Snowflake, the AI Data Cloud company, has announced its intent to acquire Observe, a leader in AI‑powered observability technology, in a strategic move aimed at expanding its platform capabilities and delivering next‑generation observability at enterprise scale. The deal will bring Observe’s technology directly into Snowflake’s ecosystem to help organizations ingest, store and act on telemetry data from complex systems — including logs, metrics and traces — while lowering costs and improving reliability.
With this acquisition, Snowflake aims to create unified, scalable observability tightly integrated with its AI Data Cloud, rather than relying on separate monitoring tools that often silo operational context from business data. According to Snowflake CEO Sridhar Ramaswamy, reliability has become “a business imperative” as companies build increasingly complex AI agents and data applications.
What Snowflake and Observe Bring Together
Observe’s AI‑powered Site Reliability Engineer (SRE) platform uses agentic AI and a unified context graph to correlate disparate telemetry signals — enabling teams to detect anomalies earlier, diagnose root causes faster and resolve production issues up to 10× more quickly than traditional approaches. By fusing this capability with Snowflake’s secure data foundation, enterprises can retain high‑fidelity data for longer, eliminate sampling tradeoffs, and apply analytics and AI consistently across observability and business datasets.
The combined platform uses open standards like Apache Iceberg and OpenTelemetry. These standards help with interoperability and scalability. They also keep storage and compute costs manageable. This is crucial for enterprises that handle large volumes of telemetry data from modern distributed systems.
Impact on the IT Industry
The acquisition signals a significant shift in the IT landscape, especially for IT operations management (ITOM) and observability technologies:
1. Observability Becomes a First‑Class Data Problem
Traditionally, observability has been treated as a specialized, standalone domain with separate tooling. Snowflake’s integration reflects a broader industry move to treat telemetry data like any other enterprise data — integrating it into enterprise data platforms where it can be analyzed at scale and used alongside business insights.
2. AI‑Driven Troubleshooting Moves Center Stage
The integration of AI-assisted SRE capabilities into a uniform data environment lets IT teams move from reactive monitoring to proactive, automated issue resolution. In this way, it minimizes downtime and operational risk for complex distributed applications and microservices-a growing priority as enterprises deploy AI agents and autonomous systems.
3. Cost and Complexity Challenges are Addressed
Modern observability can be expensive because it requires storing and processing huge volumes of telemetry. Snowflake’s scalable architecture allows enterprises to retain telemetry without excessive costs, which can democratize observability for organizations that previously had to sample or limit retention due to budget constraints.
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Broader Effects on Businesses
For businesses operating in IT, software engineering and digital operations, Snowflake’s move has several wider implications:
• Enhanced Operational Visibility:
The inclusion of observability within the data platform enhances visibility over the entire stack. This is from infrastructure toapplication performance. This is responsible for risk management and optimizing user experience.
• Faster Time to Resolution:
Because AI-powered root cause analysis and troubleshooting enable teams to act on problems much faster, downtime-related productivity and revenue repercussions are reduced.
• Better Governance and Compliance: Telemetered information under strong governance facilitates better compliance with regulatory needs, and at the same time, it provides trails for auditors, which is important in fields where finance and health come into play.
• Competitive Advantage in AI-Powered Systems: To the extent that companies increasingly rely on AI-enhanced apps and self-driving systems, observability is no longer merely a nicety—it has become a difference-maker. Snowflake’s extended platform could certainly aid these organizations in scaling these systems.
Acquiring Observe has underlined a larger trend in the market: accelerating scales and complexity of data force observability to evolve from siloed monitoring to integrated, AI-driven analysis native within enterprise data platforms. If successfully integrated, this move could reshape how organizations manage system reliability, react to disruptions, and drive performance outcomes across IT and business functions.