Artificial Intelligence and AIOps May Be the Key to Understanding Today’s World of Exploding Data
Posted: Wednesday, Jul 26

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Artificial Intelligence and AIOps May Be the Key to Understanding Today’s World of Exploding Data

“The Library of Babel” is an imaginary library containing countless rooms and books with every possible combination of letters and numbers.

The librarians and readers in these rooms spend their lives parsing through the information, but despite their best efforts, the readers cannot find one particular book they’re seeking. Many visitors find the library’s vastness and the amount of information completely useless, leaving them unable to process the books and in deep despair.

Humans will likely never build a Library of Babel using English, given the incomprehensible number of possible permutations and combinations of our 26-letter alphabet and 14 different punctuation marks. By using just 26 letters, there are more than 400 septillion ways to create one “word” (most will be nonsensical combinations of letters) – let alone entire sentences, paragraphs, or books.

It’s no wonder the librarians of Babel started to go mad.

Imagine a technological Library of Babel – a seemingly never-ending amount of data and information. An ever-expanding collection of ones and zeros, each unique combination representing something different – an application, a photograph, a song, a contract, a book. The combinations are endless.

The amount of data produced daily is mind-boggling; each year, these figures grow at an increasing rate. For reference, more data was collected between 2019 and 2021 than in all human history. How could the IT professionals tasked with managing these exploding amounts of data on behalf of their organisations ever be expected to do so effectively?

Much like the librarians of Babel, how can these modern IT people avoid going insane?

The stakes for IT professionals are high, and coping with exploding amounts of data is a skill set unto itself. Effectively monitoring and analysing this increasing information is critical for companies hoping to remain productive and profitable. If a company cannot recognize irregularities in data, it may lead to an application crash, resulting in lost sales or times when employees can’t work. With companies responsible for more data than ever – which may include sensitive personal information – threat actors are also always on the prowl, hoping to steal this information. Stolen or breached data can result in massive fines and penalties.

Thankfully, humans are no longer expected to overcome the challenges of analysing, managing, and controlling increasing amounts of data alone. Today, they have allies in these endeavours: artificial intelligence (AI), machine learning (ML), and AIOps.

AI and ML are powerful solutions transforming how IT professionals manage and analyse data to optimise performance, improve business outcomes, and mitigate security risks. Because these technologies process massive amounts of information no human ever could, they help IT professionals optimise IT performance by ensuring applications and services are running properly. This is a particularly tall task today, given that many companies’ computer systems run in multiple clouds and rely on hundreds of applications to get work done. AI and ML can predict and prevent application or system crashes and outages by automatically analysing key performance metrics. If you’ve ever tried to do your job and your computer or software keeps crashing, you know how frustrating this can be. With AI and ML, IT pros can improve the performance of these applications and services, which allows employees to work more efficiently.

Imagine if you were a librarian in Babel and had a virtual assistant read and analyse all the books for you. This would free up time for you to pursue other projects, like decorating the library, training new librarians, or signing partnership agreements to franchise the library.

AIOps is a relatively new term Forrester® describes as a “practice that combines human and technological applications of AI/ML, advanced analytics, and operational practices with business and operations data.” With AIOps, businesses can identify patterns and anomalies potentially signalling problems in an IT environment. They can quickly correlate vast amounts of data to provide root cause analysis and recommended remediation strategies. With AIOps, IT pros can receive end-to-end visibility—regardless of a company’s infrastructure or where they may be on their digital transformation journey—reducing the time spent troubleshooting while improving system reliability.

Though these advanced technologies help people parse and make sense of exploding amounts of information, they can also be considered problematic. For example, generative AI tools like ChatGPT® and OpenAI® Codex are being used to produce text and software code, respectively, directly contributing to a glut of daily data and information.

If we stop and think about the impacts of AI and ML, at what point do the means no longer justify the ends? On the one hand, these technologies enable digital transformation efforts by helping IT teams sort through all this information—on the other hand, these tools are simultaneously creating a never-ending flow of more information to process.

Imagine this as an almost infinitely large data stream constantly growing longer and longer. Try not to get dizzy.

The explosion of data presents significant challenges for IT pros related to managing and analysing today’s complicated IT environments. However, AI, ML, and AIOps are transforming how IT professionals work, enabling them to automate tasks, detect security threats, optimise performance, and make better decisions based on data analysis.

All organisations looking to implement these tools must do so with clear human oversight and boundaries. In the Library of Babel scenario, though AI tools could search through every possible book far faster than a human could, they still wouldn’t be able to “think” for themselves like humans can. AIOps isn’t a replacement for the work needing to be done. Instead, we should view it as an aid in understanding the information we can’t possibly read through – even over a thousand lifetimes.

Sascha Giese
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