Snowflake Steps Into Observability With Planned Observe Acquisition

As enterprises race to deploy AI agents and autonomous applications, reliability is quietly emerging as the next competitive battleground. Snowflake’s planned acquisition of Observe underscores that shift—placing observability squarely at the centre of modern data and AI operations.

The AI Data Cloud company has signed a definitive agreement to acquire Observe, an AI-powered observability platform built natively on Snowflake. The move positions Snowflake to expand into the IT operations management software market, estimated at over $50 billion, while rethinking how enterprises collect, store, and analyse telemetry data at scale.

From Monitoring Tools to Data-Centric Observability

Traditional observability stacks were designed for a world of sampled data, short retention windows, and siloed tooling. That model is increasingly strained by AI-driven systems that generate massive volumes of logs, metrics, and traces—and demand real-time context when things go wrong.

By integrating Observe directly into the Snowflake AI Data Cloud, Snowflake is treating observability as a first-class data problem rather than a specialised operational layer. Enterprises will be able to ingest and retain 100% of their telemetry data using Snowflake’s scalable storage and compute model, without the cost tradeoffs that typically force teams to discard high-fidelity signals.

AI SRE and the Push Toward Proactive Operations

At the core of the deal is Observe’s AI-powered Site Reliability Engineer (SRE), designed to help teams move beyond reactive alerts. By correlating logs, metrics, and traces through a unified context graph, the AI SRE enables earlier anomaly detection, faster root-cause analysis, and automated troubleshooting.

Combined with Snowflake’s high-fidelity data foundation, this approach allows operations teams to resolve production issues up to ten times faster, an increasingly critical capability as systems become more distributed, dynamic, and autonomous.

“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, Snowflake. “By bringing Observe’s capabilities directly into the Snowflake AI Data Cloud, we are empowering our customers to manage enterprise-wide observability across terabytes to petabytes of telemetry.”

Open Standards as a Strategic Bet

A notable aspect of the acquisition is its emphasis on open standards. The combined platform will be built on Apache Iceberg and OpenTelemetry, enabling interoperability and flexibility across data and observability workflows.

This unified architecture is designed to support the telemetry volumes required by next-generation AI applications while allowing enterprises to apply analytics and AI consistently across operational and business data. For organizations wary of proprietary lock-in, the open-standard approach offers a more sustainable path as observability and data platforms converge.

Cost, Retention, and the Economics of Scale

Observability costs have become a growing concern for large enterprises, particularly as AI workloads multiply. Sampling and limited retention have been common compromises. Snowflake’s move aims to eliminate those tradeoffs by applying lakehouse economics—object storage and elastic compute—to observability data.

By retaining complete telemetry datasets, enterprises gain deeper visibility into system behavior over time, enabling better forecasting, governance, and AI-driven insights across their data estate.

Industry Signals and Market Direction

“Observability’s cost problem stems from treating telemetry as special-purpose data requiring specialized infrastructure,” said Sanjeev Mohan, Principal Analyst, SanjMo. “Snowflake’s acquisition highlights a critical industry insight: the lines between data platforms and observability platforms are blurring.”

For Observe, the acquisition provides a larger platform to scale its vision. “Observability is fundamentally a data problem,” said Jeremy Burton, CEO, Observe, adding that the combination will help enterprises operate complex AI systems with greater confidence and efficiency.

Pending regulatory approvals, the acquisition will deepen Snowflake’s role in helping enterprises operate reliable AI agents and applications. Observe’s developer-focused tooling is expected to complement Snowflake’s existing workload engines, providing real-time context, faster diagnostics, and AI-assisted remediation.

As AI shifts the bottleneck from building applications to operating them, Snowflake’s bet is clear: the future of observability belongs inside the data platform.