A lot of things have changed in recent years. From the way of working to executing IT operations, the business strategies have changed overnight with arising advances like Machine Learning, Automation, and Artificial intelligence.
The technologies have changed present-day applications and IT operations, and with AI and ML on board, IT industries operate more perplexing undertakings and resolve issues across complex infrastructures. The integration of AI and ML into IT operations has led to AIOps, an advanced and insightful analytical strategy to function IT operations with ease like never before.
With endless potential, AIOps can discover specific conditions and behaviors that can precede the problems. Enterprise integrates AIOps to turn the data into action-driven information and automate the IT operations.
AIOps in 2022
As predicted by Gartner, half of the organizations will be utilizing AIOps with its applications to perform crucial IT operations. With the evolving industry and changing market every day, it is said that the worldwide AIOps market is conjecture to arrive at around $3127.44 million by 2025.
Here are the AIOps trends in 2022 everyone should be keeping their eyes on.
- IT Industries and AIOps: When AI has extraordinary adoption cases, last year, IT pioneers will genuinely observe the AI’s capabilities for IT tasks to scale up. Besides, as AIOps solutions mature, they tend to process a broader range of data types and perform faster increasing efficiency.
- Incident Management Capacities: AIOps will be used to increase natural language preparing, anomaly detection, event correlation, and analysis. Event management and incident intelligence will become more robust, resulting in an optimal incident management platform.
- Intelligent and Immense Automation: Automation, a huge strength of AIOps, offers various functions to computerize explicit IT measures. Compared to traditional solutions, today’s AIOps comes with robotic data automation to tame the information issues, resulting in a drastic reduction in the requirement of human intervention.
- Boosted Cyber Security: Even with all the innovations and advantages, the battle for cyber security remains the first concern among the enterprises, which is evident. With more incorporated security and IT activities, the implementation of AI-ML immediately identifies the issues and measures them before they even occur.
- AIOps and DevOps: With all the automation and monitoring solutions, DevOps operations can be benefited. AIOps can be helpful for IT departments by processing all the data quickly, performing data analysis, and automating mundane tasks. In addition, it helps DevOps teams monitor, manage, test, perform and secure operations seamlessly.
How to Implement AIOps
The concept of Big Data was introduced back in 2005, and that’s when the journey of AIOps started. In 2017, the term AIOps came into the picture as the need for organizations to comprehend all of their data in real time grew. The term grew and evolved in 2019 with multi-domain AIOps.
With Covid-19, cloud immigration, and digital transformation, the need for AIOps has only increased. Business leaders are considering AIOps as per their requirements and benefits. Here are the five steps businesses can approach to integrate AIOps into their business strategy and start 2022 with IT automation.
- Aligning Business Requirements: AIOps being a multi-domain technology, it is crucial to align your strategy with your business requirement and challenges. AIOps supports around eight different domain-specific roles. So, it’s advisory to plan it accordingly.
- Observer and Integrate: A concept of AIOps is to collect data from everywhere, such as networks, servers, and applications. The more data AI analyses, the better it performs. Moreover, the more domains covered, the more likely it is to discover the source of any problem. Hence, observe the infrastructure, analyze and integrate required domains.
- The use of AI: After businesses have approached the integration of IT operations data, IT professionals should consider AI as their next appropriate step. Various domain solutions come with AI capabilities these days but with their own silos. With AI-driven toot cause analysis, it is easier to resolve even missed opportunities.
- Centralize Data Lake: The next step should be to create centralized data lake to integrate AIOps better. ML can process all the data from various domains with all the available data, easing to construct data-driven actions. In addition, when AI has all the data in one place, the platform can examine to identify the behaviors and issues which will benefit the business.
- AI Automation: Adopting AIOps aims to discover the problems and resolve them faster. After discovering the common repeatedly occurring problems, with the help of ML to find the root cause and connect it with a workflow to fix the issues automatically.
Undoubtedly, 2022 is the year for enterprises to focus on strategizing AIOps to execute IT applications better and manage infrastructure robustly. Of course, the journey of AIOps can be different for each business, and the order of steps may change. However, the first step can be to make a change to achieve success ultimately.