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AnomalyGuard
بواسطة Milos Gregor
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Detect anomalies in warehouse metrics. Managed deploy on Azure Container Apps.
AnomalyGuard finds unusual patterns in the numbers that matter to your business - sales, occupancy, transactions, volumes, and similar metrics stored in your warehouse. When something breaks from normal - a spike, a drop, a data gap, or a lasting shift - it surfaces that anomaly so teams can act.
This Azure Marketplace offer deploys AnomalyGuard as a managed application on Azure Container Apps: a Master app (UI and API) plus scalable Worker apps for load and detection jobs, backed by your PostgreSQL database and secured with Microsoft Entra ID.
What you get
- Connectors - encrypted connections to supported source databases (for example SQL Server and PostgreSQL)
- Data views - define what to load, how to split series by category, which detectors to run, and when jobs run
- Detectors - statistical checks for spikes, gaps, seasonality breaks, changepoints, flatlines, and more
- Home & filters - role-ready views of the anomaly cloud, with comments and optional AI summaries
- REST API & CLI - the same operations for CI/CD, integrations, and AI agents (API keys for non-interactive access)
How deployment works
- One Container Apps environment with Log Analytics
- Master (always 1 replica) + Worker (configurable scale)
- You provide PostgreSQL, Entra ID app registration, and shared secrets at install time
- Optional VNet integration for private networking
Plans
Choose a plan by how many active data views you need—from a single-view Start plan through Small Team, Growing Team, and unlimited Enterprise Team.
Who it is for
- BI and analytics teams who need continuous monitoring of warehouse KPIs
- Operations and data-quality owners who must catch silent metric failures early
- Platform teams who want a managed Azure deploy instead of building detection from scratch
After deployment, connect your warehouse, create a first data view, run load and detection, pin filters on Home—and start reviewing anomalies the same day.
لمحة سريعة
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