Snowflake announced a definitive agreement to acquire observability platform Observe, a move that stitches telemetry-driven reliability tools directly into the company’s AI Data Cloud. The deal — subject to customary closing conditions and regulatory approval — promises to give enterprises a single place to collect, store and troubleshoot telemetry at petabyte scale.
This is immediate, practical consolidation. Snowflake says integrating Observe will let customers resolve production issues up to 10× faster than with conventional reactive monitoring by combining Observe’s AI-powered SRE workflows with Snowflake’s storage and compute economics.
Why Snowflake bought Observe
Observe was founded in 2017 and built its product on Snowflake from early on; the startup has since grown quickly, processing vast volumes of telemetry and winning customers that previously relied on systems like Splunk and Datadog. Snowflake’s pitch is straightforward: telemetry is exploding as companies deploy agentic AI and complex data applications, and keeping that telemetry online and searchable is expensive and operationally painful. By folding Observe into its platform, Snowflake aims to remove the storage-cost excuse that causes organizations to discard logs and traces — the very signals that help predict and prevent downtime.
CEO Sridhar Ramaswamy framed reliability as a business imperative, saying the combined offering will give enterprises "an open, scalable architecture and AI-powered troubleshooting workflows" to manage telemetry across terabytes to petabytes.
Observe’s CEO Jeremy Burton, who has a long history with Snowflake (including a board seat), said the merger would accelerate Observe’s ability to operate at enterprise scale and meet the demands of AI-native production systems.
Timing, price and optics
Snowflake didn’t disclose financial terms in its announcement. Industry reports have suggested a price in the neighborhood of $1 billion, which—if accurate—would make this Snowflake’s largest acquisition to date. The companies have not announced a closing timeline.
The deal also landed on a day when Snowflake experienced service incidents, which critics quickly noted. Snowflake executives told reporters that the acquisition is intended primarily to help customers — but the timing underscored how painful and visible outages can be for cloud platforms and their users. One Snowflake executive said the company had examined Observe’s tooling closely and found it reassuring during its evaluation, even if Observe’s products were not yet part of Snowflake’s internal incident toolkit.
What Observe brings to the table
Observe’s platform focuses on full telemetry retention, open standards (OpenTelemetry, Apache Iceberg), and AI-driven workflows that help site reliability engineers find root causes faster. The company has been well-capitalized, raising substantial funding in recent years and claiming rapid revenue and customer growth. For customers wrestling with sprawling stacks and agentic AI agents, the promise is faster mean-time-to-resolution and cheaper long-term storage by leveraging Snowflake’s underlying data plane.
That pitch fits a broader industry pattern: as enterprises stitch AI into production, observability becomes central to reliability and cost control. The shift toward agentic systems has already reshaped tooling expectations; examples of agentic capabilities and automated booking flows in consumer products illustrate how quickly AI agents are being embedded into workflows and the scale of telemetry they generate. See how agentic features have been rolling into other products in recent months with Google’s AI Mode Adds Agentic Booking for Tickets, Salons and Wellness Appointments, and how deep-search AI is being tied into personal and corporate data with Gemini’s Deep Research May Soon Search Your Gmail and Drive — Google Docs Gains ‘Document Links’ Grounding.
The market and the risks
Observability is crowded and strategic. Vendors such as Datadog and Splunk have established footprints, and customers will weigh the benefits of a vertically integrated solution against concerns about vendor lock-in and data mobility. Snowflake emphasizes open standards and economics as mitigations. Regulators and customers alike will watch whether the combined product preserves interoperability and avoids making telemetry harder to export.
For Snowflake, the acquisition doubles as a product bet and a market signal: it wants to be not just the place you store data, but the place you run and keep critical AI and data applications reliable.
This story will evolve as regulators and the companies disclose more details and a closing timeline. For now, enterprises building AI-native systems have another major vendor promising to make observability cheaper, faster and more tightly integrated with the data plane they already rely on.