What is Expanso and how does it work?

Expanso is a managed platform for deploying intelligent data pipelines at the edge. It processes data where it's generated - reducing bandwidth, latency, and costs. You deploy lightweight agents on your infrastructure, build pipelines using our visual builder or YAML, and control everything from a central SaaS platform.

Can I run AI/ML models directly in my data pipelines?

Yes! Expanso supports running ONNX, TensorFlow Lite, and other models as native pipeline steps. Execute low-latency inference on streaming data, enrich events with model outputs (like risk scores), and make decisions at the edge without cloud round-trips.

How many pre-built components are available?

Expanso provides 200+ pre-built components including inputs (Kafka, HTTP, files), processors (transformations, filtering, PII masking, aggregations), and outputs (S3, Snowflake, Datadog, Splunk). Browse the complete catalog in our Component Reference.

Do I need to write code to build pipelines?

No - use our drag-and-drop visual pipeline builder to create sophisticated pipelines without code. For advanced use cases, you can also write pipelines in YAML or use the Bloblang transformation language for complex data mappings.

How does Expanso help with data governance and compliance?

Expanso includes built-in governance features: automatic PII detection and masking, policy enforcement at the edge, RBAC, SSO integration, and comprehensive audit trails. Mask sensitive data before it ever leaves your network.

Get execution history

GET /executions/:id/history

Returns state change events and lifecycle history for a specific execution.

WHAT YOU GET: Timeline of events showing:

State transitions (pending → starting → running → complete/failed)
Timestamps for each transition
Messages explaining why each transition occurred
System events affecting this execution

WHEN TO USE:

Debug execution failures (see what led to failed state)
Investigate slow starts (check time in pending/starting states)
Audit execution lifecycle for compliance
Understand execution behavior over time

FILTERING:

since: Only show events after a specific timestamp (reduces noise)

COMMON PATTERNS:

"Why did this execution fail?" - Review history for error messages
"When did this execution start running?" - Find 'running' state transition
"How long was it pending?" - Calculate time between created and running states

Get execution history

/executions/:id/history

Request

Responses

Get execution history

/executions/:id/history

Request​

Responses​

Request

Responses