AIOps – Artificial Intelligence for Your IT Operation
Imagine being able to predict IT problems before they happen, or even prevent them from happening in the first place. Can you imagine how much easier and more efficient your daily work would be? This is no longer a dream, but reality thanks to AIOps.
The four steps of IT operations analysis
Let’s take a real-life example: You work for an online retailer that is about to launch its biggest sale ever. Suddenly, a serious outage occurs, right at 4pm on Saturday. A nightmare scenario, isn’t it? With AIOps, you can handle such situations much better. Ideally, AIOps maps all four of the following steps in this scenario:
Your AIOps system would first detect that a problem has occurred and tell you exactly what happened.
It would then show you why the problem occurred and give you the information you need to understand the problem.
With machine learning, the system could even predict what further problems might occur based on the current failure.
Finally, it would show you what steps you need to take to fix the problem and avoid similar problems in the future.
The 5 capabilites of AIOps according to Gartner
According to Gartner’s definition, AIOps have capabilities such as:
Cross-domain data collection and analysis
AIOps can collect and analyse data from different sources and domains, providing a comprehensive overview of the IT landscape.
Topology compilation from implicit and explicit sources
AIOps depict the relationships and dependencies between different IT components to provide a clear picture of the entire IT infrastructure.
AIOps use pattern recognition to detect incidents, their precursors or possible causes.
Automated problem solving strategies
AIOps can not only detect incidents but also suggest potential solutions.
Correlation of events
AIOps can identify and merge different events related to an incident to avoid redundant alerts and quickly identify the origin of a problem.
How AIOps Revolutionises the IT Landscape
With AIOps, we can make IT monitoring more efficient, effective and future-proof.
Proactive Fault Management
AIOps detects and anticipates IT problems before they become real disruptions.
Efficient Operation Analysis
AIOps provides a comprehensive, data-based overview of the IT environment in real time.
AIOps uses machine learning to predict the future performance of the IT infrastructure and proactively plan maintenance work.
AIOps does not only represent an improvement of existing IT monitoring practices, but marks a paradigm shift. It’s no longer just a tool, but a holistic strategy for managing IT systems.
Instead of working in isolated silos, AIOps links data from various sources to provide an overview of the IT landscape. It enables IT teams to think outside the box and take a proactive approach to troubleshooting and maintenance.
With the help of AIOps, companies can streamline their IT operations and make them more efficient. AIOps helps them respond better to unexpected events and deploy their resources to the full. In short, AIOps makes IT teams better equipped to meet the demands of the digital era.
In the future, we will see even greater integration of AIOps in IT systems as more and more companies realise and take advantage of the benefits of this technology. The revolution has just begun – and AIOps is at the core of it.
A comparison: Traditional Monitoring vs. AIOps
Traditional Monitoring without AIOps
- Predominantly reactive approach based on static rules and thresholds.
Isolated data views due to separate data silos. Lack of automation requires manual intervention by IT staff.
Lack of ability to predict and prevent future problems.
- High time expenditure for problem-solving instead of strategic optimization.
Monitoring with AIOps
- Data consolidation from different sources for a holistic view of the IT infrastructure.
Usage of artificial intelligence and machine learning to detect patterns and identify potential problems early.
Proactive instead of reactive monitoring.
- High automation relieves the IT staff and enables to focus on more strategic tasks.
- Prediction of future performance issues and failures to minimise downtime and optimise system performance.
The “Human Machine Alliance”
Will AI replace us soon? In this context, it is important to emphasise that AIOps does not aim to replace humans, but to complement and enhance our capabilities.
In fact, McKinsey stated that machines and humans can work better together than they could on their own in many areas. For instance, we can already observe this in the area of medicine and production logistics.
Studies have found that mixed teams of humans and machines were more coordinated and efficient and had fewer accidents than human-only or machine-only teams.
That said, the idea of AIOps replacing us should be replaced by the idea of AIOps helping us become better.
AIOps is all about enhancing and improving human capabilities, not replacing them.
»What if we really prioritize creating a future of work in which machines join the team instead of replacing us?«
If we consider machines as partners rather than servants or tools, we can maximise our innovation potential by building teams that augment human capabilities instead of replacing them.
Ultimately, AIOps is about fostering a human-machine alliance that increases both efficiency and creativity. This way, AIOps becomes a tool that helps us unlock the full potential of our digital landscape.