πŸ‘½Anomalies Detection

What is Anomaly Detection?

Seemore's Anomaly Detection automatically identifies unusual cost patterns in your data infrastructure before they become expensive problems. Using statistical analysis and AI-powered root cause identification, the system monitors your compute costs continuously and alerts you to significant changesβ€”whether spikes that could blow your budget or unexpected drops that might indicate issues.

Why Anomaly Detection?

Cloud data platforms like Snowflake and Databricks make it easy to scale, but costs can quickly spiral out of control. Anomaly Detection helps you:

  • Catch cost overruns early - Identify unusual spending patterns within 24 hours

  • Understand the why - AI-generated root cause analysis explains what's driving each anomaly

  • Stay informed - Automatic Slack notifications keep your team in the loop

  • Take action faster - Prioritize high-severity issues that need immediate attention

How It Works

Daily Monitoring

Anomaly Detection runs automatically as part of your overnight data pipeline. Every day, the system:

  1. Analyzes your spend across all accounts and compute units (warehouses)

  2. Compares against baseline using the previous 14 days of cost data

  3. Calculates severity using Z-score statistical analysis

  4. Generates explanations via AI-powered root cause analysis

  5. Sends notifications to configured Slack channels

Detection Methodology

Baseline Period: 14 days of historical cost data

Severity Levels:

  • High Severity: >4 standard deviations from baseline

  • Low Severity: >2 standard deviations from baseline

Classification Types:

  • Spike ⬆️ - Cost increased significantly

  • Drop ⬇️ - Cost decreased significantly

Granularity Levels

Anomaly Detection works at multiple levels:

  • Account Level - One anomaly maximum per account per day

  • Compute Unit Level - Multiple anomalies per warehouse, per day

  • Job Level - Track anomalies in specific data pipeline jobs

  • Query Level - Drill down to individual queries

Key Features

🎯 Configurable Detection Rules and Notifications

To enable alerts you will need to configure channels in the platform -> Channels

Create custom anomaly detection rules and notifications tailored to your needs:

  • Default Rules - Pre-configured to monitor top 10 most expensive warehouses per account

  • Custom Rules - Define your own rules at account or compute unit level

  • Minimum Thresholds - Set dollar amount minimums (e.g., only alert for anomalies >$50)

  • Asset Selection - Choose specific accounts or compute units to monitor

Stay informed with automatic alerts:

  • Real-time notifications when new anomalies are detected

  • Configurable per detection rule

  • Support for multiple channels and teams

πŸ€– AI-Powered Root Cause Analysis

When you click on any anomaly, the system provides:

  • Visual Timeline - Graph showing the baseline and the anomaly point

  • Cost Impact - Exact dollar amount of the increase or decrease

  • Detailed Explanation - Natural language description of what caused the anomaly

  • Contributing Factors - Queries, jobs, and warehouses involved

How To Use Anomalies detection

1. Enable Default Rules

The fastest way to start detecting anomalies:

  1. Navigate to Anomaly Detection in the Seemore app

  2. Go to Detection Rules

  3. Enable the Default Baseline rule

  4. This automatically monitors your top 10 most expensive warehouses per account

2. Configure Alerting Notifications

To receive alerts in Slack:

  1. In the Detection Rules settings

  2. Click on your active rule

  3. Under Notifications, select Slack

  4. Choose your channel (show to define channel)

  5. Save your settings

3. Create Custom Rules

For more control over what gets monitored:

  1. Click New Rule in the Detection Rules screen

  2. Choose Account Level or Compute Unit Level

  3. Select specific assets to monitor

  4. Set a Minimum Threshold (e.g., $50) to filter out small anomalies

  5. Configure notification preferences

  6. Activate the rule

Best Practices

  • Start with defaults - Enable the default baseline rule first to see how anomalies appear for your account before creating custom rules.

  • Set meaningful thresholds - Use minimum dollar thresholds to avoid alert fatigue from small, insignificant cost changes.

  • Monitor high-severity first - Focus on high-severity anomalies (>4Οƒ) as they represent the most significant deviations.

  • Review regularly - Check your Anomaly Dashboard weekly to identify patterns and adjust your detection rules accordingly.

Need Help?

Reach out to our team if you have questions or need help configuring Anomaly Detection. We're here to help you optimize your data costs!

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