IT faces constant pressure coming from ever-evolving customer demands that require organizations to do more with less. In fact, it is constant for almost every sector and it is only intensifying as time passes. In the past few years, we have noticed a trend in IT leaders striving to bring in reliability, scalability, and customer-centricity. Not only this, but they want to realize the same while lowering the total cost of ownership simultaneously. To help IT leaders realize this dream, AIOps (Artificial Intelligence for IT Operations) has been offering a lot of benefits and it is emerging as one of the best solutions to this issue so far. Since it is a new concept, it is quite obvious that your clients won’t be familiar with the term and will need answers to their questions related to the topic. The same is required to know how to better understand, approach, and implement AIOps to turbocharge your IT operations i.e., you need to understand the concept in detail. We are going to help you understand AIOPs using the simple framework along with some real-world examples that will help you relate to the topic. Ever since the term AIOps got coined in 2016, it has been getting a lot of attention. Here is why:
AIOps brings together big data and machine learning in order to automate IT operations, processes.
It includes event correlation, detecting errors, and causality determination.
AIOps is often mistaken as a single technology, but it is in fact a combination of disparate technologies.
It helps in data collection, data processing, data analysis, data visualization: all of these coupled with automation tools and solutions.
Another reason for its popularity is that business leaders around the world are now looking to IT for guidance so that they can leverage the value that can be derived from troves of data accessible to them. This is why AIOps is truly a unique opportunity for IT leaders that can lead the enterprise by example. AIOPs is the key for IT departments to further simplify the data decision-making process while helping them be more proactive.
Observability, Orchestration, and Automation – The Key to AI Application
The major question in front of IT leaders and other adopters of the technology is how to adopt AIOPs (AI and ML) in IT operations so that it can help drive glean actionable insights from data generated by various IT assets and IT systems. Here is how you can simply your AIOps implementation approach: by properly framing the application of AI across three key pillars – observability, orchestration, and automation.
Observability
In this highly competitive modern landscape, you need to be self-aware and must have the ability to self-announce, self-heal all the issues as soon as they arise. Currently, the process of monitoring IT assets and data is highly siloed, which is why observability is best achieved by bringing logging, tracing, and metrics from network and storage. The same must be accompanied by integrating servers either from across on-premises or building multi-cloud environments into applications. Having such full-stack monitoring capability on your side will provide you with deep IT, service performance, and application performance insights. These insights can later be extended to bring awareness and context for improving business-level performance.
Orchestration
In IT operations, service management is the core of all human-centric activities. AI and ML can help you bring human-in-the-loop automation that will help you streamline operations and optimize incident, problem, and service request management processes. Extending the application of AI to chatbots and digital voice assistants, you can have automated bots that can engage with users and will help you drive self-service to various types of requests. These requests can be password resets or data and report requests.
Automation
In the IT industry, we already have been automating various processes through scripts, and it is nothing new to IT departments and programmers. But as time passes by, the automation industry has been witnessing drastic advancements in automation using APIs, data management, and GUI-based robotics. All of this allows the users to easily push the envelope by delegating deterministic procedures to AI-powered chatbots while empowering human workers to take up more problem-solving challenges. Not only this but AI further pushes its limits to help users achieve self-heal-based remedial actions.
Endnote
By now, it must be quite evident how AIOps can benefit IT. With AIOps, we can derive numerous applications from the untapped potential of data sitting in IT systems. All we need is the right AIOps strategy that can help organizations have a sure-fire solution to all their pain points – be it excessive ticket issuances or manual fulfilment of service requests. AIOps is transforming the IT industry and the time is now to join the trend and take your business to new heights.