Salvatore Salamone

As the AIOps market matures, many in the industry believe businesses will turn to AIOps platforms as their sole monitoring tool as these platforms are enabled to natively acquire data and analyze it.

In this week’s real-time analytics news: HPE launched HPE Swarm Learning, a privacy-preserving, decentralized machine learning framework for the edge.

Early adopters are fusing and analyzing their massive geospatial and time-series data in real-time to support new application areas.

Modern observability solutions provide visibility into the workings of complex edge applications and help staff make data-driven decisions when investigating latency issues.

In this week’s real-time analytics news: AWS announced the general availability of AWS IoT TwinMaker, which helps developers build digital twins of real-world systems by integrating data from multiple sources and combining that data to create a knowledge graph that models the real-world environment.

Continuous Intelligence platforms leveraging multiple data sources can surface performance issues immediately, whenever they emerge.

In this week’s real-time analytics news: New and enhanced solutions for managed APIs, wireless edge-to-cloud, and IoT lead the list.

SiEMs are increasingly playing a role in identifying precursors to DDoS attacks and in helping mitigate the root causes of those attacks.

Modern observability is needed to help organizations find if and where they are using software with recently discovered vulnerabilities.

Tasks previously performed by the security staff, such as vulnerability scanning, log analysis, and ticket checking, can now be automatically executed by a CI-based platform.

In this week’s real-time analytics news: IBM unveiled its new system that delivers real-time AI for transaction processing at scale.

The new IBM z16 offers AI inferencing (delivered via the integrated on-chip AI accelerator IBM Telum Processor) and is designed to analyze real-time transactions, at scale, for mission-critical workloads.