The Present IT operational methodology is simply not tenable in the present hyper-dynamic cloud-based environment. 

Now that we have set the tone of the change we are dealing with, let’s understand why. 

IT has evolved from a cost center into an inextricably embedded, valued business asset that supports a company’s core operations and value delivery. 

In the digital-led world, an IT department is unable to keep pace with rapid business scaling, snowballing complexity, and disruptive innovation because —IT personnel cannot grow at the same rate as the complexity and disruption. In a world where most operations will be via the cloud, it is important to switch to a better alternative – AIOps.

AIOps, Artificial Intelligence for IT Operations, is platforms and software systems that combine big data and AI or machine learning functionality to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation.”

The Present Situation and Challenges 

Switching to AIops has become essential because of the massive move towards the cloud. Here are a few stats that clear the picture:

• Public cloud computing market will top massive $266 billion by 2020, Gartner predicts
• 67% of enterprise infrastructure will be cloud-based by 2020, Sys Group
• 85% of businesses worldwide are already making use of cloud technology to store information, Sys Group
• 37% of the global IT budget for 2019 was on Cloud Computing, Tech Radar

Cloud adoption stats for 2020 report that software as a service (SaaS) takes up 48% of the cloud computing budget, while infrastructure as a service (IaaS) accounts for 30%. The remaining 22% is claimed by the platform as a service (PaaS).

• 94% of the internet workload will be processed in the cloud by 2021, Network World

The adoption of cloud has many advantages, but as the business grows and develops, it becomes increasingly challenging to manage it while troubleshooting 24*7. It is not possible to do this manually without significant disruption and large costs associated with the workforce. 

AIOps: Present Status

The use of AIOps is fairly limited but is picking pace. In 2017, it was just 5%, but Gartner expected it to rise to 40% by 2021 (“Market Guide for AIOps Platforms,” Gartner, August 2017). The pandemic may have given it a nudge for better growth. The AIOps Market is expected to grow at a CAGR of 26.2% during the forecast period 2021 to 2026. Mordor Intelligence.

Behind the Rise of AIOps

There are a plethora of reasons why interest in AIOps is rising. 

AIOps can help transform IT operations into a service-oriented model with diverse benefits such as profound and real-time insights into: 

Artificial intelligence (AI) can be used to apply algorithms to IT operations and enhance current data analytics capabilities to improve outcomes. ML can autonomously analyze and process the massive quantity of data being generated by today’s IT operations — learning patterns for faster correlation and root-cause analysis.

The AIOps deliver value in terms of these desirable Outcomes:

• Prevention of future issues and downtime
• Faster triage to reach the root cause
• Use cognitive pattern technology to reduce event noise
• Optimized processes for hassle-free scaling and managing complexity
• Unprecedented agility to keep up with technological change 
• Early intimation to business associates with better risk assessment
• Superior Operational Efficiency
• Improve productivity with real-time visibility of business services

9 Unique AIOps Advantage for Businesses 

The adoption to multi-cloud IT environments demands better management, and AIOps just deliver that as it helps:

• Automate processes
• Drive faster resolution time
• Provide deep service visibility
• Ease of operations management at scale
• Simplified and unified IT operations management
• Deployment of proactive indicators
• Execute remedial action autonomously
• Cognitive pattern capabilities
• Access to accurate data for business collaboration 

Three Pillars of AIOps Value Creation

The core value created with AIOps can be subsumed into three areas: 

Health Check, Monitoring, and Course Correction:

• Advanced and predictive problem identification and remediation     
• Use of Historical data for early problem detection 
• Reducing event noise with ML and provide a real-time health status

Holistic Service Views: 

• Manage, collect and correlate incident, and event data
• Service maps: Precise and updated
• Cognitive pattern tracing 

Analysis for business services

• Data Analysis at scale
• Proactive recommendations for potential problems
• Rapid root cause analysis
• Prioritize resolution by business service

KPIs for AIOps

Measurement of outcomes is as important as the creation of the solution. Here are simple KPIs (Key performance indicators) that can be applied for AIOps for best outcomes. :

• Service and support ticket reduction 
• Faster Mean Time to Repair (MTTR)
• Reduction of P1 (major) incidents 
• Service availability improvement 

The Future is AIOps

Everyone is switching to the cloud, the data generated is massive, and with continuous updates, it is simply untenable to be effective with old-style management of IT operations. Also, software development has become so rapid that it is increasingly becoming impossible to monitor and remediate the service issues in the vast cloud environment. Not only would cost, but the damage of downtime and lengthy corrective measures necessitate that firms switch to AIOps for hassle-free management of their IT operations.