Feb 3, 2021. By Anil Abraham Kuriakose
Artificial Intelligence for IT operations (AIOps) is definitely on the go soon. The benefits AIOps poses or holds on the IT enterprise or even the benefit it brings on business is really great. These benefits make almost every organization move forward in the adoption of AIOps. The major reason for this adoption of AIOps is that, the world is changing into an era of digital transformation. This transformation can never be avoided as most organizations value and growth belongs in this current trend. A study indicates that 68 percent of IT decision-makers at companies with 500 or more employees have experimented with AIOps tools. And 73 percent are using AIOps to get greater insights into system alerts. So as we can see, the adoption of AIOps is a fire. But this adoption calls in for a really great challenge, which is nothing other than having the right skill set of people to deliver the right quality of AI based IT production. Let just say successfully implement the phase of cognitive automation. The adoption of AIOps really requires in acquiring really skill set of IT team for the right delivery of process and works. This brings in a lot of pressures on the current ITOps team.
The concept of AIOps is nothing other than applying machine learning and artificial intelligence to IT operations. That is completing automating the process that comes under the IT operations. Which really brings a big sigh of relief for the IT team as they can focus on the work. By empowering AI in analyses of both IT and business data, AIOps enables in providing the right quality of inference from data by providing automatic alerts such as events or anomaly detection and also ensuring in providing better service levels and also better production. Moreover, with AIOps the concept of Zero-Touch IT Operations is also a promise, as the auto remediation of incident tickets or auto fulfilment of service tickets are made possible.
All of these capabilities are achieved by implementing AIOps. But as mentioned before, this calls in for a great or lets just say a revolutionary changes in the current ITOps team. The change around of IT team or the current ITOps is highly needed. This frees up human capital to focus on the aspects of IT Ops that cannot be managed automatically by AI — empowering IT teams to spend their time on more complex, value-driven projects. Lets see what are the most needed or essential skill set that is actually needed for the successful adoption of AIOps.
AIOps and New IT Skill Set
In order to realize the potential benefits of AIOps fully, IT professionals will need to enhance their skill sets so that they can manage the work of AI, rather than doing the work directly. Besides many traditional IT Ops skills, the following enhanced skills will also need to be learned in order to facilitate the transition.
Machine Learning Operation skills:
The basic under stone or the building block of AIOps lies in the foundation of machine learning. ML is basically concerned to be the subset of AI based on patterns recognition and autonomously learn and enrich the environment. ML algorithms give AI the capability of ingesting and understanding new information on its own. Machine learning automates analytical model building. So, as mentioned ML is the base foundation for AIOps. Acquiring the right knowledge on ML is highly essential.
Model Development Skill:
Model development can also be considered as a base for AIOps. That is, the right amount of skill is required to develop AI based models, which is able to ingest all type of data, whether it be structured or unstructured data and provide inference from it. For this AI based model development skills are highly essential and required.
Feature Engineering skill:
Feature engineering is the process of extracting features from raw data using data mining techniques. Data is a highly essential content for every IT organization and business. Inference from each work is processed from these data. So this calls in the responsibility of understanding what the data is and also understanding the features each data poses. Thats where the IT teams needs to acquire feature engineering skills. As data is never static, it is dynamic in nature, which means its keeps on changing even without a stop. The data has really out grown in large volume and variety. So to understand data, the right skill set is required.
IT Automation Skill:
As we have seen, the basic concept of AIOps is changing ITOps to AIOps, that is, completely automating the current manually employing IT task to completely be automated by the use of AI. That is to a new phase of cognitive automation. This requires a skilled set of IT team, who are capable enough of understanding the automation phase and how to deploy and completely transition into the automation phase. That is they should be capable of handling AI based models, understanding the data and getting to know the proper inference from the data, that is the KPI and log and so understanding the alerts or any events that's occurring.
Cognitive Cloud Management Skills:
Businesses are moving to the cloud at a rapid pace. According to a research study, 83% of enterprise workloads will be in the cloud by 2020. This shift of change will call in for the requirement of highly skilled people who are really capable of handling and managing the cloud platform. Deploying and managing a single cloud is challenging enough, but getting a handle on a multicloud environment with AI can be even more difficult. The key is to find a way to bring all the disparate cloud resources into a unified management system and need to analyze it using AI. Ideally, a cognitive cloud engineer would want to have a single pane of glass for centralized control of all public or private clouds used by the organization using AI based analytics and automation.
We can conclude that for AIOps to operate effectively, IT professionals need to understand the algorithms, access data and unify applications and services. This enabled automation of mundane tasks and IT professionals now can handle much bigger responsibilities to retain the machines and infrastructure of the business, running along with other value driven projects.
To learn more about Algomox AIOps please visit our AIOps Platform Page.