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Clusters group similar events together to help you discover patterns, debug at scale, and detect anomalies. When you have many events (either custom events or semantic events), clustering reveals what’s actually happening in your system.

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What Are Clusters?

Every event has an attribute field containing JSON data. Clusters group events by extracting a string value from this JSON using a Mustache template, then grouping events with similar extracted values. For example, if your events have attributes like {"error_message": "Connection timeout", "url": "..."}, you can cluster by {{error_message}} to group similar errors together. Common patterns that emerge:
  • Similar failures — Errors with the same root cause, regardless of surface differences (for example, 47 failures all caused by lazy-loaded content).
  • Behavioral groups — Events that share a common action or intent (for example, all “search for product” events).
You control clustering by defining a Mustache template that extracts the value to cluster on. Laminar handles the similarity matching and keeps clusters updated as new events arrive. Each cluster has member events and automatically generated cluster name. Cluster name is can be regenerated when the member events change significantly.

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Set up clustering

Start Clustering dialog with value template input
  1. In Events, click your event definition to open it.
  2. Click Start Clustering.
  3. Enter a Value Template — a Mustache string like {{content}} or {{error.message}} that extracts the value to cluster on from the event’s attribute JSON.
  4. Click Start, then switch to Clusters to see grouped results.

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How Clustering Works

Every event stores its data in an attribute field as JSON. When you start clustering:
  1. Laminar evaluates your Mustache template against each event’s attribute JSON
  2. The template extracts a string value (for example, {{content}} pulls the content field)
  3. Events with similar extracted strings are grouped into clusters
As new events arrive, clusters continuously update and stay current, so you can track emerging patterns and regressions over time.

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What You Can Do With Clusters

Understand user behavior — See what users are actually trying to accomplish, not just what buttons they clicked. Intent clusters reveal the “why” behind actions. Debug at scale — When something breaks, find all similar failures instantly. One fix addresses an entire cluster of issues. Detect anomalies — Unusual patterns surface automatically. Spot problems before users report them. Track trends — See how behavior changes over time. New clusters emerging? Old patterns disappearing? Build datasets — Export clusters as evaluation datasets. Test your agent against real-world patterns, not synthetic examples.

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Viewing Clusters

In the Laminar dashboard:
  1. Go to Events to see the raw event stream
  2. Switch to Clusters to see grouped patterns
  3. Click any cluster to see its members, centroid, labels, and confidence score
  4. Filter by time range, event type, or cluster label
  5. Export cluster members to a dataset for evaluation

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Example: Finding Extraction Failures

Your browser agent extracts product data. Some extractions fail. Each extraction.failed event has an attribute like: 
{
  "error_message": "Element not found: .product-price",
  "url": "https://shop.example.com/item/123",
  "selector": ".product-price"
}
Instead of searching through logs:
  1. Start clustering with the template {{error_message}}
  2. View clusters to see failures grouped by similar error messages
  3. One cluster shows 47 failures, all on sites with lazy-loaded content
  4. Another cluster shows 12 failures, all with the same malformed selector
  5. Fix each root cause once, verify with the cluster members