7 Things You Need to Know to Successfully Deploy AIOps

AIOps requires a considered and measured implementation approach if it is to deliver immediate results.

John Allen

December 29, 2020

5 Min Read
7 Things You Need to Know to Successfully Deploy AIOps
(Source: Unsplash)

From ride-hailing algorithms to customer service using an AI bot, artificial intelligence is being utilized to improve a wide variety of services in the modern era.

AIOps is an acronym for artificial intelligence for IT operators. It refers to a multi-faceted technology platform that can automate and enhance IT operations using analytics and machine learning.

AIOPs works by leveraging and collecting a vast quantity of diverse data from a range of IT operations tools. It does this to detect and react to issues in real-time, while simultaneously providing traditional historical analytics.

Used properly, AIOps has a variety of benefits which include the removal of noise and distractions. This means a speeding up of problem detection and faster resolution of service issues. 

AIOps can also eliminate silos and provide a more overarching vision of the entire IT environment, including infrastructure, network applications, and storage.

1) Staff: It is important when implementing AIOps to make sure that you have the right staff on board who understand the technology and how it applies to your business.  You may be lucky enough to have people employed who are already familiar with the concept.

However, it would be useful to employ additional personnel who are specialists in data science and automation, even if they are in a remote capacity.  Finding suitable staff for these specific roles can be made easier by using the best employee management software systems on the market.

2) Spread the word: One of the best business management tips, with regards to AIOps, is to ensure everyone affected is aware of the changes you intend to make. Not only will it be essential to inform your user community, but everyone that the system overhaul is going to affect also needs to know how it will change their role (if at all).

You can communicate the changes by presenting a webinar or hosting workshops as to how to understand the system’s implementation and its benefits, for example.

3) Understand AIOps’ utility: Ensure that you understand what the system’s capabilities are and what results you are looking for by implementing it. Common results that businesses look for are anomaly detection, event correlation, or alert and notification suppression.

Emphasize seeking results that can be quickly registered by staff to instill confidence in your team about its effectiveness. AIOps should be implemented to make your business more successful, and understanding how they can help is key.

4) Test and monitor: Configuring and launching the system on smaller inconsequential workloads will give you an idea as to its viability without the risk of damage being caused. If configuration to inform machine learning is taking a protracted period to work, it could be worth re-evaluating its validity to your business.

At this stage, IT operators should be able to see how the system is interacting with the collected data and produce guidance and analysis on how the system can be improved. This is an important step to achieve before expanding to larger cloud size data sets.

5) Guide the system: IT operatives will be able to define certain predictable and routine functions that the AIOps system should be able to deal with quickly. Setting the system these tasks will not only show how it can be effective in tasks such as patch updates but demonstrate how the system can save time for human operatives.

6) Install: Assuming the results from the various test scenarios have been favorable, you should deploy your system to the wider network. If you are still hesitant as to whether your AIOps system is worthwhile, you can run the system in testing mode for an initial period.

This should provide assurances that outputs are accurate and that your user base is content with the results. In addition, think about whether it’s a good idea to combine your AIOps with data quality software.  These pieces of software can help with data analytics and data mining.

7) Assess and improve

Once a few weeks have passed, you and your team must review the system’s effectiveness in the context of achieving the goals you set for the system’s introduction. This includes measurable metrics such as registering a reduction of system errors. It also means conducting surveys and recording customer feedback.

Broadly speaking, AIOps should mean you can extract greater value from your data and improve service.

Wrapping up

AIOps is an incredible evolving tool that can help your business save time and money as well as improve performance.  However, it should not be expected to deliver immediate results without the implementation of a considered and measured approach.

About the Author(s)

John Allen

John Allen is the Director of Global SEO at RingCentral, a global UCaaS, VoIP andcontact center softwareprovider. He has over 14 years of experience and an extensive background in building and optimizing digital marketing programs. He has written for websites such asHubspotandBambooHR.

Stay informed! Sign up to get expert advice and insight delivered direct to your inbox

You May Also Like

More Insights