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Artificial Intelligence and Machine Learning to Run Faster and Smarter IT Operations

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What is AIOps?

AIOps stands for Artificial Intelligence in IT Operations and is the use of advanced algorithms and AI techniques for analyzing big data from various IT and business operations tools, to speed service delivery, increase IT efficiency and deliver a superior user experience. AIOps enables a move away from siloed operations management and provides intelligent insights that drive automation and collaboration for continuous improvement.

Since AIOps leverages big data, data analytics and machine learning to provide insight and enable a higher level of automation, no longer does IT Ops need to depend extensively on human operators for the management tasks that modern infrastructure and software require. AIOps solutions ingest data from a variety of resources and then store and provide access to that data enabling advanced analytics at the point of ingestion and the point following the access of stored data.

For this reason, AIOps holds tremendous value. Going forward, AIOps will play a key role in enabling new efficiencies for IT Ops teams. It will also make practical the adoption of complex next-generation technologies that cannot be managed successfully using traditional solutions.

Key Drivers for AIOps

In today’s economy where every business is in the software business, downtime is costly and slow is the new down. Proactively managing and improving experience of modern applications, cloud or traditional infrastructures and networks is a necessity but it’s not easy.

Digital businesses and technologies are increasing the volume, velocity and variety of data. Manually correlating and analyzing data or alerts is becoming increasingly difficult for IT operations teams with existing siloed tools spread across mobile, the cloud and the mainframe.

It is now imperative that you have comprehensive visibility coupled with AI and machine learning. That means normalizing, correlating and analyzing massive volumes of IT operational data across your entire digital delivery chain to speed service delivery, increase IT efficiency and deliver a superior user experience.

Successful digital transformation requires AIOps. It enables IT teams to automatically analyze large volumes of digital data—making it easier to solve hard problems. It’s operational intelligence across user, app, API, infra and network services. It’s cross-tier correlated insights, machine learning and predictive analytics.


Driving Faster Root-Cause Analysis

AIOps can help IT teams rapidly understand the causality of a problem affecting one or more services and contextualize the relevant information so you can execute the appropriate remediation.

Easily Predicts Issues Earlier With Smarter Alarms

AIOps can generate alerts based on values of abnormal scenarios (anomaly detection). Behind the scenes, the appropriate algorithms learn from data across tools and identify events that do not conform to an expected pattern. This also reduces your need to manage manual alarm thresholds.

Algorithmic Noise Reduction and Correlation

AIOps eliminates redundant alerts and automatically correlate related alerts to improve detection of critical issues and helps you with faster resolution.

Predictive Identification of Capacity Bottlenecks

AIOps can help you to avoid service disruptions and reduce waste by discovering under-utilized capacity across hybrid infrastructures.

Intelligent Automation

AIOps leverages cross-domain, intelligent insights to trigger processes in your automation and collaboration tools to drive faster, automated issue remediation.

Service Driven Proactive Remediation

AIOps helps you solve complex IT problems like performance, capacity, configuration issues by proactively detecting and remediating them before they impact users. 


  • US Bank

  • KPN

  • William Hill

  • Coty

  • LinkedIn

  • Barclays

US Bank

AIOps helps US Bank increase automation across the tool chain 

Learn how AIOps will help US Bank increase automation across the tool chain by analyzing large, monitoring-driven data sets. US Bank shares how they have so much data to get through that the root cause correlation is a large part of the bank’s triage process today. With the help of automation, US Bank envisions that the resolution side will be more effective, delivering better up time and improving customer experience.

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How AIOps is helping breakdown DevOps silos at KPN

Learn how AI and machine learning are impacting the future of IT Ops at KPN. This leading Dutch telecommunications company shares how AIOps is helping breakdown DevOps silos and providing insight into the business process as a whole.

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William Hill

Behind the Bet: How William Hill is Using AIOps to Analyze Data

Learn how AI and machine learning are helping William Hill, one of the world’s leading betting and gaming companies, analyze large volumes of digital data—making it easier to solve hard problems. With a new services model, it's imperative for companies like William Hill to have comprehensive visibility of IT operational data across the entire digital delivery chain. But there’s also the human factor. There is a real skills gap. William Hill shares why they need to rely on automation and machines even down to driving self-writing code, since there will not be enough developers around.

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Coty Employs AIOps to Gain Service-Centric Visibility

Coty makes many of the world’s most popular cosmetics, beauty products, and fragrances. The company has established itself at the top of a number of segments, and has grown to become one of the largest beauty companies, generating more than $9 billion a year in revenue.

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LinkedIn Automates All of the Easy Things, and Makes all of the Hard Things Easy 

Hear LinkedIn’s senior SRE, Todd Palino, share how the company continually improves the state of its infrastructure, so that the developers who are rolling out applications have a framework that they can do it within, and they can do it safely. LinkedIn currently generates over 50 terabytes a day of unique metrics on applications. No human is going to look at 50 terabytes a day of data and get anything useful out of it, so LinkedIn relies on systems give them some useful signal out of all that noise.

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How AIOps will help Barclays Bank enhance user experience 

Barclays Bank shares how AI and machine learning will play a key part in automation by requiring IT Ops to look at your full infrastructure end-to-end, and the various monitoring tools you're using across that estate in order to pull together information to deliver the best user experience.

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Learn more about how banks can profit from AIOps by visiting the CA AIOps for Financial Services page.


CA Digital Experience Insights

Combines cross-correlated data across app, infra and network services with machine learning and advanced analytics to deliver a new level of visibility and actionable operational intelligence via an AIOps-driven platform.

CA Operational Intelligence

Comprehensive operational intelligence spans cloud to mainframe for proactive issue resolution and improved efficiency.

CA Automic Service Orchestration

Deliver the services your users, applications and infrastructure need, when they need it.



AIOps Essentials: Service-Driven Autonomous Remediation


Empowering User Experience With AIOps

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Video running time: [01:23]

    VIDEO, 451 Research AIOps and Monitoring Platform Approach featuring Nancy Gohring, senior analyst.

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    Insights to deliver flawless digital experiences through modern, full-stack, AI-driven IT operations monitoring and analytics from CA. Check out our blogs on AIOps, APM, Infrastructure Management, Network Operations and more.


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