What Is AIOps? How does it work?| Elements |Benefits | User Cases | Future of AIOps.

What Is AIOps?

AIOps stands for Artificial intelligence IT operations. AIOps refers to a multi-layered technology that automates and enhances IT operations. It uses smart algorithms (supported by AI and ML), where machines solve known IT problems and intellectually automate repetition.

Through algorithmic analysis of IT data, AIOps helps the IT ops and DevOps team to work smarter and faster, so that they can detect and fix digital-service problems before they affect business operations and customers. AIOPs thinks of  continuous integration and continuous deployment for core IT functions. It is important to understand that AIOPS has two main components: Big Data and Machine Learning.

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AIOPS uses analysis and machine learning to analyze big data from a variety of IT operations tools and devices. As a result, it is able to automatically spot, and more importantly, respond to cases in real-time.

Elements Of AIOps

• Extensive and diverse data
• Aggregated big data platform
• Machine Learning
• Observe
• Engage
• Act.

How Does AIOps Work?

Not all AIOps products are created equal. To get the highest value, the organization should deploy as a separate item that incorporates data from all IT monitoring sources and acts as a central system of investment.

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Such a platform should be supported by five types of automated algorithms and direct five-dimensional IT performance monitoring:

• Data selection:- Taking the highly redundant and noisy IT data created by the modern IT environment and selecting data components that indicate there is a problem is often filtering up to 99% of this data.
• Pattern discovery:- Improving and finding the relationship between the semantic data components and their grouping, selected for further analysis.
• Inference:-Identify the root cause of the problems and recurring problems so that you can take action on what was discovered.
• Collaboration:-Notify the right operators and teams and collaborate with them, especially when people are geographically dispersed, as well as save data on events that can speed up the future diagnosis of the same events.
• Automation:- To make the solution more precise and quick, automatic response and solution as much as possible.

AIOps Benefits

• Achieve faster Mean Time To Resolution(MTTR)
• Go from Reactive to proactive  to  predictive management
• improve your IT operations and your IT operations team

AIOps User cases

1. Anomaly/Threat detection
2. Event correction
3. Intelligent alerting and escalation
4. Incident auto-remediation
5. Capacity optimization

Future Of AIOps

• Technology becomes more human.
• The automation of technology and hence, business processes
• Enterprise ITOps gains DevOps agility
• Data becomes currency

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