A definitive guide to AIOps

Have you ever wondered why Artificial Intelligence, fondly known as AI, is the most popular choice among businesses aiming for a digital transformation?  Allow me to tell you about how the term AIOps came into existence.  Simply put, cutting-edge AI technology has the potential to disrupt modern IT systems with its ability to determine the challenges in business environments by replicating human intelligence and leveraging it to take over complex decision-making.

With ever-evolving business scenarios, the integration of AI into IT operations has led to the emergence of AIOps which uses big data analytics, machine learning, and cognitive engineering to accelerate the process of complex decision-making in the realm of IT. I will now explain what exactly AIOps is and how it is beneficial for different IT industries.

What is AIOps?

In 2016, Gartner, coined the term Artificial Intelligence for IT operations (AIOps) to simplify and enhance IT operation analytics. Gartner defined AIOps as “A combination of big data and machine learning to automate IT operation processes, including event correlation, anomaly detection, and causality determination.”

With IT at the heart of digital transformation, AIOps is the best platform for present and future business operations. With its ability to automate as well as provide a real-time understanding of any issues to IT teams, AIOps must be at the top of your list of potential investments for your business.

Working of AIOps

You should know that not all AIOps platforms are created equal. Every organization should employ it as an independent platform so that it admits data from all IT sources and acts as a central system of engagement, customized AIOps that is just right for you!

The five key steps to fully automate and streamline IT operations include-

1. Filter Data – AIOps involves classification of the data as per the modern IT environment and filtering the data that indicates any problem or duplicity. It uses analytics like rule application and pattern matching to separate significant data from irrelevant data.  
2. Discover Patterns – With AIOps, you can find a relationship between the selected and meaningful data elements. You can make an advanced analytics report by correlating and grouping the data to monitor the performance more closely.  
3. Draw Inference – AIOps lets you identify the root cause or problem in advance so that you can act on what is discovered. 
4. Collaborate – With AIOps, you can notify and collaborate with the appropriate teams to accelerate the future diagnosis.  
5. Automate – AIOps facilitates you to make solutions quick and accurate by automating response and remediation.  

An AIOps platform merges with the existing tools and brings together information and insights that were earlier disconnected. The IT team uses multiple tools to monitor the data but getting access to each tool and its insights is nearly impossible. AIOps brings them all together and facilitates seamlessly shared visibility across all tools and domains.  

AIOps across industries  

According to Gartner, there are five primary use cases of AIOps namely performance analysis, big data management, event correlation, anomaly detection, and IT service management. Let me tell you some uses of AIOps in different industries.  

1. AIOps in Healthcare IT – You can automate the IT operations with AI to enhance system performance. AIOps helps in keeping electronic personal healthcare information safe in compliance with HIPAA.  You can also prevent ransomware attacks and hazards of mobile networking by utilizing AIOps. Additionally, you can delve into voluminous data that is made available for research and diagnostic use.  
2. AIOps in Retail – AIOps helps in syncing data across all retail platforms and keep customer data and information secure and safe. It ensures flexible infrastructure to add new technologies. With AIOps, you can also reduce costs by maintaining effective operations and supporting multiple devices in the retail store. 
3. AIOps in Manufacturing – AIOps helps in better utilization of data to create efficient supply chain management systems. It uses machine data to predict maintenance. With real-time monitoring, you can keep a track of machines on the factory floor gathering data such as capacity utilization, manufacturing cycle times, supplier quality levels etc.  
4. AIOps in Banking and Financial Services – AIOps helps in improving network speed and performance. It ensures data security and prevents cybercrimes. By making customer data available, AIOps helps in driving marketing and growth opportunities in the BFSI sector. You can also predict revenue growth by analyzing historical customer data.  

 Benefits of AIOps  

By now, you already know that AIOps is essentially the strategic use of AI, machine learning (ML) and machine reasoning (MR) technologies to streamline and simplify processes and optimize the use of IT resources. Its benefits include- 

• Saving time and cost, thereby enhancing the organization’s efficiency and productivity.  
• Allowing experienced engineers to devote their time to more value-added work and avoid manual work.  
• Enabling businesses to make better use of data to accelerate digital transformation.  

AIOps is used in companies that use DevOps or cloud computing and provides additional insights to the development team. It eliminates the risks involved in hybrid cloud platforms, detects problems in the IT environment earlier, and allows smooth communication between teams. AIOps and DevOps amalgamate and equip operators to work smarter and build reliable services.  

Reach out to us at Nitor Infotech to learn more about how you can employ AIOps along with DevOps to run your business efficiently by mitigating manual intervention and take a look at our blog to know some amazing facts on AI Engineering.