AIOps, or artificial intelligence for IT operations, is a term that refers to the use of machine learning, data analytics, and automation to improve the performance, reliability, and security of IT systems. Here at IPTel we are always looking at ways to engineer improvements to our service and leveraging AIOps is one such way.
This blog touches on our current implementations of AIOps and what is coming up in the future with the sole aim of adding value to our customers and improving our ability to support our managed networks.
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Edwin AI leverages LogicMonitor's rich data and contextual information, and applies natural language processing, deep learning, and reinforcement learning, to deliver human-like intelligence and guidance
The exciting thing with Edwin AI is also the ability to ingest data from external sources and not just your network data in LogicMonitor. External sources could include Splunk, Azure, CrowdStrike and many more.
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Edwin AI analyses Logicmonitor's alerts and metrics, and filters out the irrelevant, duplicate, or false alerts.
Edwin AI also ranks the alerts based on their severity, impact, and urgency, and notifies the right people at the right time. As a support team we often have the scenario with alert storms accross the network and it can be tricky and time-consuming to correlate the alerts and establish the root cause.
Edwin AI allows us to compartmentalize related alerts into insights which are pushed to our ITSM platform.
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Whether it's a unique alert or something common it always helps our support teams to give them a head start on their ability to resolve an issue. Providing common methods to resolve the issue and areas of the network to check and validate allow us to resolve issues quicker and provide confidence to customers on our ability to maintain our SLA's.
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Inbuilt into LogicMonitor is the ability to look at forecast data. This is a prediction based on current and previous trends on what performance will look like. Anomaly detection provides the ability to run comparisons across graph data to pinpoint variances and anomalies. E.g. status of a device at 1:10pm vs the save time the week before
Whether its CPU, Port throughput or Memory etc... LogicMonitor reviews the past metrics over a pre-determined period of time and predicts and models the likely trajectory. This allows our support teams to predict potential issues before they even happen.
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Remember is you are interested to learn more about our Managed Services then please complete our managed services request form.
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