Do you know AIOps and what its characteristics?

Let's start by understanding that it is AIOps, it is established that this technology combines the power of Big Data and Machine Learning to automate the processes for IT operations, including the correlation of events for the anomaly detection and determination of causality. In simpler words this is Artificial Intelligence for IT operations, that is, where AI and its subsets are leveraged to monitor and solve problems related to IT operations within any company.

According to the following report, the market with this technology is estimated to be around 6.8 billion USD by 2025. Digital transformation has undoubtedly redefined business operations and ITOps are no exception, so large companies with multi-layered operating systems can benefit from this to accelerate critical services.

AIOps is also known as the AI for operations, you have various use cases in cloud environments such as threat intelligence analysis and malware detection. According to Gartner, AIOps implementation in enterprises is estimated to reach 30% by 2023. With industries embracing the cloud without hesitation, now is the time for companies to learn about this advanced monitoring technology to optimize their cloud security operations.

Characteristic

When it comes to advantages, AIOps brings many advantages, such as large-scale data monitoring and analysis. This will allow us to improve the efficiency of identifying underlying issues in the IT environment. In some cases, we may also apply the use of this technology for behavioral trend analysis and automated correction.

Among its main characteristics, the following stand out:

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  Various data sets.
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  A large-scale platform powered by big data to aggregate event data and information.
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  Analytical processing and machine learning algorithms.
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  API and automation capabilities.
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  Granular reports.

At the end of it all comes the million dollar question. Can AIOps applications help in cloud security operations for an enterprise?

By combining Big Data with Machine Learning for automation, cloud security operations can be assisted in the following ways:

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  Threat intelligence analysis
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  Security event management
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  Fraud detection
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  Malware detection
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  Data classification and tracking