AI Ops is the new buzzing term in the world of IT and business. If you are a part of an IT organization, you must be hearing a lot about ai for IT ops and enterprise ai and how AI and Machine Learning can benefit your systems, processes, and productivity.
This article focuses on AI Ops and and how Machine Learning makes all the difference to IT Operations in an enterprise. But before we dive deep into that, let’s understand what is AI Ops.
AI Ops definition
IT organizations have become an integral part of businesses today. Enterprises generate massive data across business units and regions, which rest in their hardware, operating systems, servers, applications, and other monitoring and troubleshooting systems.
Earlier, these data would be in different systems across geographies not helping in deriving insights, but today these datasets can be gathered, formatted and learned from, to derive insights and improve and automate the IT infrastructure management.
The platform or tool that helps us achieve this is broadly termed as AI Ops. Gartner defines AI Ops as the application of machine learning (ML) and data science to IT operations problems.
AI Ops benefits
With the increasing dependence on IT for data generation, transfer, and storage, the complexity of cloud system has also increased. Due to the complexity of disparate apps and systems, enterprises are under huge threat as they are unable to track the problems that occur during an IT incident. And with each undiscovered incident, enterprises are losing out on cost, credibility and business. To mitigate such incidents, enterprises have increased their investment in cloud systems, and integrated tools among others, which have further complicated the process and increased the burden on IT organizations to manage the increasing complexity.
AI Ops solutions help mitigate this burden of IT teams by leveraging machine learning and automation. In today’s scenario, every IT organization is dependent on a plethora of tools, which need constant care and development in order to perform the tasks. These tools need regular updates, alerts, and rewriting of scripts, which take away the team’s time to do actual work. This is where AI Ops helps IT teams, by automating these tasks and leveraging ML to set alerts and resolve issues. Thanks to their self-learning capabilities, AI Ops platforms can learn from the patterns within the distributed cloud systems and provide insights to improve the cloud environments, apps, and services.
Another way how AI OPs helps IT organization is by filtering through so many alerts and only highlighting the important ones to avoid delays in resolving the critical ones. This is where IT teams leverage AI Ops strategies to identify patterns and suppress all noises to focus only on critical information.
This is done in three simple steps –
| Data Segregation |
| Data Analytics |
| Predictive Analytics |
The use of AI for document analysis makes it easier to gather, segregate and analyze data. AI Ops tools first segregate data coming from different sources and transform them into usable and format. This data is then understood with the help of analytics and insights are drawn. These insights are then gathered from data analytics by leveraging machine learning to enable automated decision-making, leading to quicker problem identification and resolution. Machine Learning also empowers IT teams with predictive insights, preventing such incidents from occurring.
Best AI Ops tools are both cost-effective and timesaving. One of the most significant AI OPs benefits is that the IT teams can spend their time and energy in building scalable systems rather than resolving alerts and doing mundane tasks. AI Ops platforms also predict probable incidents and resolve them without human intervention.
AI Ops Use cases
AI OPs platforms are helping enterprises across the world make informed decisions by bringing together data from siloed systems, deriving insights out of them and empowering IT teams to perform the following:
- Implementing AI OPs helps IT teams automate and enhance their regular IT operations so that they can focus on more strategic tasks
- AI OPs tools also identify inconsistencies more quickly and accurately and suggest solutions which are both time-saving and intelligent.
Choosing the right AI OPs platform
There are many AI OPs vendors today providing solutions that vary in terms of functionality, flexibility, cost and data management. However, there are a few significant features you must consider which choosing the right AI OPs platform for your organization.
- The best AI OPs tools carry out data collection efficiently at scale.
- They collect different types of data from various sources, enabling deeper analysis.
- They are also quick to identify data relationships and reliabilities. This helps Data managers to allocate their resources in the most optimum way and make an informed decision, which making technology purchases.
- The tool must also be able to provide analytical insights that can help identify and understand the root cause of anomalies which can help IT teams make an informed decision with the help of predictive insights.
- The tool should be quick to generate and deploy automation.
- Any AI OPs platform should provide the key members of the IT teams with dashboards and reports that can help derive insights from the data presented allowing for informed and intelligent decision making.
At the end of the day, it is data that rules the game. Like any other platform, AI for IT Ops is also only as good as the data it gets and the algorithms it learns. The amount of time and effort taken to implement, maintain and manage the platform plays a significant role in its performance and realization of ROI.
Before you choose the AI Ops vendor, it is important to identify the problems you want to solve with your AI OPs platform. This will help you pick up a platform, which suits your requirements the best and will deliver the desired results.
Conclusion
The rise of ML has helped improvise operations across business verticals and AI Ops is one emerging technology that beautifully amalgamates automation and ML capability to strengthen the IT organization to realize greater business value. The icing on the cake is that unlike other ML tools, AI Ops provides quicker value and excellent ROI with lesser effort. Therefore, AI Ops is an investment worth making.
