Overview

Azure’s Humble Beginnings

Microsoft Azure was officially launched in February 2010 as “Windows Azure.” It began as a platform-as-a-service (PaaS) offering primarily focused on providing Windows-based cloud services.

The Azure Branding Shift

In 2014, Microsoft rebranded Windows Azure to Microsoft Azure to reflect its broader support for various operating systems, programming languages, and frameworks. This rebranding marked a significant shift in Azure’s identity and capabilities.

Key Milestones

Over the years, Azure has achieved numerous milestones, including the introduction of Azure Virtual Machines, Azure App Service, and the Azure Marketplace. These milestones have expanded its capabilities and made it a go-to choice for businesses of all sizes.

Expanding Service Portfolio

Azure’s service portfolio has grown exponentially since its inception. Today, it offers a vast array of services catering to diverse needs:

Compute Services: Azure provides a range of options, from virtual machines (VMs) to serverless computing with Azure Functions.

Data Services: Azure offers data storage solutions like Azure SQL Database, Cosmos DB, and Azure Data Lake Storage.

AI and Machine Learning: With Azure Machine Learning and Cognitive Services, IT pros can harness the power of AI for their applications.

IoT Solutions: Azure IoT Hub and IoT Central simplify the development and management of IoT solutions.

Azure Regions and Global Reach

Azure boasts an extensive network of data centers spread across the globe. This global presence offers several advantages:

Scalability: IT pros can easily scale their applications by deploying resources in multiple regions.

Redundancy: Azure’s global datacenter presence ensures high availability and data redundancy.

Data Sovereignty: Choosing the right Azure region is crucial for data compliance and sovereignty.

Integration and Hybrid Solutions

Azure’s integration capabilities are a boon for businesses with hybrid cloud needs. Azure Arc, for instance, allows you to manage on-premises, multi-cloud, and edge environments through a unified interface. Azure’s compatibility with other cloud providers simplifies multi-cloud management.

Security and Compliance

Azure has made significant strides in security and compliance. It offers features like Azure Security Center, Azure Active Directory, and extensive compliance certifications. IT pros can leverage these tools to meet stringent security and regulatory requirements.

Azure Marketplace and Third-Party Offerings

Azure Marketplace is a treasure trove of third-party solutions that complement Azure services. IT pros can explore a wide range of offerings, from monitoring tools to cybersecurity solutions, to enhance their Azure deployments.

Azure DevOps and Automation

Automation is key to efficiently managing Azure resources. Azure DevOps services and tools facilitate continuous integration and continuous delivery (CI/CD), ensuring faster and more reliable application deployments.

Monitoring and Management

Azure offers robust monitoring and management tools to help IT pros optimize resource usage, troubleshoot issues, and gain insights into their Azure deployments. Best practices for resource management can help reduce costs and improve performance.

Future Trends and Innovations

As the technology landscape continues to evolve, Azure remains at the forefront of innovation. Keep an eye on trends like edge computing and quantum computing, as Azure is likely to play a significant role in these domains.

Training and Certification

To excel in your IT career, consider pursuing Azure certifications. ACTE Institute offers a range of certifications, such as the Microsoft Azure course to validate your expertise in Azure technologies.

In conclusion, Azure’s evolution is a testament to Microsoft’s commitment to cloud innovation. As an IT professional, understanding Azure’s history, service offerings, global reach, security measures, and future trends is paramount. Azure’s versatility and comprehensive toolset make it a top choice for organizations worldwide. By staying informed and adapting to Azure’s evolving landscape, IT pros can remain at the forefront of cloud technology, delivering value to their organizations and clients in an ever-changing digital world. Embrace Azure’s evolution, and empower yourself for a successful future in the cloud.

[khaysvelle]

"EMPOWERMENT TECHNOLOGIES"

TRENDS IN ICT_

1. CONVERGENCE

-Technological convergence is the combination of two or more different entities of technologies to create a new single device.

2. SOCIAL MEDIA

-is a website, application, or online channel that enables web users web users to create , co-create, discuss modify, and exchange user generated content.

SIX TYPES OF SOCIAL MEDIA:

a. SOCIAL NETWORKS

- These are sites that allows you to connect with other people with the same interests or background. Once the user creates his/her account, he/she can set up a profile, add people, share content, etc.

b. BOOKMARKING SITES

- Sites that allow you to store and manage links to various website and resources. Most of the sites allow you to create a tag to others.

c. SOCIAL NEWS

– Sites that allow users to post their own news items or links to other news sources. The users can also comment on the post and comments may also be rank.

d. MEDIA SHARING

– sites that allow you to upload and share media content like images, music and video.

e. MICROBLOGGING

- focus on short updates from the user. Those that subscribed to the user will be able to receive these updates.

f. BLOGS AND FORUMS

- allow user to post their content. Other users are able to comment on the said topic.

3. MOBILE TECHNOLOGIES

- The popularity of smartphones and tablets has taken a major rise over the years. This is largely because of the devices capability to do the tasks that were originally found in PCs. Several of these devices are capable of using a high-speed internet. Today the latest model devices use 4G Networking (LTE), which is currently the fastest.

MOBILE OS

•iOS

- use in apple devices such as iPhone and iPad.

•ANDROID

- an open source OS developed by Google. Being open source means mobile phone companies use this OS for free.

•BLACKBERRY OS

- use in blackberry devices

•WINDOWS PHONE OS

- A closed source and proprietary operating system developed by Microsoft.

=Symbian - the original smartphone OS. Used by Nokia devices

= Web OS- originally used in smartphone; now in smart TVs.

= Windows Mobile - developed by Microsoft for smartphones and pocket PCs

4. ASSISTIVE MEDIA

- is a non- profit service designed to help people who have visual and reading impairments. A database of audio recordings is used to read to the user.

CLOUD COMPUTING

- distributed computing on internet or delivery of computing service over the internet. e.g. Yahoo!, Gmail, Hotmail

-Instead of running an e-mail program on your computer, you log in to a Web e-mail account remotely. The software and storage for your account doesn’t exist on your computer – it’s on the service’s computer cloud.

It has three components ;

1. Client computers

– clients are the device that the end user interact with cloud.

2. Distributed Servers

– Often servers are in geographically different places, but server acts as if they are working next to each other.

3. Datacenters

– It is collection of servers where application is placed and is accessed via Internet.

TYPES OF CLOUDS

PUBLIC CLOUD

-allows systems and services to be easily accessible to the general public. Public cloud may be less secured because of its openness, e.g. e-mail

PRIVATE CLOUD

-allows systems and services to be accessible within an organization. It offers increased security because of its private nature.

COMMUNITY CLOUD

- allows systems and services to be accessible by group of organizations.

HYBRID CLOUD

-is a mixture of public and private cloud. However, the critical activities are performed using private cloud while the non-critical activities are performed using public cloud.

—Khaysvelle C. Taborada

#TrendsinICT

#ICT

#EmpowermentTechnologies