Snowflake has signed a definitive agreement to acquire Observe, an AI-powered observability platform built natively on Snowflake, as the data cloud provider deepens its push into enterprise-scale reliability, operations, and AI-driven application management.

The acquisition positions Snowflake to deliver a new generation of AI-powered observability, designed for the scale, complexity, and economics of modern AI-native enterprises operating across distributed systems, autonomous agents, and data-intensive applications.

“As our customers build increasingly complex AI agents and data applications, reliability is no longer just an IT metric—it’s a business imperative,” said Sridhar Ramaswamy, CEO of Snowflake. “By bringing Observe’s capabilities directly into the Snowflake AI Data Cloud, we’re enabling enterprise-wide observability with open architecture and AI-powered troubleshooting at massive scale.”

From Monitoring to Agentic, AI-Driven Troubleshooting

Observe was built on Snowflake from its inception, making the integration a natural extension of the Snowflake AI Data Cloud. Together, the companies aim to move observability beyond reactive monitoring toward proactive, automated operations.

At the core of the offering is Observe’s AI-powered Site Reliability Engineer (SRE), which correlates logs, metrics, and traces through a unified context graph. By combining this intelligence with Snowflake’s trusted enterprise data, teams can detect anomalies earlier, identify root causes faster, and resolve production issues up to 10 times faster, according to the companies.

This agentic approach is increasingly critical as enterprise systems become more distributed, autonomous, and AI-driven.

Open Standards and Telemetry at Scale

The acquisition also establishes a unified, open-standard observability architecture based on Apache Iceberg and OpenTelemetry, both of which Snowflake actively contributes to.

By treating telemetry as first-class data within the Snowflake AI Data Cloud, enterprises can manage terabytes to petabytes of logs, metrics, and traces using economical object storage and elastic compute. This approach allows observability data to be analyzed alongside business and operational data with consistent governance, analytics, and AI models.

Industry analysts see this as part of a broader shift away from specialized observability stacks toward lakehouse-style economics.

“Observability’s cost problem stems from treating telemetry as special-purpose data,” said Sanjeev Mohan, Principal Analyst at SanjMo. “Snowflake’s acquisition highlights how the lines between data platforms and observability platforms are blurring.”

Eliminating the Cost-Retention Tradeoff

As AI-driven applications generate unprecedented telemetry volumes, many organizations have been forced to rely on data sampling or short retention windows to control costs. Snowflake and Observe say their combined platform removes that tradeoff.

By unifying Observe’s AI-driven observability with Snowflake’s scalable data foundation, enterprises can retain high-fidelity telemetry data for longer periods while reducing overall observability costs—improving visibility across their entire data estate without sacrificing economics.

“Observability is fundamentally a data problem,” said Jeremy Burton, CEO of Observe. “By combining our AI-powered SRE with Snowflake’s AI Data Cloud, we can deliver faster insights, greater reliability, and dramatically better economics for operating the next generation of AI applications.”

Expanding Snowflake’s IT Operations Footprint

Beyond product integration, the acquisition expands Snowflake’s presence in the fast-growing IT operations management (ITOM) market. Gartner estimates the ITOM software market reached $51.7 billion in 2024, growing 9% year over year.

Following the close of the transaction—subject to regulatory approvals—Snowflake plans to deepen its focus on helping enterprises operate reliable AI agents and applications at scale. Observe’s developer-friendly approach is expected to complement Snowflake’s existing workload engines with real-time enterprise context, faster root-cause analysis, and AI-assisted troubleshooting.

Together, Snowflake and Observe aim to redefine observability as a core capability of the modern data platform—one built for AI-native systems where reliability, cost efficiency, and speed are inseparable.

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