IBM Watson AIOps’ state-of-the-art and multi patent-pending log anomaly detection technology is capable of automatically parsing IT application and infrastructure logs from log aggregation tools (e.g., Splunk, Humio, LogDNA, and Logstash) to automatically detect anomalies in real-time. In this article, we describe the AI in our Watson AIOps solution: This, in turn, saves millions of dollars by preventing direct costs (lost revenue, penalties, opportunity costs, etc.) and indirect costs (customer dissatisfaction, lost customers, lost references, etc.).įortunately, Watson AIOps can do all of this for you! Figure 1 shows the various types of data that Watson AIOps can process. AI can help IT operations managers, also known as Site Reliability Engineers (SREs) in detecting issues early, predicting them before they occur, reducing event and alert noise, locating the specific application or infrastructure component that is the source of the issue, determining the scope of incident impact, and recommending relevant and timely actions.Īll these analytics help reduce the mean times to detect (MTTD), identify/isolate (MTTI) and resolve (MTTR) an incident. Information Technology (IT) Operations management is a vexing problem for most companies that rely on IT systems for mission-critical business applications.ĭespite the best intentions of engineers, good designs, and solid development practices, software and hardware systems deployed in companies in service of critical business applications are susceptible to outages, resulting in millions of dollars in labor, revenue loss, and customer satisfaction issues each year.Īrtificial intelligence (AI) can help solve these problems.
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