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Use Case


AIOps is the use of machine learning and artificial intelligence to automate IT operations and reduce bottlenecks associated with technology needs.

AIOps initiatives create business agility by accelerating time-consuming ITOps tasks.

Hazelcast AIOps Architecture Diagram

Hazelcast’s low latency in-memory computing platform is ideal for AIOps applications.

Fast Stream Processing for data filtering and aggregation – many IT Ops tools charge for the data stored. Hazelcast Jet enables you to sample/filter/aggregate data ingested into AIOps and ITOps tools, helping reduce costs while still delivering real-time visibility.

Ultra-Fast Distributed Machine Learning – Bring the machine learning closer to applications across Multi-Cloud and Edge Architectures to drive further autonomous sense and response capabilities.

Edge-to-Cloud Ingest – Hazelcast Platform can run at the Edge, where the volumes of data are orders of magnitude greater, and therefore it isn’t practical to bring all the data back and aggregation, filtering, sampling and compression become a necessity.

Ingest and Correlation Z/OS to Multi-Cloud and Microservices – Today’s complex applications are interconnected, requiring cross-platform visibility to correlate problems across omni-channel applications in microservices and Core applications running on Z Platform. End-to-end visibility plus AIOps ensures accurate, fast root cause analysis and a complete picture of business impacts.

Hazelcast and IBM for AIOps

Hazelcast can be run at the edge, in any cloud (private, hybrid or multi-) to run and accelerate AIOps applications that need to process and analyze critical operations to create efficiency on technology deployments.