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AIOps Trends in 2021

Andrew Parsons

 Infrastructure Solution Specialist at Blue Turtle Technologies

 

In my last blog, we discussed the different levels of AIOps, mapping out the different maturity levels businesses find themselves in. If you aren’t quite able to align yourself to one of these, don’t worry, we can help you gauge where you are along the journey and assist.

There is no doubt that AIOps is a needle mover technology and will make waves well beyond 2021. Here are some insights into where we see AIOps as a discipline headed:

AIOps moving from just one data type to multiple data type algorithms.

So far, most statistical analysis is applied to a single data type, like metrics, logs or transactions. In the year ahead, we will see data scientists designing AI algorithms to analyse multiple data sets together. The beauty of this is that you will then be able to view all metric, log, and transactional data in one place.

This will make it easier to spot patterns, see how data correlates across processes, and aid IT in determining what can be filtered out and where there are warning signs to show potential problems in the system. Using this combined data, you can apply early warning systems, use automation to rationalise the alerts you receive, and save time.

Remote work driving more tech platforms to deploy AI

At the start of 2020, millions of workers were forced to work from home at short notice due to the global Coronavirus pandemic. Luckily, location doesn’t matter to AIOps. In fact it can even be used to help enhance productivity by predicting performance. Once an AIOps algorithm is running, it just needs to receive input data, extract the intelligence, and then produce the optimised value. This process can be done at any time and anywhere with no impact on customer experience or employee productivity.

For example, one of our partners LogicMonitor, has a financial customer who had used intelligent AI to create a dashboard and report in real-time on the usage of their VPN connections when staff began working from home. This meant they could load balance network usage across data centres and ensure consistent connections for employees with no loss of service for their customers.

Observability Platforms will have AIOps embedded.

In IT, observability is when external monitoring tools can see what’s happening inside a system. Observability platforms bring together data like metrics, dependencies and logs to give a bird’s eye view of the environment. They provide organisations with visibility across customer experience, employee productivity, and the digital infrastructure driving this to give an overall idea of how a business performs.

Adding AIOps and automation into the mix makes these insights actionable as users can use them to optimise systems, reduce the time required to troubleshoot, and fix problems before they impact customers or staff.

Integration of Security and IT Operations

Data and historical usage patterns can be used to spot when there are anomalies within the IT environment. For example, suppose a hacker is trying to access data. In that case, the system will notice unusual devices trying to access the network, data traffic changes, or potential access from a new location. This could then be dealt with by automating some of these access/security features and flagged for deeper/later investigation.

IT Operations can use all data, metrics, logs, and transactions gathered by AIOps and Security to monitor IT performance and detect cybersecurity threats in real-time.

ROI for AIOps platforms will speed up

We regularly see organisations keen to “jump on” the latest industry trends but have not considered the business problem they need to solve. This approach can lead to projects that fail or the unsuccessful implementation of irrelevant technologies as no success metrics were defined at the start.

Using a consultative approach, we partner with our customers and their IT departments to map out the desired goals they hope to achieve with an AIOps solution. We then create a framework to help decide on the steps that need to be taken and then implement it per the ROI a company hopes to achieve.

If any of the above has captured your attention and you want to get more from your data to drive an AIOps approach – let me know. I’d be keen to hear about your plans, and maybe we can help you along the way!

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