Amelia AIOps Brings Advanced Self-Healing to Autonomics

2 minute read

The more your company is able to automate problem resolution, the more your employees can focus on complex and creative tasks.

The more a business can employ machines to handle basic tasks without human intervention, the more time human workers will have to perform creative and complex work. This is especially critical when dealing with the overall health of a digital ecosystem. Mission-critical elements of an IT environment, such as server performance, website load time and uptime, and network traffic can be tracked and fixed by Artificial Intelligence (AI) and machine learning, creating advanced self-healing autonomic environments.

With IPsoft’s AIOps (formerly 1Desk), organizations empower a collection of cognitive virtual engineers that are designed to solve problems before those issues damage your environment. This isn’t an out-of-the-box feature, but rather a collaborative experience that allows human workers to fix an issue once and never think about it again. This is possible because AIOps' IPconnect lets engineers build workflows that are studied and recorded by virtual engineers. If the virtual engineer believes it can repeat this workflow on its own when a subsequent issue occurs, it will recommend turning the workflow into an automation triggered by a data threshold. If and when the problem occurs, the system will see that the threshold has been reached and will perform the automation necessary to solve the problem.

At the heart of AIOps' self-healing capabilities is IPpredictive and Event Monitoring. Predictive monitoring and analysis are basic IT ops requirements. AIOps takes them a step further by allowing virtual engineers to respond to data to run automations. AIOps is the only IT operations tool that can provide true end-to-end oversight. Thanks to Icinga 2 Monitoring, AIOps users can perform fast, multi-threaded performance-oriented checks, in most cases thousands of times per second. Through its RESTful API configuration, users don’t have to worry about last-minute updates causing delays.

IPadmin within AIOps gives teams total control of their monitoring thresholds. Instead of assigning a human engineer a ticket every time the network becomes congested, AIOps can automatically process traffic data and solve the problem before a human worker even knows the threshold was met. IPpredictive uses nine algorithm parameters to stay ahead of anomalies before they cause issues to your end-to-end IT environment. With Grubbs, Histogram Bins and other proven algorithm parameters, your organization can be alerted to looming anomalies and quickly apply pre-configured anomaly suppressors.

AIOps is designed to become more intelligent the more your teams collaborate with the platform’s virtual engineers. For example, you’ve built an automation for a server failure, but the automation doesn’t work because of one minor system change. AIOps will ask a human engineer for help, monitor the fix and add the new procedure to the back end of the original automation. This way, if AIOps has the same issue the next time it attempts to solve a server failure, it will have multiple options for resolution.

AIOps' IPcorrelate offers users a single dashboard for viewing and understanding historical and new anomalies. This unified vision enables simplified detection and resolution using probabilistic determination. The feature is designed to protect the entire end-to-end system against a flood of alerts from the same hosts, monitors, or array of devices. Instead of choosing a best-of-breed event management and correlation system, users receive a single module that is already integrated with the downstream automation system, thereby creating real end-to-end anomaly detection.

By combining excellent self-service features, as well as in-depth event monitoring and correlation, AIOps provides users with a true end-to-end platform for preventing issues from becoming dangerous, and learning how to stop them in the future.


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