What is AIOps?
Artificial Intelligence for IT Operations (AIOps) AIOps tools involve using artificial intelligence and machine learning techniques, as well as big data, data integration, and automation techniques, to make IT operations smarter and more predictive. AIOPS complements manual operations with machine-driven decisions.
AIOps is a collection of best practices, tools, and techniques for deploying and maintaining optimal output from AI models in production. The term AIOps bears a resemblance to another acronym – DevOps – that is also being used in the technology world. Like DevOps, AIOps aims to break down silos and merge different processes. However, unlike DevOps, AIOps is more concerned with the automation of IT services.
Let’s look into this roadmap of AIOps in 5 different perspective:
Reactive Stage:
Bandage phase or more like the initial phase of AIOps in any organization. Any organization working with traditional monitoring tools usually operates in a reactive phase. IT teams receive thousands of programs from gossip monitoring tools every day and struggle to figure out where to focus. Most IT teams will find it difficult to progress because they have to locate and fill in a lot of data to get the proper results. This slow running will eventually affect the entire system. In this age of digital transformation, the ark phase will not work for any system.
Proactive stage:
The proactive stage, as the name suggests, is proactive, and acts quickly before something happens. AIOPS helps in achieving this proactive approach. In this competitive environment, reacting to real events is no longer sufficient. Now the time has come when we can already predict the issue and bottlenecks. At this stage, AIOps tools and processes can quickly determine the root cause and notify the IT operations team. This will help the IT operations team to take quick action before the problem is noticed by the end users. Plus, it minimizes the impact on business operations.
Predictive stage:
This is the third level, the predictive stage. This stage comes with more analytics to foresee future events like service outages or infrastructure capacity exhaustion with a high degree of probability. An AIOps platform provides predictive recommendations to the IT operations team to minimize or eliminate business impacts. Also provides the ability to monitor the health or status of the organization so that you can predict and respond to outages. The ability to prevent failures before they happen is a bigger green flag wave for any IT system.
Perspective stage:
IT organizations at this prescriptive level can get prescriptive recommendations from the AIOps systems and can make better and faster-informed decisions. This will enable them to be a better agile organization to deal with the fast-moving business requirements with the highest level of efficiency.
Automotive Stage:
The automated IT organization can leverage an advanced AIOps platform that can provide resource optimization and auto-remediation recommendations to the automation platform based on AI-based analytics and keep the system up and running without much human intervention. AIOps hits a big wave in the automotive stage. The automotive stage helps businesses to make efficient data processing and better decision-making. Much more, it helps in the speed tracking of digital transformation.
