How to Use AIOps to Improve Your Application Performance

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Tuesday, June 25, 2019

AIOps could revolutionize how you approach application performance management strategies. How can this technology make you better-informed about their operations?

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Monitoring and managing the performance of your applications is a vital but often undervalued part of any IT professional's role. Being able to spot anomalies quickly, address any problems that might lead to downtime, and optimize systems to ensure they are performing to their full potential are all essential if firms are to be productive.

But this task is getting harder all the time. As businesses' IT environments grow and the number of applications and amount of data available expands exponentially, maintaining control of the resulting sprawl can pose many headaches to IT administrators.

However, there is an emerging technology that looks to tackle these issues, known as AIOps. This is set for a huge rise in popularity over the coming years as more businesses recognize its potential. Indeed, Gartner predicts that by 2022, four out of ten organizations will have implemented such a solution. But what is AIOps, and how can you use it to transform your application performance?

What is AIOps?

AIOps is a combination of artificial intelligence and IT operations, and refers to a series of tools that help businesses monitor and manage their systems much more effectively through automation and machine learning.

According to Gartner, who first coined the term, it aims to support activities including data center monitoring, service desks, and automation processes. It utilizes big data, machine learning and other automation technologies to bring together service management and performance management, and better support IT staff by pinpointing issues much more quickly and accurately than human staff could manage on their own.

"AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies." - Gartner

Applying AIOps to your application monitoring

But what does this mean in practice? For most businesses, the introduction of AIOps will enable them to monitor the performance of their applications in much greater detail, bringing together disparate sources of data from across the business and analyzing them quickly to cut through the noise and identify the most relevant issues that need to be brought to IT pros' attention.

The power of artificial intelligence and machine learning allows enterprises to effectively deal with the huge quantities of information generated by today's businesses, no matter where across the network such data originates or is processed. In a world of Internet of Things devices, edge computing and cloud, it will be impossible for manual monitoring processes to keep up.

Therefore, there are three key things you can do with AIOPs that would now be achievable using legacy application monitoring techniques:

1. Spotting hidden relationships

Today's IT operations are a complex web of interdependencies, and no one system works in isolation. But being able to understand these relationships is not easy when there is so much data flying around the business. With AIOps, you can more easily compare performance metrics across a wide range of systems to identify the impact your IT applications are having on overall performance and customer satisfaction.

This can be done by first working with business units to identify mission-critical activities for these applications, then gathering data generated during their day-to-day activities, such as orders, transactions, cancellations etc.

AIOps algorithms can then be used to spot patterns or clusters in the combined business and IT data, from which businesses can better understand the relationship and build up a chain of causality that identifies what applications are affecting particular business activities.

2. Forecasting future issues

Another key role of AIOps will be in boosting predictive analytics activities. By closely studying past and current behavior within apps, this technology can extrapolate what the most likely future scenarios will be, allowing businesses to proactively adjust their strategy to best take advantage.

This may, for example, help companies spot changing trends in how users interact with customer-facing apps, which will inform the future direction of software development. Or it could flag up anomalies that are early warning signs of forthcoming failures or business risks. This technology will enable businesses to conduct an in-depth analysis of the root cause of any problems and take steps to mitigate them before they become an issue that affects performance.

3. Making the most of customer and transaction data

AIOps machine learning capabilities can assist in pattern recognition, anomaly detection, classification and extrapolation, all of which are key elements of the big data analytics operations that businesses should be applying to their customer and transaction data. Therefore, turning AIOps' focus to these information sources can greatly help understand how user behavior impacts the wider IT system and vice-versa.

This may make it easier to track the effects any changes you make to your applications will have on business units. Will a certain change here lead to slower response times for customers, for example, and if so, what impact will it have on sales? With AIOps helping to bring together customer and transaction data with internal application monitoring information, businesses can have this information to hand immediately, helping them choose the right path for their applications' future.

How these activities can transform your business

These operations will all work to ensure businesses are much more proactive and responsive to changing environments. In today's data-driven world, it is vitally important that enterprises are able to delve deep into the information they have in order to get ahead of the competition and keep mission-critical applications up and running, as even short periods of downtime can be hugely costly.

AIOps ensures businesses can get control of the huge amount of data their systems generate. With applications vital to the success of any business today, being able to see easily where any issues lie - and where any problems may be about to arise - is essential in keeping performance levels high in a hugely competitive environment.


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