How AI Software Enables It Operations Teams To Find And Fix Problems Before They Happen

By George Thangadurai, CEO (www.healsoftware.ai)

Today’s artificial intelligence for IT operations (AIOPs) tools often claim to use machine learning (ML) models and artificial intelligence (AI) algorithms to detect and flag incidents, perform correlations between seemingly unrelated events across monitoring silos and provide variants of a potential root cause. However, these tools typically rely on a “break and fix” model with any remedial actions always after the fact; and none of these tools are effective at eliminating downtime or solving problems before they occur.

The “break and fix” model has always been the status quo, but it no longer has to be the reality. IT’s recent shift toward focusing on the diagnosis of the reasons behind failing application health has put more emphasis on being able to detect and fix problems quickly. Troubleshooting is now aimed at getting to the root cause of an issue, and prevention is the natural next step. Preventive healing is a new category of monitoring and AIOps software that helps digital enterprises mitigate problems before they occur.

How “predict and prevent” is changing the game

Preventive healing uses AI and ML to preempt any possible outage by acting before it occurs. By detecting a situation where an outage or issue is imminent, IT teams are able to “predict and prevent” versus wait for something to break and then fixing it. Shifting to the “predict and prevent” model is not only beneficial for the internal team, but also the customer and end-user experience.

• Internal teams gain valuable insights and improve interventions:

The benefits for the internal team are two-fold. First, predictive technology can provide valuable insights to business leaders. The technology can help determine where capacity bottlenecks are by analyzing growth data. In addition, shifting to “predict and prevent” can help businesses make smarter decisions and save valuable resources. Oftentimes, to mitigate risk enterprises invest time and money into resources that might not be needed just to ensure they are well covered. With a model focused on root cause identification and prevention this over-provisioning of resources is no longer necessary.

The second benefit to the internal team includes simplifying internal intervention. For IT professionals, alarm fatigue is real. When the IT team receives dozens or even hundreds of notifications on a regular basis, it can be hard to prioritize where to begin to focus due to the quantity of pressing items on the IT teams’ plate. Preempting an outage or issue is complex and requires detailed algorithms and 24/7 monitoring, which is well-beyond the scope of even the best IT professional’s capacity. Leveraging AI technology helps IT teams by automatically detecting an anomaly and identifying the source so the problem can be fixed before it occurs. If the tool cannot fix the problem on its own, it will find and flag the root cause for the IT team, minimizing time and energy wasted on discovering issues.

• Limits disruptions for customers and end-users: Under a traditional “break and fix” model, customers and end-users are typically the first to notice when an error or outage occurs. These reactive models mean that by the time a problem is detected, the issue has already occurred which can be very frustrating to end-users and erode customer retention. Preventive technology can help identify and warn against unnatural patterns of behavior before they result in an issue. Therefore, shifting to a “predict and prevent” model can help reduce disruptions to end-users, helping to ensure a better customer experience.

If your IT team is ready to make the switch to preventive healing software, it is important to understand what capabilities are available. Here are four key capabilities you will want to be sure your software includes: 

1. Predictive and Preventive

Look for a preventive healing software that can intelligently detect anomalies and leverage healing actions and remedial workflows to bring system parameters back to normal before an issue occurs.

2. Collective Knowledge

Integration is critical, so look for a solution that is comprised of a suite of APIs and connectors so it can integrate with your APM vendors and content formats. Additionally, find a solution that comes equipped with its own agents to collect workload, behavior, configuration and log data. Lastly, some solutions offer more than just preventive healing and can also provide a full-stack infrastructure and business activity monitoring solution.

3. Situational Awareness

It is important that the responses are coherent and complete. Seek out a solution that can produce precise predictions by using contextual data at the time of the anomaly – including forensic data capturing the state of the processes/queries running on the system at the time

4. Remedial and Autonomous

Some preventive healing software uses intelligent machine learning to ensure it can deliver the best responses to the problem. The remedial actions can be provided in two scenarios: by scaling up to handle the workload and triggering autonomous correction of underlying issues that cause anomalies. IT teams and enterprises who leverage these patented techniques can feel confident they are receiving the best response.

The multi-cloud environment is making it even more important for IT operations to assess current gaps and seek out solutions. Replacing the “break and fix” model with a “predict and prevent” approach is the only way to provide confidence that a company’s IT infrastructure is up and running all the time and applications are available 24×7.

ABOUT THE AUTHOR:

George Thangadurai is the CEO at Heal Software Inc., the innovator of the game-changing preventive healing software for enterprises known as HEAL, which fixes problems before they happen.