IT crisis: history, major blackouts and current effects

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Computer crises have been a constant companion to the digital transformationAlthough we sometimes only remember them when WhatsApp crashes, an airport is paralyzed, or the dreaded Windows blue screen appears on millions of computers simultaneously. From the first commercial computers to the explosion of artificial intelligence, recent history is peppered with bugs, global blackouts, tech bubbles, and financial scares that demonstrate just how fragile the entire system can be.

Understanding the history and current effects of these cyber crises is key to understand the extent of our dependence on technology, to assess the role of ciberseguridad and anticipate what may come after the AI ​​boom, the stock market bubbles, and the massive software failures that are crippling airlines, banks, hospitals, and governments around the world.

From the Y2000K bug to the fear of global digital collapse

A few years ago, the entire planet prepared for a supposed digital apocalypse.The famous Y2K bug, also known as the millennium error, was a simple but unsettling theory: because many systems stored dates using only two digits for the year ("dd/mm/yy"), when transitioning from 1999 to 2000, 01/01/00 could be interpreted as 1900. This meant that programs of all kinds could "believe" they had gone back a century and begin to malfunction in unpredictable ways.

The origin of this problem dates back to the 50s and 60s.Back when memory and storage were extremely expensive and limited, programmers cut corners wherever they could to save space. One of the most practical ways to do this was to abbreviate dates by omitting the century. Thus, January 1900 was stored as 01/00 and December 1999 as 12/99—a scheme we still see today, for example, on many credit cards.

For decades nobody paid much attention to the two-digit trickBecause everything was happening within the same century and there seemed to be no conflict. However, little by little, strange symptoms began to appear: records of centenarians listed in the database as four-year-old girls, batches of products expired "eighty years" before their actual date, and billing systems that calculated impossible periods. These were clues that, when the millennium turned, the mess could be monumental.

In the early 90s, the warnings began to be taken seriously.IT specialists and systems administrators warned that almost every sector was affected: banks, insurance companies, public administrations, construction companies, telecommunications operators, energy companies, transportation, hospitals, and defense systems. Any software that handled two-digit dates was a prime candidate to crash as the year 2000 approached.

Governments and large corporations reacted with a multi-million dollar investmentIt was necessary to inventory programs, databases, files, and procedures, locate all points where dates were handled, and rewrite enormous amounts of code. Specific tools were developed to scan applications, extensive test plans were defined, and on-call teams were assembled to spend New Year's Eve 1999 in front of consoles and servers, ready to... react to critical incidents.

The case of Spain illustrates the scale of the effort.The Spanish government alone allocated some €420 million to adapting systems and equipment for the millennium change, while globally it is estimated that around €214.000 billion was spent. Many organizations took advantage of this mandatory work to also introduce other strategic improvements, such as preparing their systems for the introduction of the euro.

The effective entry into the year 2000 was a moment of contained tension.Technical teams were closely monitoring developments in countries like New Zealand, Australia, and Japan, which crossed the time zone threshold before Europe or the Americas. The news arriving from the east was reassuring: the lights were still on, planes weren't crashing, and power plants were still operating.

In the end, the feared global computer collapse did not occurThere were incidents, yes, but they were mostly minor: invoices generated with incorrect dates, offline service terminals, some devices that stopped working, or isolated errors at nuclear power plants or other critical systems that were resolved without serious consequences. In Spain, for example, minor faults were detected at a couple of nuclear power plants, some gas stations, and certain automated traffic data collection systems.

The fact that the disaster did not materialize led some to speak of myth or exaggeration.However, experts agree that the danger was very real and that the reason nothing serious happened was precisely the preventative effort. If those systems hadn't been reviewed and corrected in time, the jump from '99 to '00 would have caused operational chaos in banks, businesses, and public services, with a direct impact on the economy and public safety.

The Y2000K bug left a lesson that remains relevant today.We live glued to technology, and the more we depend on it, the greater the potential impact of a massive failure. Furthermore, it demonstrated that even when faced with a problem predicted well in advance, coordinating global responses, engaging all stakeholders, and mobilizing sufficient resources in time is extremely difficult.

From bugs to massive blackouts: global failures that bring the world to a standstill

Two decades after that millennium scare, the threat of a global technological standstill has become much more tangible.This is no longer a prediction based on how dates are stored, but real computer blackouts that have grounded planes, blocked ATMs, and overwhelmed emergency services in many countries simultaneously.

The most striking example is the recent computer blackout caused by a faulty CrowdStrike updateA cybersecurity company that protects systems running Microsoft Windows, among others, was responsible for a simple content update to its Windows 10 security agent, which triggered a cascade of critical errors on up to 8,5 million affected devices, displaying the iconic "blue screen of death" on computers worldwide.

The scale of the incident was such that many experts have already categorized it as the biggest computer blackout in history.This is precisely what was feared with the Y2000K bug, but which didn't materialize then. This time, air transport, financial systems, communications, and even emergency services were suddenly disrupted, highlighting the fragility of the global digital infrastructure when it relies so heavily on a handful of key providers.

The exact origin of the problem was a "defect" in a content update distributed to Windows systems protected by CrowdStrike.The company's CEO himself had to come forward to explain, emphasizing that it wasn't a cyberattack, but rather an internal software flaw. Although the fix was rolled out relatively quickly, the damage had already been done: millions of computers were rendered unusable until the problematic file could be removed and the systems restarted in safe mode, one by one, in organizations with thousands of computers.

As the outage spread, airlines around the world began to feel the impactBusy airports like Sydney, Gatwick, and Stansted were forced to delay or cancel flights due to the collapse of check-in, boarding control, and baggage handling systems. Some airlines declared a "global ground stop," halting all operations until the situation stabilized, causing queues, confusion, and a domino effect that lasted for days.

The healthcare sector also fared poorly in this computer blackoutHospitals and clinics found themselves without access to electronic health records, appointment schedules, or computerized diagnostic testing systems. In many cases, they had to resort to manual methods, recording data on paper and prioritizing only critically ill patients while they rebuilt their systems.

The banking and financial services sectors also experienced difficult times.There were disruptions to transaction processing, problems with ATMs, and inoperative mobile applications, creating an added sense of vulnerability at a time when most payments and transactions rely on digital platforms. Some stock exchanges and financial information systems, such as the London Stock Exchange Group's Workspace platform, were also affected.

Meanwhile, many everyday services experienced intermittent failures or total shutdowns: supermarket and fast food chains with locked checkouts, media outlets with affected broadcasting systems, iconic billboards like those in Times Square turned off by the failure of their control systems, or central banks and public bodies dealing with critical applications out of service.

Although CrowdStrike quickly isolated and corrected the flaw, the recovery was not immediate.The solution required restarting computers in safe mode, locating the problematic file, and deleting it before restarting in normal mode—a very laborious process when dealing with large corporate networks. Microsoft even recommended up to 15 power cycles on some devices, illustrating the complexity of reversing a widespread vulnerability when it has been automatically distributed to millions of endpoints.

This IT blackout has also had a clear reputational and economic impactCrowdStrike shares fell sharply on the stock market and Microsoft also suffered a decline, while the entire technology sector saw the distrust generated by such a high-profile failure in a component theoretically designed to reinforce the security and resilience of systems reflected in the markets.

Large platform collapses: when everyday life comes to a standstill

Beyond blackouts linked to cybersecurity providers, recent history is full of major digital service outages that have left half the planet disconnected.A sophisticated attack isn't necessary: ​​sometimes a simple configuration error or a poorly tested update is enough to take down social networks, messaging applications, email, or even entire stock exchanges.

Meta's platforms (Facebook, Instagram, WhatsApp, and Messenger) are a good example of this fragility in the social mediaIn November 2017, WhatsApp suffered a global outage of approximately one hour, leaving millions of users without communication. In March 2019, one of the longest incidents recorded by Facebook occurred: a partial outage of up to 22 hours that also affected Instagram and WhatsApp, officially attributed to a server configuration change.

That wasn't the only time Meta's applications crashed in a coordinated fashion.In April 2019, the problems recurred for several hours, and in July of the same year, there were again simultaneous outages affecting Facebook, Instagram, WhatsApp, and Messenger, with a particular impact on Western Europe, the United States, Mexico, the Philippines, and several South American countries. In October 2021, another widespread outage occurred, this time lasting more than five hours, with global repercussions.

WhatsApp, in particular, has continued to experience highly visible service outages.In October 2022, millions of users were unable to send or receive messages for around two hours, and in July 2023, a similar global outage occurred, lasting approximately one hour. These episodes, although relatively short, have enormous social and media repercussions because they affect a tool used for both personal and professional communication.

Other major platforms are not immune to failures either.In July 2019, Twitter experienced a global outage of approximately 90 minutes, also attributed to an internal configuration change. In August 2020, Gmail, Drive, Meet, and other essential Google services suffered intermittent outages for several hours in numerous countries, affecting corporate email, video calls, and online collaboration at the height of the remote work boom.

Not all incidents affect only consumer platformsIn October 2020, the Tokyo Stock Exchange had to suspend all trading for a full day due to a problem with its main computer system, in what was considered the most serious disruption in the history of the world's third-largest stock market. And in June 2021, a failure at the CDN and cloud services provider Fastly left dozens of media websites and other services around the world either partially or completely inoperable.

These cases show that even critical or highly regulated infrastructures are vulnerable to technological errors.The interconnection between systems, the dependence on cloud providers and content delivery networks, and the constant search for efficiency and automation mean that a single failure can spread on a massive scale with a speed that would have been unthinkable just a few decades ago.

Power outages, cybersecurity, and cloud vulnerability

Modern cybersecurity has become an essential pillar for protecting critical systemsHowever, the case of the blackout caused by a faulty security software update demonstrates that these same tools can also be a single point of failure. When a security agent is deployed on a massive scale, any error in its updates can cause precisely what it is designed to prevent: a large-scale outage.

Today, organizations of all sizes, from SMEs to large corporations, rely on multiple layers of digital defense.Antivirus, firewalls, detection and response systems (EDR/XDR), continuous monitoring, backups, constant updates, and increasingly, solutions based on Artificial Intelligence and machine learning to detect anomalous behavior. The idea is to strengthen end-to-end security, but the complexity of these ecosystems also introduces new risks.

Mass migration to the cloud has multiplied the advantages, but also the attack surfaceMany companies now enjoy enormous scalability, virtually unlimited storage, and access to advanced technologies such as data analytics, AI, and the Internet of Things. However, this same centralization on cloud platforms means that a provider error, misconfiguration, or failure in the update chain can impact thousands of customers at once.

In countries like Chile, for example, more than 60% of SMEs report using cloud computing and storage solutions.This illustrates the extent to which this model has become standard even outside of large multinational corporations. At the same time, around 76% of companies report implementing specific cybersecurity and information management plans, aware that a single successful incident can have devastating effects on their operations and reputation.

The recent IT outage has reinforced a key idea: relying on a single provider is not enough.The affected companies, whose entire security infrastructure and part of their operations relied on the same service, found themselves without alternatives when it failed. This is why the multicloud approach and provider diversification are gaining importance, with the aim of avoiding dependence on a single point of failure and having realistic contingency plans in place.

Among the technical lessons learned from this incident, three aspects stand out.The first is the need to thoroughly test any update in isolated and controlled environments before mass deployment. The second is the importance of having clear and proven rapid response plans that allow for agile action to minimize damage. The third is transparency: acknowledging errors, explaining what happened and what is being done to fix it and prevent its recurrence is fundamental to regaining the trust of customers and the market.

Companies in any sector, not just those dedicated to cybersecurity, should internalize these lessons.Designing robust cybersecurity policies and strategies, investing in training, maintaining up-to-date systems, and defining clear protocols for serious incidents is no longer optional, but a basic condition for operating in a hyperconnected world where a computer failure can translate into economic losses, legal problems, and image crises in a matter of hours.

The artificial intelligence boom as a new source of crisis

While blackouts and large-scale failures are multiplying, another force is completely reshaping the technological landscape: artificial intelligence.In just a few years, generative AI, language models, and autonomous agents have gone from being a distant promise to an economic and technological engine that permeates almost everything, from software development to customer service, marketing, and financial analysis.

Models and services like those of OpenAI, DeepSeek and other competitors have marked a turning point.What began as a kind of mirage, with a spectacular rise of hardware companies like NVIDIA, has solidified into a sustained boom that continues to drive demand for computing power, energy, and specialized talent. AI has been sold as a kind of panacea, and today it is sought after by both everyday users and large corporations.

This boom is even generating fears about a possible AI bubble.With clear parallels to the dot-com bubble of the late 90s. Back then, it was the internet that seemed capable of justifying any exorbitant valuation; now it is artificial intelligence that has sparked the enthusiasm of investors, venture capital funds and large technology companies, fueling valuation growth that in many cases does not yet correspond to the actual generation of income.

In the previous bubble, companies like Lycos, Terra, and Boo.com ended up disappearing.While others like Amazon weathered the storm and emerged stronger after a tough market cleanup process, similar dynamics are evident today: AI startups are proliferating in search of a quick buck, often driven by large funds and constant media pressure, while giants like Google, Microsoft, and Elon Musk's projects compete fiercely to dominate this new technological frontier.

The difference now is that AI already has well-established, profitable uses.Cloud services, process automation, specialized semiconductors, productivity tools, and advanced analytics solutions generate tangible revenue for established companies. Furthermore, financial markets have more sophisticated risk analysis tools than in the 2000s, and the global digital infrastructure is much more mature, which, in theory, could foster somewhat more sustainable growth.

Even so, the dependence on AI in economies like the US is extremely highSome analyses estimate that around 40% of recent US economic growth is linked, directly or indirectly, to this technology. And it's not just an economic phenomenon: the industry's biggest names—Elon Musk, Mark Zuckerberg, Jeff Bezos, and others—now wield considerable political influence and have little interest in allowing a bubble to burst uncontrollably, although some weeding out of unviable projects is almost inevitable.

Hardware pushed to its limits: GPU, RAM, SSD and HDD under pressure

The artificial intelligence boom is not only reflected in balance sheets and headlines, but also in the physical hardware that supports the entire industry. chip revolutionData centers dedicated to training and running generative AI models have become real resource hogs: they need brutal computing performance, huge amounts of memory and storage, and extremely high-bandwidth networks.

At the heart of this infrastructure are GPUs and other specialized acceleratorsGraphics cards like the NVIDIA H100, Blackwell architectures, AMD Instinct solutions, and Google TPUs have relegated traditional CPUs to the sidelines for many AI workloads because they allow for massively parallel processing of huge volumes of operations, albeit with less precision. This shift has driven up demand for GPUs in data centers, partially displacing the supply destined for the consumer and gaming markets.

The result is a genuine crisis in the consumer GPU marketBy prioritizing the manufacturing and allocation of stock for AI-oriented and professional-grade models, many manufacturers have reduced their focus on the consumer segment. There are fewer graphics cards available for gamers and content creators, and the few units that do reach stores are priced inflated, putting upgrades out of reach for a significant portion of users.

Memory is also suffering a huge impact, especially in the area of ​​DRAM.Modern GPUs and accelerators not only require conventional RAM for the CPU, but also high-bandwidth memory (HBM) chips for their own VRAM, multiplying global demand. Manufacturers like Samsung Electronics, SK Hynix, and Micron have been increasingly shifting production capacity toward enterprise-grade HBM and DRAM, reducing supply for the traditional PC, mobile, and other consumer device markets.

This production reorientation, along with the classic cyclical volatility of the DRAM market, has generated a perfect stormAfter a period of overproduction and falling prices, many manufacturers cut capacity. Just then, demand linked to AI exploded, causing a sharp adjustment in supply. The result: shortages and unprecedented price increases for DDR5 modules and similar products, to the point that some memory kits have reached prices of several thousand euros.

The impact has been so strong that historic brands in the consumer segment have closed down.This is the case of Crucial, Micron's brand for home RAM and SSDs, whose commercial disappearance was announced for February 2026, symbolizing the progressive abandonment of the end user by large manufacturers who prefer to focus on more profitable businesses linked to data centers and enterprise applications.

Storage, both in the form of SSDs and HDDs, is not immune to the pressure from AI either.Data centers that train massive models require monstrous capacities to store datasets, checkpoints, and logs. This drives up demand for both high-performance NVMe SSDs, ideal for intensive workloads and fast access, and large-capacity traditional hard drives, used in nearline environments for cold or historical storage, where cost per terabyte matters more than speed.

NAND memory manufacturers, led by companies like Samsung, SK Hynix and Micron itself, have had to readjust their production, in line with the chip law Following a period of oversupply, production cuts coincided with the rise of AI, creating availability issues and significant price increases, particularly for high-density enterprise SSDs. In the HDD sector, companies like Western Digital and Seagate have also seen their entire stock committed to large contracts, leaving little room for the retail market.

For the end consumer, all of this has translated into a rather painful paradigm shiftBy 2026, PC hardware prices—especially GPUs, RAM, and storage drives—had risen so dramatically that upgrading their equipment had become virtually impossible for many users. And the problem isn't limited to desktop computers: mobile phones, routers, smart TVs, and other devices that rely on DRAM and flash memory had also become more expensive.

Faced with this situation, many users are looking to the second-hand market or to new players, especially Chinese manufacturers.Companies like CXMT, specializing in DRAM and capable of producing DDR5-8000 modules, or YMTC, focused on high-density NAND Flash with technologies like Xtacking 4.0 to reach capacities of up to 8 TB, have become interesting alternatives for consumers, often integrated into brands like Netac, Asgard, KingBank or Gloway.

There are even extreme proposals such as manufacturing RAM modules by hand.From Russia came news of individuals and groups considering assembling their own memory due to high prices and lack of stock, an anecdote that illustrates the extent to which the traditional hardware market has become unbalanced by prioritizing the AI ​​craze.

Software, AI and the so-called "SaaSpocalypse"

While hardware is being pushed to its limits and data centers are multiplying, the very concept of software is undergoing a profound transformation.Since Marc Andreessen coined the phrase "software is eating the world" in 2011, the development and distribution of applications have shifted towards a model dominated by SaaS (Software as a Service), in which applications cease to be products you buy once and become subscription services in the cloud.

Classic programs like Photoshop or Office are now ongoing servicesAccessible via browser or connected applications, for a monthly or annual fee. This model has allowed software companies to generate recurring revenue, but it has also led to abuses: aggressive price increases, rigid contracts, and a growing sense of captivity among customers, who feel tied down by their data, their integrations, and the complexity of migrating to another solution.

The rise of AI is putting this model under pressureGenerative AI tools and intelligent agents allow organizations—and even individual users—to create customized solutions, automate tasks, and, in some cases, eliminate the need for expensive licenses. At the same time, we've seen brutal stock market corrections in SaaS companies like MongoDB, Salesforce, Shopify, and Atlassian, which lost between 15% and 20% of their value in a matter of hours, fueling the narrative of a supposed "SaaSpocalypse."

Part of this adjustment has to do with the dynamics of valuations themselves after the pandemicThis inflated expectations about the infinite growth of SaaS. But it also reflects the weariness of many customers with abusive commercial policies, such as Salesforce's 35% price hikes or Broadcom's increases of up to 1.500% in virtualization software licenses in Europe. AI appears here as a kind of key that allows users to "escape" these dependencies.

However, talking about the death of software is, in all likelihood, an exaggeration.Authoritative voices like that of Steven Sinofsky, former head of Windows at Microsoft, point out that major technological transitions rarely completely destroy what came before. The PC didn't kill the mainframe, but rather integrated it; e-commerce didn't eliminate the physical store, but rather gave rise to omnichannel giants. Something similar will happen with AI: there won't be less software, but much more, because countless processes remain to be digitized or optimized.

What does seem clear is that the role of the human developer will change.AI is taking over many routine programming tasks, especially through "vibe coding" or "agent engineering" tools that allow anyone to prototype and build micro-applications by simply logging instructions in natural language. This democratizes development, but it also creates a new technical debt: who will maintain all that machine-generated code in three years?

Figures like Linus Torvalds have expressed it bluntlyAI will be a fantastic tool for getting started with programming and increasing productivity, but the code it generates will be difficult to maintain without a solid foundation of knowledge. Programmers won't disappear; their role will evolve into that of systems architects and supervisors, responsible for ensuring that what is deployed in production is robust, secure, and sustainable over time.

Added to all this is a critical issue of data sovereignty and securityIf the software we use, or parts of it, is generated and run on third-party platforms such as those of OpenAI, Anthropic, or other providers, legitimate concerns arise regarding intellectual property, the privacy of corporate information, and strategic dependence. In a context where IT outages have already demonstrated that a failure in one provider can paralyze half the world, placing even more power in the hands of a few actors poses obvious risks.

The so-called "SaaSpocalypse" may not be an apocalypse, but a profound metamorphosis of the software market.Logic points to a future in which developers and technology companies will sell not so much licenses or lines of code, but results, autonomy and services that self-adjust in real time, always within a framework of strong human supervision and clear responsibility for what happens to the data.

Looking back, from the Y2000K bug to recent mass blackouts, through the AI ​​craze and hardware and software crises, an uncomfortable but obvious pattern emerges.Every technological leap amplifies both opportunities and vulnerabilities. We live more connected, automated, and powerful lives than ever before, but we are also more exposed to the possibility that a single failure, a poor design decision, or a simple faulty update could have global consequences. The key is to accept this fragility as part of the game and, with a bit more humility, build systems, markets, and business models that won't collapse at the first serious bug.