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jcmarchi · 6 months ago

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Building Better in the Cloud: Why the Time Is Now

New Post has been published on https://thedigitalinsider.com/building-better-in-the-cloud-why-the-time-is-now/

Building Better in the Cloud: Why the Time Is Now

Massive cloud investment continues worldwide, with Gartner predicting public cloud spending to reach an eye-popping $1 trillion by 2027. This number is growing significantly as companies invest more in generative AI, as GenAI initiatives require a lot of cloud capacity.

And yet, many organizations still struggle to maximize the value of their cloud investments. Cloud waste is a rampant problem; it’s estimated that anywhere from 28-35% of cloud spend is wasted. It’s little wonder, then, that a recent CloudZero survey found that 72% of respondents said their cloud costs were either “too high” or “way too high.”

How do you get the most bang for your buck? It starts with taking a different approach to how you think about and use the cloud.

The cloud waste problem

The right mindset involves veering away from the “lift and shift” mentality of just taking existing resources and moving them into the cloud. Cloud waste stems largely from this antiquated mindset, which treats cloud infrastructure like traditional infrastructure.

The consumption and management of cloud infrastructure has little in common with traditional infrastructure. Before the cloud, companies invested heavily in data centers and servers, spending outsized sums of money on the infrastructure they thought they’d need to process the demand they expected to generate. The process was: Product teams proposed some innovation, predicted demand, and made formal requests to IT procurement teams for the infrastructure they expected to need. The procurement team could approve, deny, or modify the request, and months later, the product teams might have the infrastructure they’d need to execute the innovation.

Companies often bought more infrastructure than they ended up using, and found themselves sitting on servers that weren’t generating any value. Virtualization promised to even this balance, but over-provisioning and under-utilization continued to be a challenge. And while the cloud has introduced endless possibilities through a diverse set of infrastructure, database, and platform services and a consumption-driven utility model, many companies still manage it like a collection of physical virtual machines.

Procurement and finance teams used to be involved in every infrastructure purchase. Now, in the cloud, infrastructure consumption happens instantly, whenever an engineer spins up a new cloud resource or writes a line of code that consumes those resources. The purchase moment has changed entirely: In the cloud, every engineering (building) decision is a buying decision. Engineers — not finance leaders or centralized IT teams — are directly spending the company’s technology budget.

So, when companies pin cloud costs on finance teams or centralized IT teams, they miss the mark. Engineers make building decisions based on engineering expertise — expertise that other teams don’t have. Finance teams can make bulk purchases or optimized committed use discounts, but you do not want them distinguishing between the use of a m7g.2xlarge and a m7gd.metal. IT teams are great at finding underutilized resources, but they are not in the best position to understand if the code running on a highly utilized resource is healthy or not. In the cloud, buying better only gets you so far.

For a long time, engineers have lacked the financial insight to make cost-efficient building decisions in the cloud, leading to a torrent of cloud waste annually. A recent survey by CloudZero found that companies that implement formal cloud cost management programs tend to reduce their annual cloud spending by 20-30%. Given that 61% of companies don’t have formalized programs, this means that when cloud spending hits $1 trillion in 2027, as much as $122–183 billion of that could be wasted.

This needs to change. Companies need to realize that cloud infrastructure is entirely different from traditional infrastructure, and that cloud cost management requires a completely new approach. We need to shift away from buying better to building better: equipping engineers to take ownership of their own cloud costs, and, as Amazon CTO Werner Vogels put it in The Frugal Architect, “make cost a non-functional requirement” of great software.

Time to build better in the cloud vs. buying better

Building better is an engineering philosophy rather than a financial paradigm. “Building” refers to every architecture, coding, or operations decision engineers make in the process of developing a product and bringing it to market.

Until recently, there hasn’t been a way to grasp the true cost of such decisions, and organizations weren’t very invested in finding out. The mindset of buying better comes from a reactive desire to reduce costs, whereas the mindset of building better is all about developing and running efficient software.

Benefits of building better

Engaged engineers. The data suggests that when engineers are equipped to manage their own costs, they do — and that companies perform better. In that same survey, 81% of companies said cloud costs are “about where they should be” when engineers had some level of ownership over cloud costs. Focusing on building better means focusing squarely on engineering engagement: giving engineers relevant, timely data about their cloud infrastructure costs, and making it easy to track efficiency gains.

Improved finance-engineering relations. When companies focus on building better, it allows finance and engineering teams to focus on their respective specialties. Engineers weigh the factors that go into well-architected software; finance teams get regular, detailed reports about the cost efficiency of that software. The friction between the teams is reduced, and overall productivity improves.

Unit economic clarity. Giving engineers meaningful cost data means ingesting all spend data (beyond just the hyperscalers to include platform services, database services, observability tools, etc.) and allocating it in a framework that mirrors the company’s business. Such robust allocation yields the material for cloud unit economics: assessing profitable and unprofitable products, features, and customers, understanding fixed versus variable costs and the relationships to margins, and refining your GTM strategy based on this data. Cloud unit economics is the holy grail of cloud financial operations (FinOps) — and the mark of a truly cloud efficient organization.

It’s time to build better

More and more organizations feel that they’re getting too little return on their cloud investments. By switching from a buying better to a building better approach, organizations gauge their approach to the true nature of the cloud, producing better engineering engagement, improved relations between finance and engineering teams, and stronger unit economics.

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xcalable24 · 6 months ago

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#Western Digital #ultrastar #hc680 #27tb #data center #youtube #@inphi #@lucent #@marvell #@nokia #@alcatel #@xcalable #amazon #ebay

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sanjanabia · 8 months ago

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Why AWS is Becoming Essential for Modern IT Professionals

In today's fast-paced tech landscape, the integration of development and operations has become crucial for delivering high-quality software efficiently. AWS DevOps is at the forefront of this transformation, enabling organizations to streamline their processes, enhance collaboration, and achieve faster deployment cycles. For IT professionals looking to stay relevant in this evolving environment, pursuing AWS DevOps training in Hyderabad is a strategic choice. Let’s explore why AWS DevOps is essential and how training can set you up for success.

The Rise of AWS DevOps

1. Enhanced Collaboration

AWS DevOps emphasizes the collaboration between development and operations teams, breaking down silos that often hinder productivity. By fostering communication and cooperation, organizations can respond more quickly to changes and requirements. This shift is vital for businesses aiming to stay competitive in today’s market.

2. Increased Efficiency

With AWS DevOps practices, automation plays a key role. Tasks that were once manual and time-consuming, such as testing and deployment, can now be automated using AWS tools. This not only speeds up the development process but also reduces the likelihood of human error. By mastering these automation techniques through AWS DevOps training in Hyderabad, professionals can contribute significantly to their teams' efficiency.

Benefits of AWS DevOps Training

1. Comprehensive Skill Development

An AWS DevOps training in Hyderabad program covers a wide range of essential topics, including:

AWS services such as EC2, S3, and Lambda

Continuous Integration and Continuous Deployment (CI/CD) pipelines

Infrastructure as Code (IaC) with tools like AWS CloudFormation

Monitoring and logging with AWS CloudWatch

This comprehensive curriculum equips you with the skills needed to thrive in modern IT environments.

2. Hands-On Experience

Most training programs emphasize practical, hands-on experience. You'll work on real-world projects that allow you to apply the concepts you've learned. This experience is invaluable for building confidence and competence in AWS DevOps practices.

3. Industry-Recognized Certifications

Earning AWS certifications, such as the AWS Certified DevOps Engineer, can significantly enhance your resume. Completing AWS DevOps training in Hyderabad prepares you for these certifications, demonstrating your commitment to professional development and expertise in the field.

4. Networking Opportunities

Participating in an AWS DevOps training in Hyderabad program also allows you to connect with industry professionals and peers. Building a network during your training can lead to job opportunities, mentorship, and collaborative projects that can advance your career.

Career Opportunities in AWS DevOps

1. Diverse Roles

With expertise in AWS DevOps, you can pursue various roles, including:

DevOps Engineer

Site Reliability Engineer (SRE)

Cloud Architect

Automation Engineer

Each role offers unique challenges and opportunities for growth, making AWS DevOps skills highly valuable.

2. High Demand and Salary Potential

The demand for DevOps professionals, particularly those skilled in AWS, is skyrocketing. Organizations are actively seeking AWS-certified candidates who can implement effective DevOps practices. According to industry reports, these professionals often command competitive salaries, making an AWS DevOps training in Hyderabad a wise investment.

3. Job Security

As more companies adopt cloud solutions and DevOps practices, the need for skilled professionals will continue to grow. This trend indicates that expertise in AWS DevOps can provide long-term job security and career advancement opportunities.

Staying Relevant in a Rapidly Changing Industry

1. Continuous Learning

The tech industry is continually evolving, and AWS regularly introduces new tools and features. Staying updated with these advancements is crucial for maintaining your relevance in the field. Consider pursuing additional certifications or training courses to deepen your expertise.

2. Community Engagement

Engaging with AWS and DevOps communities can provide insights into industry trends and best practices. These networks often share valuable resources, training materials, and opportunities for collaboration.

Conclusion

As the demand for efficient software delivery continues to rise, AWS DevOps expertise has become essential for modern IT professionals. Investing in AWS DevOps training in Hyderabad will equip you with the skills and knowledge needed to excel in this dynamic field.

By enhancing your capabilities in collaboration, automation, and continuous delivery, you can position yourself for a successful career in AWS DevOps. Don’t miss the opportunity to elevate your professional journey—consider enrolling in an AWS DevOps training in Hyderabad program today and unlock your potential in the world of cloud computing!

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phantomrose96 · 1 year ago

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If anyone wants to know why every tech company in the world right now is clamoring for AI like drowned rats scrabbling to board a ship, I decided to make a post to explain what's happening.

(Disclaimer to start: I'm a software engineer who's been employed full time since 2018. I am not a historian nor an overconfident Youtube essayist, so this post is my working knowledge of what I see around me and the logical bridges between pieces.)

Okay anyway. The explanation starts further back than what's going on now. I'm gonna start with the year 2000. The Dot Com Bubble just spectacularly burst. The model of "we get the users first, we learn how to profit off them later" went out in a no-money-having bang (remember this, it will be relevant later). A lot of money was lost. A lot of people ended up out of a job. A lot of startup companies went under. Investors left with a sour taste in their mouth and, in general, investment in the internet stayed pretty cooled for that decade. This was, in my opinion, very good for the internet as it was an era not suffocating under the grip of mega-corporation oligarchs and was, instead, filled with Club Penguin and I Can Haz Cheezburger websites.

Then around the 2010-2012 years, a few things happened. Interest rates got low, and then lower. Facebook got huge. The iPhone took off. And suddenly there was a huge new potential market of internet users and phone-havers, and the cheap money was available to start backing new tech startup companies trying to hop on this opportunity. Companies like Uber, Netflix, and Amazon either started in this time, or hit their ramp-up in these years by shifting focus to the internet and apps.

Now, every start-up tech company dreaming of being the next big thing has one thing in common: they need to start off by getting themselves massively in debt. Because before you can turn a profit you need to first spend money on employees and spend money on equipment and spend money on data centers and spend money on advertising and spend money on scale and and and

But also, everyone wants to be on the ship for The Next Big Thing that takes off to the moon.

So there is a mutual interest between new tech companies, and venture capitalists who are willing to invest $$$ into said new tech companies. Because if the venture capitalists can identify a prize pig and get in early, that money could come back to them 100-fold or 1,000-fold. In fact it hardly matters if they invest in 10 or 20 total bust projects along the way to find that unicorn.

But also, becoming profitable takes time. And that might mean being in debt for a long long time before that rocket ship takes off to make everyone onboard a gazzilionaire.

But luckily, for tech startup bros and venture capitalists, being in debt in the 2010's was cheap, and it only got cheaper between 2010 and 2020. If people could secure loans for ~3% or 4% annual interest, well then a $100,000 loan only really costs $3,000 of interest a year to keep afloat. And if inflation is higher than that or at least similar, you're still beating the system.

So from 2010 through early 2022, times were good for tech companies. Startups could take off with massive growth, showing massive potential for something, and venture capitalists would throw infinite money at them in the hopes of pegging just one winner who will take off. And supporting the struggling investments or the long-haulers remained pretty cheap to keep funding.

You hear constantly about "Such and such app has 10-bazillion users gained over the last 10 years and has never once been profitable", yet the thing keeps chugging along because the investors backing it aren't stressed about the immediate future, and are still banking on that "eventually" when it learns how to really monetize its users and turn that profit.

The pandemic in 2020 took a magnifying-glass-in-the-sun effect to this, as EVERYTHING was forcibly turned online which pumped a ton of money and workers into tech investment. Simultaneously, money got really REALLY cheap, bottoming out with historic lows for interest rates.

Then the tide changed with the massive inflation that struck late 2021. Because this all-gas no-brakes state of things was also contributing to off-the-rails inflation (along with your standard-fare greedflation and price gouging, given the extremely convenient excuses of pandemic hardships and supply chain issues). The federal reserve whipped out interest rate hikes to try to curb this huge inflation, which is like a fire extinguisher dousing and suffocating your really-cool, actively-on-fire party where everyone else is burning but you're in the pool. And then they did this more, and then more. And the financial climate followed suit. And suddenly money was not cheap anymore, and new loans became expensive, because loans that used to compound at 2% a year are now compounding at 7 or 8% which, in the language of compounding, is a HUGE difference. A $100,000 loan at a 2% interest rate, if not repaid a single cent in 10 years, accrues to $121,899. A $100,000 loan at an 8% interest rate, if not repaid a single cent in 10 years, more than doubles to $215,892.

Now it is scary and risky to throw money at "could eventually be profitable" tech companies. Now investors are watching companies burn through their current funding and, when the companies come back asking for more, investors are tightening their coin purses instead. The bill is coming due. The free money is drying up and companies are under compounding pressure to produce a profit for their waiting investors who are now done waiting.

You get enshittification. You get quality going down and price going up. You get "now that you're a captive audience here, we're forcing ads or we're forcing subscriptions on you." Don't get me wrong, the plan was ALWAYS to monetize the users. It's just that it's come earlier than expected, with way more feet-to-the-fire than these companies were expecting. ESPECIALLY with Wall Street as the other factor in funding (public) companies, where Wall Street exhibits roughly the same temperament as a baby screaming crying upset that it's soiled its own diaper (maybe that's too mean a comparison to babies), and now companies are being put through the wringer for anything LESS than infinite growth that Wall Street demands of them.

Internal to the tech industry, you get MASSIVE wide-spread layoffs. You get an industry that used to be easy to land multiple job offers shriveling up and leaving recent graduates in a desperately awful situation where no company is hiring and the market is flooded with laid-off workers trying to get back on their feet.

Because those coin-purse-clutching investors DO love virtue-signaling efforts from companies that say "See! We're not being frivolous with your money! We only spend on the essentials." And this is true even for MASSIVE, PROFITABLE companies, because those companies' value is based on the Rich Person Feeling Graph (their stock) rather than the literal profit money. A company making a genuine gazillion dollars a year still tears through layoffs and freezes hiring and removes the free batteries from the printer room (totally not speaking from experience, surely) because the investors LOVE when you cut costs and take away employee perks. The "beer on tap, ping pong table in the common area" era of tech is drying up. And we're still unionless.

Never mind that last part.

And then in early 2023, AI (more specifically, Chat-GPT which is OpenAI's Large Language Model creation) tears its way into the tech scene with a meteor's amount of momentum. Here's Microsoft's prize pig, which it invested heavily in and is galivanting around the pig-show with, to the desperate jealousy and rapture of every other tech company and investor wishing it had that pig. And for the first time since the interest rate hikes, investors have dollar signs in their eyes, both venture capital and Wall Street alike. They're willing to restart the hose of money (even with the new risk) because this feels big enough for them to take the risk.

Now all these companies, who were in varying stages of sweating as their bill came due, or wringing their hands as their stock prices tanked, see a single glorious gold-plated rocket up out of here, the likes of which haven't been seen since the free money days. It's their ticket to buy time, and buy investors, and say "see THIS is what will wring money forth, finally, we promise, just let us show you."

To be clear, AI is NOT profitable yet. It's a money-sink. Perhaps a money-black-hole. But everyone in the space is so wowed by it that there is a wide-spread and powerful conviction that it will become profitable and earn its keep. (Let's be real, half of that profit "potential" is the promise of automating away jobs of pesky employees who peskily cost money.) It's a tech-space industrial revolution that will automate away skilled jobs, and getting in on the ground floor is the absolute best thing you can do to get your pie slice's worth.

It's the thing that will win investors back. It's the thing that will get the investment money coming in again (or, get it second-hand if the company can be the PROVIDER of something needed for AI, which other companies with venture-back will pay handsomely for). It's the thing companies are terrified of missing out on, lest it leave them utterly irrelevant in a future where not having AI-integration is like not having a mobile phone app for your company or not having a website.

So I guess to reiterate on my earlier point:

Drowned rats. Swimming to the one ship in sight.

#chrissy speaks #long post #-gestures broadly-

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poojalate · 11 months ago

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How Leading Companies Are Leveraging Infrastructure as a Service (IaaS)

As businesses increasingly turn to digital solutions, Infrastructure as a Service (IaaS) has emerged as a vital component for modern enterprises. By utilizing cloud platforms, companies can enhance their agility, scalability, and cost-efficiency. This article explores infrastructure as a service examples and how leading companies are leveraging IaaS providers to drive innovation and growth.

What is Infrastructure as a Service (IaaS)?

IaaS is a cloud computing service model that delivers virtualized computing resources over the internet. It enables businesses to rent infrastructure components like servers, storage, and networking, rather than investing in physical hardware. This flexibility allows companies to scale resources according to their needs and focus on core activities without the burden of managing IT infrastructure.

1. Netflix: Enhancing Scalability and Performance

Cloud Infrastructure Examples

Netflix, the global streaming giant, leverages IaaS to manage its vast content library and ensure seamless streaming experiences for millions of users worldwide. By using IaaS providers like Amazon Web Services (AWS), Netflix can quickly scale its infrastructure to handle peak loads, such as new releases or seasonal spikes in viewership. This scalability ensures high performance and availability, crucial for maintaining customer satisfaction.

2. Airbnb: Optimizing Resource Management

IaaS Use Cases

Airbnb, the popular online marketplace for lodging, utilizes IaaS to manage its global operations. The company employs cloud services examples like dynamic scaling to match infrastructure resources with fluctuating demand. During peak travel seasons or significant events, Airbnb can scale up its infrastructure to accommodate increased traffic, ensuring reliable service and user experience.

3. Slack: Ensuring Data Security and Compliance

Cloud Platforms

Slack, a leading collaboration platform, relies on IaaS for data security and regulatory compliance. By partnering with IaaS providers like Google Cloud Platform (GCP), Slack benefits from advanced security features, including encryption and compliance with industry standards such as GDPR and HIPAA. This ensures that sensitive business communications remain secure and compliant with regulations.

4. Pinterest: Enhancing Development and Innovation

IaaS Providers

Pinterest, a visual discovery and bookmarking platform, leverages IaaS to accelerate development cycles and foster innovation. Using cloud platforms like Microsoft Azure, Pinterest provides its developers with the tools and resources needed to build, test, and deploy new features rapidly. This agile development environment supports continuous improvement and innovation.

5. Spotify: Delivering Seamless Music Streaming

Cloud Infrastructure Examples

Spotify, the music streaming service, utilizes IaaS to manage its extensive music catalog and deliver high-quality streaming experiences. By using cloud platforms like Google Cloud, Spotify ensures that users can access their favorite music anytime, anywhere. The scalable infrastructure allows Spotify to handle millions of concurrent users without compromising performance.

6. Coca-Cola: Supporting Global Operations

IaaS Use Cases

Coca-Cola, a global beverage leader, uses IaaS to support its worldwide operations. By partnering with IaaS providers like IBM Cloud, Coca-Cola manages its supply chain, customer data, and digital marketing initiatives across different regions. This integrated approach enables Coca-Cola to maintain consistency and efficiency in its global operations.

7. Twitter: Managing Real-Time Data

Cloud Services Examples

Twitter, the social media platform, leverages IaaS to manage and process vast amounts of real-time data. Using cloud platforms like AWS, Twitter can handle high volumes of tweets, mentions, and user interactions with minimal latency. This capability is crucial for delivering real-time updates and maintaining user engagement.

8. General Electric: Facilitating Industrial IoT

IaaS Providers

General Electric (GE) uses IaaS to power its Industrial Internet of Things (IIoT) initiatives. By utilizing cloud platforms like Microsoft Azure, GE connects industrial equipment and collects data to optimize performance and predict maintenance needs. This data-driven approach enhances operational efficiency and reduces downtime.

9. eBay: Ensuring High Availability

Cloud Infrastructure Examples

eBay, the e-commerce giant, employs IaaS to ensure high availability and reliability for its global marketplace. By using IaaS providers like AWS, eBay can quickly scale its infrastructure to handle large volumes of transactions and user interactions. This reliability is essential for maintaining trust and satisfaction among buyers and sellers.

10. Zoom: Supporting Remote Communication

IaaS Use Cases

Zoom, the video conferencing service, relies on IaaS to support its global user base. By leveraging cloud platforms like Oracle Cloud, Zoom ensures high-quality video and audio communication, even during peak usage times. This scalability and reliability are critical for supporting remote work and virtual events.

Conclusion

Leading companies across various industries are leveraging Infrastructure as a Service (IaaS) to enhance scalability, performance, security, and innovation. By partnering with top IaaS providers and utilizing cloud infrastructure services, these businesses can stay agile, competitive, and responsive to market demands. Whether it's optimizing resource management, ensuring data security, or supporting global operations, IaaS provides the flexibility and power needed to drive business success in the digital age.

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viperallc · 1 year ago

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Data Centers in High Demand: The AI Industry’s Unending Quest for More Capacity

The demand for data centers to support the booming AI industry is at an all-time high. Companies are scrambling to build the necessary infrastructure, but they’re running into significant hurdles. From parts shortages to power constraints, the AI industry’s rapid growth is stretching resources thin and driving innovation in data center construction.

The Parts Shortage Crisis

Data center executives report that the lead time to obtain custom cooling systems has quintupled compared to a few years ago. Additionally, backup generators, which used to be delivered in a month, now take up to two years. This delay is a major bottleneck in the expansion of data centers.

The Hunt for Suitable Real Estate

Finding affordable real estate with adequate power and connectivity is a growing challenge. Builders are scouring the globe and employing creative solutions. For instance, new data centers are planned next to a volcano in El Salvador to harness geothermal energy and inside shipping containers in West Texas and Africa for portability and access to remote power sources.

Case Study: Hydra Host’s Struggle

Earlier this year, data-center operator Hydra Host faced a significant hurdle. They needed 15 megawatts of power for a planned facility with 10,000 AI chips. The search for the right location took them from Phoenix to Houston, Kansas City, New York, and North Carolina. Each potential site had its drawbacks — some had power but lacked adequate cooling systems, while others had cooling but no transformers for additional power. New cooling systems would take six to eight months to arrive, while transformers would take up to a year.

Surge in Demand for Computational Power

The demand for computational power has skyrocketed since late 2022, following the success of OpenAI’s ChatGPT. The surge has overwhelmed existing data centers, particularly those equipped with the latest AI chips, like Nvidia’s GPUs. The need for vast numbers of these chips to create complex AI systems has put enormous strain on data center infrastructure.

Rapid Expansion and Rising Costs

The amount of data center space in the U.S. grew by 26% last year, with a record number of facilities under construction. However, this rapid expansion is not enough to keep up with demand. Prices for available space are rising, and vacancy rates are negligible.

Building Data Centers: A Lengthy Process

Jon Lin, the general manager of data-center services at Equinix, explains that constructing a large data facility typically takes one and a half to two years. The planning and supply-chain management involved make it challenging to quickly scale up capacity in response to sudden demand spikes.

Major Investments by Tech Giants

Supply Chain and Labor Challenges

The rush to build data centers has extended the time required to acquire essential components. Transceivers and cables now take months longer to arrive, and there’s a shortage of construction workers skilled in building these specialized facilities. AI chips, particularly Nvidia GPUs, are also in short supply, with lead times extending to several months at the height of demand.

Innovative Solutions to Power Needs

Portable Data Centers and Geothermal Energy

Startups like Armada are building data centers inside shipping containers, which can be deployed near cheap power sources like gas wells in remote Texas or Africa. In El Salvador, AI data centers may soon be powered by geothermal energy from volcanoes, thanks to the country’s efforts to create a more business-friendly environment.

Conclusion: Meeting the Unending Demand

The AI industry’s insatiable demand for data centers shows no signs of slowing down. While the challenges are significant — ranging from parts shortages to power constraints — companies are responding with creativity and innovation. As the industry continues to grow, the quest to build the necessary infrastructure will likely become even more intense and resourceful.

FAQs

1. Why is there such a high demand for data centers in the AI industry?

The rapid growth of AI technologies, which require significant computational power, has driven the demand for data centers.

2. What are the main challenges in building new data centers?

The primary challenges include shortages of critical components, suitable real estate, and sufficient power supply.

3. How long does it take to build a new data center?

It typically takes one and a half to two years to construct a large data facility due to the extensive planning and supply-chain management required.

4. What innovative solutions are companies using to meet power needs for data centers?

Companies are exploring options like modular nuclear reactors, geothermal energy, and portable data centers inside shipping containers.

5. How are tech giants like Amazon, Microsoft, and Google responding to the demand for data centers?

They are investing billions of dollars in new data centers to expand their capacity and meet the growing demand for AI computational power.

Muhammad Hussnain Visit us on social media: Facebook | Twitter | LinkedIn | Instagram | YouTube TikTok

#data #data center #data centers #Google #Amazon #Nvidia #Micerosoft #viperatech

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