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Home » Features » OpsRamp Extends AI Reach to Incident Management

OpsRamp Extends AI Reach to Incident Management

Avatar photoBy: Mike Vizard on September 21, 2021 Leave a Comment

OpsRamp today extended its IT operations platform infused with machine learning algorithms, also known as AIOps, into the realm of incident management.

The Summer 2021 release of the company’s namesake platform adds alert predictions for preventing outages and incidents, alert enrichment policies for faster incident troubleshooting and enhancements for automatically ingesting metrics data collected from the Alibaba Cloud environment and open source Prometheus monitoring software as well as Hitachi, Poly, VMware and Dell EMC platforms.

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IT operations teams can now also visualize metric values that can increase or decrease within a fixed range using Gauge charts. IT teams can also now add alert context details to provide more relevant information. There’s also now a mobile app for both Apple iOS and Google Android devices through which IT teams can now respond to alerts and incidents.

Finally, OpsRamp is also making available a beta release of dynamic Workflows, which enable IT team to maintain a single decision table to address specific operational scenarios.

Sheen Khoury, chief revenue officer at OpsRamp, said the goal is to leverage artificial intelligence (AI) to increase application availability by enabling IT teams to better predict when there are indicators of an incident caused by, for example, higher volumes of seasonal traffic that could lead to an outage.

At the same time, IT operations teams can improve overall time-to-value by leveraging the automatic monitoring tools that are embedded in the platform, he added.

OpsRamp is betting that rather than waiting for incumbent providers of IT operations platforms to add AI capabilities, many IT teams will opt to deploy a new IT management framework altogether. Many of the manual tasks IT operations teams regularly perform today can then be automated faster, noted Khoury.

Naturally, it takes time for machine learning algorithms to be trained, so the benefits of AIOps are not instantaneous. However, those algorithms will continuously learn the unique attributes of an IT environment in a way that makes it easier for IT teams to manage an IT environment more proactively. The algorithms provide the added benefit of making it easier for new members to join an IT operations team without having to spend months learning all the nuances that are unique to that environment.

Each IT team will need to decide for itself the degree to which they want to rely on an AIOps platform to manage their IT environment. Initially, most IT teams will need to evaluate the recommendations made by an AI platform. However, as they gain confidence in the recommendations, they will trust the platform to automate more processes in response to events occurring in the IT environment in real-time.

Regardless of how much faith IT teams put in AI, it has become apparent that enterprise IT environments are only going to become more complex. Many IT teams will not be able to manage some environments without the aid of an AI platform. Many IT professionals may not want to work for organizations that don’t provide some way to augment their skills using AI—the stress level would simply be too high.

One way or another, DevOps teams that are highly committed to ruthlessly applying automation will be at the forefront of AI adoption in the enterprise.

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Filed Under: Application Performance Management/Monitoring, Continuous Delivery, DevOps Practice, Enterprise DevOps, Features, IT Administration, News, Observability, Monitoring and Analytics Tagged With: ai, automation, it automation, machine learning, OpsRamp

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