Unleashing Innovation and Business Value with AIOps

What Is AIOps?

AIOps stands for Artificial Intelligence (AI) for IT Operations.

It is advanced analytics including machine learning (ML) and other forms of AI to monitor and manage the performance and reliability of applications and hardware systems, detect anomalous problems, adapt to changes in requirements, handle failures, and to adjust proactively or rapidly with minimal disruption of services.

AIOps tools collect data from multiple IT sources including metrics, logs, traces, events, and telemetry, process the data, use machine learning to find useful information, and deliver the findings to IT operations. The output includes IT anomalies, patterns, correlations, and predictions.

The objective is to enable better decision making, issue avoidance, and outage prevention by:

Rapidly identifying the cause of degradation or failure, and quickly restoring the service

Detecting and predicting failures before they impact users. Driving more actionable insights; adopting a proactive versus reactive approach

Optimizing teams by aligning people, process, and technology to deliver a better customer experience

Ensuring the consistent delivery of high performing network and telecom services


How Big Is AIOps? How Fast Is It Growing?


dot-pattern
revenue and growth

AIOps is a large market with

$4.2 billion

in software and SaaS revenue

in 2021

AIOps is growing at
an annual rate of 9.3%
and is forecast to reach

$6.6 billion in 2026

multi-cloud-analytics-infrastructure-icon

Growth is
highest in
SaaS-based AIOps

at 17.5%


Source: IDC WW IT Operations Analytics Software Forecast, 2022-2026, March 2022


AIOps Drivers

As organizations modernize, transform digitally, and adopt automated operations, they need:

dot-pattern

Speed

Organizations must increase their speed to meet rising consumer and business demands for fast restoration of services when problems are discovered. Customers demand great experience and highly reliable services.


Scale

The explosion in scale, the amount of data and resources to be managed (metrics, logs, traces, events, telemetry, others) go beyond reasonable manual efforts. Automation is required to collect, analyze, and react to the vast data volume and varieties involved, as well as the many simultaneous workloads required.


Flexibility

Business services are becoming more distributed and interconnected across networks. Increasingly, this is a multi-infrastructure world (private cloud, hybrid, public cloud, on prem, multicloud, SaaS, etc. ). Modern software and services are often also containerized; cloud-native architectures and complex networks deliver services to consumers and businesses. AIOps platforms have to be able to flex to function in all the places optimization is needed.


IT teams have to manage vast increases in data, applications, and infrastructure as a result of the advent of 5G in telecom and increasing demand for smart sensors, networks, etc.

Business innovators depend on their organization’s ability to scale, adapt, transform, and deliver IT services on demand across physical, virtual, cloud, and multicloud infrastructures.

aiops machine learning icon

AIOps is vital to effectively operate these complex environments. Automation corrects many minor issues, and increases productivity of IT staff by providing clues, root causes, and analyzed patterns to reduce mean time to detect issues (MTTD) and mean time to repair them (MTTR).



What Benefits Are Expected from AIOps?

Improved customer
satisfaction and
retention

Increased IT
personnel
productivity

IT cost
savings and
containment

Decreased downtime and
increased system
reliability

Faster mean time
to repair (MTTR) and problem
identification

Improved
service
reliability

Increase
in team
collaboration

Reduced
churn
rates


AIOps in Action: Use Cases

Datacenter
operations optimization

Early fault and
failure detection

Root cause
analysis

Incident
prediction

Alert noise
reduction

Smart hardware
data center intelligence

Telecom network
analysis

Energy usage
optimization

Predictive
maintenance

Capacity prediction
and planning


Automated IT Optimization Is Essential

Modern Networks Require Finding and Solving Issues at Machine Speed

With cell usage data increasing and IoT and edge data flooding everything, especially 5G networks, an analytics capability that can linearly scale is essential. Total IoT spending in 2021 totaled just over $690 billion.
Source: IDC WW Internet of Things Forecast, August 2022
Finding root causes of incidents and predicting incidents before they occur is needle in a haystack work that requires every single data point, not aggregates. You can’t find the needle if it’s been mushed into a clump of hay.

84.4 ZB of data was generated in 2021, with 55.8 ZB of that from IoT.
Source: Worldwide IDC Global DataSphere IoT Device Installed Base and Data Generated Forecast, 2022-2026
Time series analytics, geospatial analytics, machine learning, event pattern matching, even good old-fashioned business intelligence – every kind of analytics available is frequently what is needed to find, predict, prevent, or solve issues.
Engineers who can troubleshoot network problems are smart, skilled, and expensive. Make every minute of their time count by automating and pointing them at relevant information. Don’t make them search through giant piles of logs.

Vertica is the analytical database with the best value for the highest performance on any data analytics, at any scale, anywhere.

Best Value

Compressed storage, efficient processing, fungible license

Any Analytics

BI, time series, IoT, geospatial, machine learning

Any Scale

Terabytes to petabytes

Anywhere

On-prem, clouds, hybrid, containerized


View PDF of infographic created by IDC Insights.


“AIOps has become a must-have technology to deliver great customer experiences and differentiation for network and telecommunications organizations.”

Explore how AIOps technology offers the speed and scale to stay ahead of service reliability problems that impact the customer experience, and ultimately revenues.

Learn more about how Vertica can help solve AIOps challenges.