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IBM's Confluent buy has observability, IT ops implications | TechTa...

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Dec 9, 2025

IBM's Confluent buy has observability, IT ops implications | TechTa...

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IBM's $11 billion deal for another open source software company raises possibilities for its Red Hat and HashiCorp portfolios, and for some, uneasy echoes of the past.

Industry watchers see potential tie-ins with a wide range of IBM software tools resulting from its acquisition of Confluent, including products from Red Hat and HashiCorp.

IBM reached an agreement this week to acquire the Mountain View, Calif.-based company for $11 billion in cash in a deal expected to close in mid-2026. Confluent's business is primarily based on enterprise support through its Confluent Cloud platform for near-real-time data pipelines built on the open source Apache Kafka project. While the impetus for the deal is primarily enhanced data management for agentic AI systems, DataOps tools including Kafka have seen growing use among enterprise IT operations teams outside AI and data science disciplines over the last three years to feed data to advanced IT automation systems and observability tools.

Thus, IBM could also use the Confluence acquisition to enhance data management for its observability, IT automation and FinOps tools, according to IT analysts.

"Integrating the ability to move data around in real time means, for example, that Instana can now analyze live data streams from all kinds of different hybrid cloud locations and sources, centralize all OpenTelemetry streams and even add eBPF to that mix," said Torsten Volk, an analyst at Omdia. "Especially in cloud-native environments, where issues often start as seemingly innocent correlations between events, real-time analysis is key."

The Kafka data pipeline could eventually feed Project infragraph, part of IBM's AI roadmap with HashiCorp, Volk said.

"The dependency graph in infragraph is compiled through basically the same telemetry data that Instana ingests," he said. "Infragraph could have a real-time dependency map with a lot more detail compared to the currently ingested batch data. And Confluent could make sure that only

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