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How AIOps Can Help Contextualize Your Data

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Defined by Gartner, artificial intelligence for IT operations (AIOps) platforms utilize big data, modern machine learning (ML) and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps addresses key areas, including data collection and storage, analytical engines (real time and deep), visualization/UI, and integration with other applications. AIOps is seen as a way to reduce MTTR and to sort through noise with algorithms, visualization, retrospective analytics and dashboards. Some AIOps tools helps in aggregating and contextualizing data to provide timely insights for IT Ops teams. Over time, you can validate the results of AI/ML algorithms and test the reliability of these forecasts.

More Data for Better Context?

AIOps tools can help in analyzing unstructured data in order to identify higher-level correlations that traditional IT monitoring tools wouldn’t be capable of. But IT Ops teams often struggle with drawing meaningful insights from this data due to lack of context. They invariably end up doing data manipulation or aggregation by setting up models of data ingestion without thinking about the business first. The success of AIOps and other automation methods relies on the quality of the data. Good, representative data is what any machine needs to operate accurately and perform the task that meets the needs of the business. Contextualized data, when taken together from a variety of sources, provides an accurate view of what’s really going on in the business.

“By 2023, 40% of I&O teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity.” - Gartner

Most IT infrastructure monitoring platforms have relied on two key sources of data: performance metric data and infrastructure metadata. Intelligent application and service monitoring solutions like Zenoss integrate with Splunk, Moogsoft, BigPanda, etc. to simplify this wave of data by sorting through the noise to highlight the key events by enabling cross-functional collaboration. This also helps you find higher-level, seasonal trends beyond your usual monitoring metrics and indicators

“Get IT infrastructure-related insights that are timely, actionable and enriched with contextual data for resolution.” - Gartner

Now, Zenoss has introduced full-stack monitoring with AIOps. This means eliminating the number one problem AIOps tools have experienced thus far — limited visibility and context due to the lack of cardinality in the data they're analyzing. Zenoss is delivering a new level of AIOps analytics capabilities for all data types, including metrics, dependency data, events and streaming data. This provides unprecedented context and unprecedented acceleration of problem resolution. For more information on how you can utilize Zenoss Cloud to unify your observability practices across legacy and modern IT environments, contact Zenoss to set up a demo. To learn more about intelligent application and service monitoring, download the Forrester Wave report here.

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The Forrester Wave™: Intelligent Application and Service Monitoring, Q2 2019
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