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AIOps

What is AIOps and What are Top 10 AIOps Use Cases

Artificial Intelligence for IT Operations (AIOps) is an advanced analytics and operations management solution that is designed to help organizations address the challenges of monitoring and managing IT operations in the era of digital transformation. AIOps leverages the power of Artificial Intelligence and Machine Learning Technologies to enable continuous insights across IT operations monitoring.

MARTINA | Xalient's AIOps Platform | UK

Xalient’s advanced virtual network engineer, bringing AI/ML technology and automation to network management, helping deliver high-performing and resilient networks. MARTINA (Monitoring through Artificial Intelligence and Analytics) is a unique and game-changing AIOps innovation from Xalient that’s making a difference in many global businesses today.
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AIOps Hurdles Not Many Vendors Talk About

According to one survey, 94% agree that AIOps is “important or very important” to manage network and cloud applications performance. AIOps intends to help customers contextualize humongous data volumes and streamline IT operations with automation. As IT infrastructure grows in complexity, alerts flood IT Ops centers and Ops teams drown in managing the deluge.
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Are you depending on CMDB to build topology for AIOps?

The absence of topology can be a key inhibitor for AIOps tools, creating blind spots for AIOps as they only have access to event data. A topology, an IT service model, or a dependency map is a real-time picture of tools and services that are connected and dependent on each other to deliver an IT service. Suppose an application is driven by cloud-native technology, connected with any kind of ephemeral systems (containers and microservices), and relies on storage, database, and a load balancing tool.
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Why Composable Analytics Matter for Multi-Cloud AIOps

There’s plenty of loaded terminology and buzzword bingo when it comes to the latest advances in cloud application delivery. Especially when it comes to multi-cloud – which should merely mean multiple cloud instances when modern cloud applications really leverage multiple hybrid IT operating models, atop both existing business silos and newer microservices application workloads.
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Data Value Gap - Data Observability and Data Fabric - Missing Piece of AI/AIOps

A pivotal inhibitor to mitigate these challenges is the Data Value Gap. Data automation and Data Fabric are emerging as key technologies to overcome these challenges. Learn from industry experts about these key technologies and how they create a lasting impact in enterprise IT.