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.

types.NodeStatus

connected_sincestring

ConnectedSince is when the node connected in the current session

connection_statetypes.NodeConnectionState (string)

ConnectionState is the current connection state of the node

Possible values: [disconnected, connected, lost, deleted]

created_atstring

CreatedAt is when the node was first registered

disconnected_sincestring

DisconnectedSince is when the node last disconnected

last_edge_seq_numinteger

LastEdgeSeqNum Last seq received from edge node

last_heartbeatstring

LastHeartbeat is when the last heartbeat was received

last_orchestrator_seq_numinteger

LastOrchestratorSeqNum Last seq received from orchestrator

messagestring

Message provides additional context about the current state

resource_usage object

ResourceUsage contains the current resource usage metrics (updated with each heartbeat)

cpu_percentnumber

CPUPercent is the CPU usage percentage (0-100)

disk_capacity_bytesinteger

DiskCapacityBytes is the total disk capacity in bytes

disk_percentnumber

DiskPercent is the disk usage percentage (0-100)

disk_used_bytesinteger

DiskUsedBytes is the disk space used in bytes

memory_capacity_bytesinteger

MemoryCapacityBytes is the total available memory in bytes

memory_percentnumber

MemoryPercent is the memory usage percentage (0-100)

memory_used_bytesinteger

MemoryUsedBytes is the memory currently in use in bytes

revisioninteger

Revision is incremented on each update for optimistic concurrency control

session_idstring

SessionID uniquely identifies the current connection session

updated_atstring

UpdatedAt is when the node was last updated

types.NodeStatus
{
  "connected_since": "string",
  "connection_state": "disconnected",
  "created_at": "string",
  "disconnected_since": "string",
  "last_edge_seq_num": 0,
  "last_heartbeat": "string",
  "last_orchestrator_seq_num": 0,
  "message": "string",
  "resource_usage": {
    "cpu_percent": 0,
    "disk_capacity_bytes": 0,
    "disk_percent": 0,
    "disk_used_bytes": 0,
    "memory_capacity_bytes": 0,
    "memory_percent": 0,
    "memory_used_bytes": 0
  },
  "revision": 0,
  "session_id": "string",
  "updated_at": "string"
}