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Sumo Logic's new Data Pipelines feature directly addresses a core challenge for AI operations: managing the escalating costs and noise associated with ingesting massive telemetry volumes. By allowing users to filter and route data upstream, the tool aims to improve the quality of datasets used for training and running generative AI models while reducing storage expenses. This capability is significant for organizations seeking to optimize their observability infrastructure without sacrificing the data fidelity required for advanced machine learning workloads.
Sumo Logic expands Data Pipelines to cut observability and security data costs
Data analytics software firm Sumo Logic Inc. today unveiled an expanded Data Pipelines service that lets customers cut and reroute telemetry before any of it is ingested and stored. The controls sit inside the company’s own platform rather than in a separate tool. Security and operations teams are collecting more telemetry than ever, and Sumo Logic […] The post Sumo Logic expands Data Pipelines to cut observability and security data costs appeared first on SiliconANGLE.
Data analytics software firm Sumo Logic Inc. today unveiled an expanded Data Pipelines service that lets customers cut and reroute telemetry before any of it is ingested and stored. The controls sit inside the company’s own platform rather than in a separate tool. Security and operations teams are collecting more telemetry than ever, and Sumo Logic argues that artificial intelligence workloads…
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