--- title: Observability at Scale: Whatnot at Snowflake Summit description: Whatnot, a hyper-growth live-shopping platform processing billions of daily events, shared how they tackled data observability and analytics at scale using... canonical: https://daily.dev/posts/observability-at-scale-whatnot-at-snowflake-summit-q2xwcm14y twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Observability at Scale: Whatnot at Snowflake Summit | daily.dev og:description: Whatnot, a hyper-growth live-shopping platform processing billions of daily events, shared how they tackled data observability and analytics at scale using... og:url: https://daily.dev/posts/observability-at-scale-whatnot-at-snowflake-summit-q2xwcm14y og:image: https://api.daily.dev/og/posts/Q2XWcm14y.png og:image:alt: Observability at Scale: Whatnot at Snowflake Summit og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Observability at Scale: Whatnot at Snowflake Summit **[Snowflake](https://daily.dev/sources/snowflake)** · 8 min read · 0 upvotes · 0 comments ## Summary Whatnot, a hyper-growth live-shopping platform processing billions of daily events, shared how they tackled data observability and analytics at scale using Snowflake. They evolved from a centralized dbt setup to a decentralized, modular data stack with infrastructure-as-code, enabling individual business units to manage their own Snowflake warehouses. To democratize data access, they progressed through three phases of AI analytics — from a rigid Slack SQL bot to Snowflake Cortex Agents powering conversational analytics via Hex Threads — achieving 80%+ employee adoption within 90 days. On the monitoring side, Snowflake's next-gen event tables (via Snowflake Trail) made log ingestion 10x faster, and AI-assisted alert creation replaced hundreds of lines of SQL with natural language prompts. Whatnot also enforces strict epistemic hygiene rules for AI agents, prohibiting causal claims and requiring probabilistic language to maintain data trustworthiness. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is Snowflake Trail and how does it improve event logging performance? Snowflake Trail is a telemetry engine built on next-generation event tables that made event ingestion roughly 10 times faster than previous logging methods. Before this change, standard utilization logs were delayed by three to four hours, and running frequent diagnostic scans every 15 minutes to catch issues sooner burned through compute budgets and required strict admin access to view. _Teams weighing real-time monitoring options on Snowflake can track platform changes like this via daily.dev._ ### How did Whatnot's internal AI data assistant evolve from 2024 to 2026? Whatnot progressed through three phases: a 2024 Slack bot (@databot) that auto-generated SQL but needed heavy human verification, a 2025 rollout of Snowflake semantic views across tools like Sigma and Glean that pushed text-to-SQL accuracy above 90% but lacked a unified entry point, and a 2026 launch of Hex Threads, a conversational assistant built on Snowflake Cortex Agents that scans the data network directly. _Developers building conversational analytics tools can follow similar Cortex Agents patterns via daily.dev._ ### What guardrails does Whatnot use to prevent AI analytics agents from making false causal claims? Whatnot enforces an 'epistemic hygiene' playbook requiring agents to use probabilistic language by default (like 'this likely reflects' or 'the data is consistent with') while banning definitive phrases such as 'this proves' or 'this clearly shows.' Agents must separate raw data observations from subjective interpretation and are prohibited from declaring causation from observational data, using terms like 'associated with' instead. _Teams designing trustworthy AI data agents can compare guardrail approaches like this on daily.dev._ ## Similar posts on daily.dev - [Introducing Snowflake Interactive Analytics for Modern Data Analytics](https://daily.dev/posts/introducing-snowflake-interactive-analytics-for-modern-data-analytics-cd9e7bmwl) · Snowflake · 0 upvotes · 0 comments - [AI Observability in Snowflake](https://daily.dev/posts/ai-observability-in-snowflake-iza5dnqgy) · Snowflake Community · 1 upvotes · 0 comments - [AIがデータベース市場を再定義する](https://daily.dev/posts/ai--msvmj1rkk) · ClickHouse · 2 upvotes · 0 comments - [Revolutionizing Analytics: ThoughtSpot and Snowflake Cortex AISQL](https://daily.dev/posts/revolutionizing-analytics-thoughtspot-and-snowflake-cortex-aisql-epkiopcqz) · Snowflake Community · 0 upvotes · 0 comments --- Tags: [#data-analysis](https://daily.dev/tags/data-analysis), [#observability](https://daily.dev/tags/observability), [#big-data](https://daily.dev/tags/big-data), [#snowflake](https://daily.dev/tags/snowflake) [View this post on daily.dev](https://daily.dev/posts/observability-at-scale-whatnot-at-snowflake-summit-q2xwcm14y) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Observability at Scale: Whatnot at Snowflake Summit","url":"https://daily.dev/posts/observability-at-scale-whatnot-at-snowflake-summit-q2xwcm14y","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/observability-at-scale-whatnot-at-snowflake-summit-q2xwcm14y"},"datePublished":"2026-08-04T14:31:25.763Z","dateModified":"2026-09-14T09:30:56.348Z","description":"Whatnot, a hyper-growth live-shopping platform processing billions of daily events, shared how they tackled data observability and analytics at scale using...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/ee5e2a29133a112b3ed6ff52b32fc965?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/ee5e2a29133a112b3ed6ff52b32fc965?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Snowflake","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Snowflake","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/fd3e7ffcdf2c438db701a0c6b34281ca","url":"https://daily.dev/sources/snowflake"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/observability-at-scale-whatnot-at-snowflake-summit-q2xwcm14y","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"data-analysis,observability,big-data,snowflake","timeRequired":"PT8M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Snowflake","item":"https://daily.dev/sources/snowflake"},{"@type":"ListItem","position":3,"name":"Observability at Scale: Whatnot at Snowflake Summit"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/observability-at-scale-whatnot-at-snowflake-summit-q2xwcm14y#faq","mainEntity":[{"@type":"Question","name":"What is Snowflake Trail and how does it improve event logging performance?","acceptedAnswer":{"@type":"Answer","text":"Snowflake Trail is a telemetry engine built on next-generation event tables that made event ingestion roughly 10 times faster than previous logging methods. 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