--- title: Fueling the AI SRE: How monday.com Standardized... description: monday.com's engineering team built Observability Guard, a centralized observability platform integrated into their Internal Developer Portal (Sphera), to... canonical: https://daily.dev/posts/fueling-the-ai-sre-how-monday-com-standardized-observability-for-600-services-1kvwmav54 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Fueling the AI SRE: How monday.com Standardized Observability for 600+ Services | daily.dev og:description: monday.com's engineering team built Observability Guard, a centralized observability platform integrated into their Internal Developer Portal (Sphera), to... og:url: https://daily.dev/posts/fueling-the-ai-sre-how-monday-com-standardized-observability-for-600-services-1kvwmav54 og:image: https://api.daily.dev/og/posts/1kvWmAv54.png og:image:alt: Fueling the AI SRE: How monday.com Standardized Observability for 600+ Services 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. # Fueling the AI SRE: How monday.com Standardized Observability for 600+ Services **[monday Engineering](https://daily.dev/sources/monday)** · 13 min read · 7 upvotes · 1 comments ## Summary monday.com's engineering team built Observability Guard, a centralized observability platform integrated into their Internal Developer Portal (Sphera), to standardize alerting and log management across 600+ services and 10 different monitoring vendors. The system provides 107 alert templates covering Kubernetes infrastructure, automated resource discovery for per-resource thresholds, and MAD-based (Median Absolute Deviation) threshold calculation using 14-day baselines with k=3 for warnings and k=5 for critical alerts. Log management is handled through tiered storage with per-subsystem controls that propagate instantly. Beyond helping human engineers, the standardized alert structure creates a clean data contract for AI SRE agents, enabling accurate incident correlation. After over a year as opt-in, mandatory alerts were introduced for high-confidence signals. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What is Median Absolute Deviation (MAD) used for in setting alert thresholds? MAD is used to automatically propose alert thresholds by measuring how far metric data points deviate from the median rather than the mean, making it more robust against outlier spikes than standard deviation. The threshold is calculated as k times MAD, with k=3 for warning alerts and k=5 for critical alerts, typically over a 14-day baseline window. _daily.dev surfaces practical approaches like this for engineers designing their own alerting thresholds._ ### Why does a single blanket alert threshold fail for monitoring multiple SQS queues of different sizes? A single blanket threshold tuned to protect the largest queue will never trigger for smaller queues, so localized backups go undetected. The fix is combining a broad default wildcard alert covering all queues with smart overrides: engineers can set a custom threshold for a specific queue, which automatically excludes it from the blanket rule to avoid double-alerting. _engineers weighing per-resource alert strategies can find similar infrastructure lessons on daily.dev._ ### Why is standardized alerting important for AI SRE agents handling incident response? Standardized alert structures give AI agents a clean, predictable data contract instead of forcing them to correlate hundreds of subtly different custom alerts achieving the same goal. Because the alert structure is uniform, an AI agent can instantly match a current incident to the exact chain of thought used to resolve a past incident triggered by the same alert. _teams building AI-assisted incident response can track this kind of tooling evolution on daily.dev._ ## Community discussion Top comments from developers on daily.dev. **@trevorsuna** · 0 upvotes > Standardizing alert shape before adding an AI layer feels like the real win. Consistent ownership, severity, runbooks, and resource context make automation safer and help humans too. The MAD thresholds are interesting, though I’d still want explicit handling for seasonal workloads and brand-new services. ## Similar posts on daily.dev - [SRE best practices and platform engineering trends: How AI workloads raise demands on observability to meet reliability requirements](https://daily.dev/posts/sre-best-practices-and-platform-engineering-trends-how-ai-workloads-raise-demands-on-observability--y52vimkrl) · Dynatrace · 1 upvotes · 0 comments - [Observability overload is drowning engineers](https://daily.dev/posts/observability-overload-is-drowning-engineers-fes9rhxs9) · The New Stack · 1 upvotes · 0 comments - [Observability 2.0: Why DevOps Teams Are Moving From Monitoring to Intelligent System Understanding](https://daily.dev/posts/observability-2-0-why-devops-teams-are-moving-from-monitoring-to-intelligent-system-understanding-uveczef2f) · DevOps.com · 9 upvotes · 1 comments - [AI-powered data pipeline observability: Stop monitoring and start preventing](https://daily.dev/posts/ai-powered-data-pipeline-observability-stop-monitoring-and-start-preventing-5smmyohkr) · InfoWorld · 1 upvotes · 0 comments - [Autonomous Ops & Observability: Watching Systems That Increasingly Watch Themselves: SD Times 100](https://daily.dev/posts/autonomous-ops-observability-watching-systems-that-increasingly-watch-themselves-sd-times-100-tzivbjvno) · SD Times · 0 upvotes · 0 comments --- Tags: [#kubernetes](https://daily.dev/tags/kubernetes), [#observability](https://daily.dev/tags/observability), [#opentelemetry](https://daily.dev/tags/opentelemetry) [View this post on daily.dev](https://daily.dev/posts/fueling-the-ai-sre-how-monday-com-standardized-observability-for-600-services-1kvwmav54) ```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":"Fueling the AI SRE: How monday.com Standardized Observability for 600+ Services","url":"https://daily.dev/posts/fueling-the-ai-sre-how-monday-com-standardized-observability-for-600-services-1kvwmav54","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/fueling-the-ai-sre-how-monday-com-standardized-observability-for-600-services-1kvwmav54"},"datePublished":"2026-08-10T10:07:17.033Z","dateModified":"2026-09-14T07:54:02.815Z","description":"monday.com's engineering team built Observability Guard, a centralized observability platform integrated into their Internal Developer Portal (Sphera), to...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/3720a86d3b4ff8402712d14c131df772?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/3720a86d3b4ff8402712d14c131df772?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"monday Engineering","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":"monday Engineering","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/3bce2c4601a8468097dd077a4a9e1417","url":"https://daily.dev/sources/monday"},"commentCount":1,"discussionUrl":"https://daily.dev/posts/fueling-the-ai-sre-how-monday-com-standardized-observability-for-600-services-1kvwmav54","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":7},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":1}],"keywords":"kubernetes,observability,opentelemetry","timeRequired":"PT13M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"monday Engineering","item":"https://daily.dev/sources/monday"},{"@type":"ListItem","position":3,"name":"Fueling the AI SRE: How monday.com Standardized Observability for 600+ Services"}]} {"@context":"https://schema.org","@type":"WebPage","@id":"https://daily.dev/posts/fueling-the-ai-sre-how-monday-com-standardized-observability-for-600-services-1kvwmav54","comment":[{"@type":"Comment","text":"Standardizing alert shape before adding an AI layer feels like the real win. 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