Cloud data firm Snowflake will buy AI-powered observability leader Observe to expand its capabilities in a $50+ billion IT operations management software market.
Snowflake played it cool with the acquisition price, as that’s a secret. But the idea is to offer a unified platform blending data storage, AI deployment, and monitoring.
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Market forces are aligned well at this moment. The IT operations management software market grew 9% in 2024 to reach $51.7 billion, according to Gartner, while 54% of organizations adopted AI monitoring last year.
What makes this acquisition interesting isn’t just the numbers – it’s the relationship history. Observe was built on Snowflake from its inception, and Snowflake’s venture arm invested in Observe in March 2024. These weren’t strangers suddenly deciding to merge – they were partners who’ve been solving everything from application slowdowns to AI model performance issues together for nearly two years.
AI assistant that solves problems
The acquisition’s crown jewel isn’t traditional monitoring software – it’s Observe’s AI Site Reliability Engineer (AI SRE), an AI chatbot that can resolve production issues up to 10x faster than traditional troubleshooting methods.
Consider the transformation: instead of developers spending hours or days hunting down system failures, they now engage in natural language conversations with an AI that diagnoses problems in real-time. Users ask the AI to identify malfunction causes and customize its investigation approach for each unique scenario.
Behind this speed lies the O11y Context Graph, a data management engine that processes hundreds of terabytes of telemetry data daily. This creates indexes and materialized views that cut search times and eliminate frustrating loading delays.
Beyond routine monitoring, the platform tracks specialized metrics like inference costs for large language models, positioning it perfectly for the AI-first enterprise landscape rapidly emerging across industries.
What this means for enterprise AI operations
This acquisition eliminates a business issue: the cost of retaining observability data long enough for meaningful troubleshooting. Previously, organizations were forced to delete telemetry data frequently to avoid storage expenses, making investigation of older incidents virtually impossible.
Snowflake’s approach is compressing data and storing it in low-cost object storage, which means companies can now retain observability data for extended periods without budget constraints. Christian Kleinerman, Snowflake’s EVP of product, explained that the combined platform enables customers to manage enterprise-wide observability across petabytes of telemetry data.
The integration establishes a unified, open-standard architecture based on Apache Iceberg and OpenTelemetry, directly challenging established players like Datadog. For enterprises already using Snowflake, the benefits are immediate: they can keep their observability data within their Snowflake account rather than shipping it to third-party providers – a significant advantage for data governance and security compliance.
Snowflake’s AI evolution
This acquisition represents far more than monitoring capabilities – it’s the culmination of Snowflake’s broader strategy to transition from data warehousing company to AI-centric platform. The deal builds on strategic moves including acquiring TruEra in May 2024 and November 2024’s acquisitions of Select Star and Datometry technology.
Snowflake simultaneously revealed an expanded partnership with Google Cloud, bringing Gemini models directly into Snowflake Cortex AI. This dual announcement sends an unmistakable message: Snowflake positions itself as the central hub where data teams, model providers, and applications converge.
Subject to regulatory approval, this acquisition will deepen Snowflake’s commitment to helping customers build and operate reliable AI agents and applications.
For enterprises watching AI workloads become mission-critical to their operations, Snowflake bets they’ll choose a unified platform combining data storage, AI model deployment, and comprehensive monitoring over disconnected tool collections.
Experts predict 2026 will bring less AI hype and more governance, delayed enterprise spending, AI moving into OT, smarter cyberattacks, and faster cooling tech.
