AIOps, also known as artificial intelligence for IT operations has many use cases in cloud environments like threat intelligence analysis, malware detection, and has the potential to give sound advice on implementation considerations. According to Gartner's research, the implementation of AIOps in enterprises is expected to reach 30% by 2023. With industries adopting the cloud without hesitation, now is the time for businesses to learn about this advanced monitoring technology to optimize their cloud security operations.

Features Of AIOps

AIOps brings many advantages to the table. It implements large-scale data monitoring and analysis. This helps in improving the efficiency of altering and identifying underlying problems in the IT environment. In some cases, this technology can also help with behavioral trend analysis and automated remediation.

AIOps comes with the following features:

• Diverse data sets

• A large-scale platform powered by big data to aggregate data and event information

• Machine learning algorithms and analytics processing

• APIs and automation capabilities

• Granular reporting

How AIOps Applications Can Optimize Cloud Security Operations For A Business

AIOps combines big data and machine learning for automation. This affects cloud security operations in many good ways. But this effect will only be visible if all the preconditions are met. With everything set right, like the investments in the budget, architecture, and skills, here are five of the most effective use cases of AIOps to optimize cloud operations and security.

1. Threat Intelligence Analysis

Threat intelligence gives perspective on the source of the attack, shows all the behavioral trends related to the use of the cloud account along with attacks against various cloud services. Threat intelligence feeds can be collected and analyzed at scale using machine learning engines in the cloud that can be processed for predictability models.

AIOps has a wide variety of IT operational data in use as a part of AIOps along with additional threat intelligence from external providers. These attributes will help security operations teams to predict and assist during attacks on cloud infrastructure, particularly in the case of account hijacking.

2. Security Event Management

Businesses who have digitaized their processes are flooded with data. Security teams need to be alert at all times to identify specific indicators, event patterns and spot events in the cloud system. With machine learning and AI capabilities, AIOps can augment massive data processing technology to have stronger intelligence detection and alerting plans of actions.

3. Fraud Detection

For firms that deal with financial services and insurance, fraud detection requires many inputs and data types along with intensive types of processing. Text mining, database searches, social network analysis and anomaly detection are a part of this system. These attributes are combined with predictive models to help detect frauds quickly.

4. Malware Detection

Large-scale event processing of data and files can help ransomware and malware detection, especially of those data points with unknown signatures, thanks to machine learning and AI technology. While the AIOps supports this application, custom malware detection requires security professionals who are highly skilled in this domain.

5. Data Classification And Monitoring

Also known as content types and patterns, AIOPs analysis engineers process the entire data uploaded to classify and tag them on the basis of predefined policies and then monitor them for access. Data-specific monitoring depends on operation teams to manage many types of data with the help of security and risk teams to tag along and track data types or patterns.

AIOps has the ability to naturally align with security-specific use cases. However, challenges in sourcing cloud-specific security skills in personnel, data import and export costs, and aligning these practices with internal business functions is a challenge. Integrating IT operations and security will require some time and effort but will benefit businesses that run on cloud?