Graph Ingestion

Graph Ingestion enables you to populate the context graph with custom data from your infrastructure, applications, and integrations. Import nodes and relationships in single or batch operations.

Overview

The Ingestion Service provides APIs to load data into the context graph:

Ingest Nodes: Add individual or batches of nodes (up to 1000 per batch)
Ingest Relationships: Create connections between nodes
Duplicate Handling: Control how duplicates are managed (error, skip, update, merge)
Transactional Mode: All-or-nothing batch operations
Dataset Association: Organize ingested data into logical datasets

Use batch operations for importing large amounts of data efficiently. Batch ingestion is significantly faster than individual imports.

Quick Start

from kubiya import ControlPlaneClient

# Initialize the client
client = ControlPlaneClient(api_key="your-api-key")

# Ingest a single node
result = client.ingestion.ingest_node(
    id="server-01",
    labels=["Server", "Production"],
    properties={
        "name": "prod-web-01",
        "ip": "10.0.1.10",
        "region": "us-east-1"
    },
    duplicate_handling="skip"
)

# Ingest nodes in batch
batch_result = client.ingestion.ingest_nodes_batch(
    nodes=[
        {
            "id": "server-02",
            "labels": ["Server"],
            "properties": {"name": "prod-web-02"}
        },
        {
            "id": "server-03",
            "labels": ["Server"],
            "properties": {"name": "prod-web-03"}
        }
    ]
)

print(f"Batch: {batch_result['summary']['success']} succeeded")

Core Concepts

Nodes

Nodes represent entities in the graph:

ID: Unique identifier (string)
Labels: Categories/types (e.g., [“Server”, “AWS”])
Properties: Key-value attributes

Relationships

Relationships connect nodes:

Source ID: Starting node
Target ID: Ending node
Relationship Type: Connection type (e.g., “CONNECTS_TO”)
Properties: Optional relationship metadata

Duplicate Handling Strategies

error: Fail if node exists (default)
skip: Ignore if exists, continue
update: Replace existing node
merge: Merge properties with existing

Transactional Mode

true: Roll back all if any operation fails
false: Process individually, some may succeed

Basic Usage

Ingest Single Node

from kubiya import ControlPlaneClient

client = ControlPlaneClient(api_key="your-api-key")

# Ingest node with duplicate handling
result = client.ingestion.ingest_node(
    id="db-prod-01",
    labels=["Database", "PostgreSQL", "Production"],
    properties={
        "name": "production-db",
        "version": "14.5",
        "size": "db.r5.xlarge",
        "region": "us-east-1",
        "multi_az": True
    },
    duplicate_handling="skip"
)

print(f"Success: {result['success']}")
print(f"Node ID: {result['node_id']}")
print(f"Created: {result['created']}")

Example Response

{
  "success": true,
  "node_id": "db-prod-01",
  "created": true,
  "message": "Node ingested successfully"
}

Ingest Node with Dataset

from kubiya import ControlPlaneClient

client = ControlPlaneClient(api_key="your-api-key")

# Associate with dataset for organization
result = client.ingestion.ingest_node(
    id="app-service-01",
    labels=["Service", "Application"],
    properties={"name": "auth-service", "port": 8080},
    dataset_id="production-infrastructure",
    duplicate_handling="update"
)

Ingest Nodes in Batch

from kubiya import ControlPlaneClient

client = ControlPlaneClient(api_key="your-api-key")

# Prepare batch of nodes
nodes = [
    {
        "id": "server-001",
        "labels": ["Server", "AWS", "EC2"],
        "properties": {
            "name": "web-server-01",
            "instance_type": "t3.medium",
            "region": "us-east-1"
        }
    },
    {
        "id": "server-002",
        "labels": ["Server", "AWS", "EC2"],
        "properties": {
            "name": "web-server-02",
            "instance_type": "t3.medium",
            "region": "us-west-2"
        }
    },
    {
        "id": "lb-001",
        "labels": ["LoadBalancer", "AWS", "ALB"],
        "properties": {
            "name": "prod-alb",
            "type": "application",
            "scheme": "internet-facing"
        }
    }
]

# Batch ingest with options
result = client.ingestion.ingest_nodes_batch(
    nodes=nodes,
    duplicate_handling="skip",
    transactional=False  # Continue even if some fail
)

# Review results
print(f"Total: {result['summary']['total']}")
print(f"Success: {result['summary']['success']}")
print(f"Failed: {result['summary']['failed']}")
print(f"Skipped: {result['summary']['skipped']}")

if result.get('errors'):
    print("\nErrors:")
    for error in result['errors']:
        print(f"  - {error}")

Example Response

{
  "summary": {
    "total": 3,
    "success": 3,
    "failed": 0,
    "skipped": 0
  },
  "results": [
    {
      "node_id": "server-001",
      "success": true,
      "created": true
    },
    {
      "node_id": "server-002",
      "success": true,
      "created": true
    },
    {
      "node_id": "lb-001",
      "success": true,
      "created": true
    }
  ],
  "errors": []
}

Ingest Single Relationship

from kubiya import ControlPlaneClient

client = ControlPlaneClient(api_key="your-api-key")

# Create relationship between nodes
result = client.ingestion.ingest_relationship(
    source_id="server-001",
    target_id="db-prod-01",
    relationship_type="CONNECTS_TO",
    properties={
        "port": 5432,
        "protocol": "postgres",
        "connection_pool": 20
    }
)

print(f"Success: {result['success']}")
print(f"Relationship ID: {result['relationship_id']}")

Example Response

{
  "success": true,
  "relationship_id": "rel-abc123",
  "created": true
}

Ingest Relationships in Batch

from kubiya import ControlPlaneClient

client = ControlPlaneClient(api_key="your-api-key")

# Prepare batch of relationships
relationships = [
    {
        "source_id": "lb-001",
        "target_id": "server-001",
        "relationship_type": "ROUTES_TO",
        "properties": {"weight": 50}
    },
    {
        "source_id": "lb-001",
        "target_id": "server-002",
        "relationship_type": "ROUTES_TO",
        "properties": {"weight": 50}
    },
    {
        "source_id": "server-001",
        "target_id": "db-prod-01",
        "relationship_type": "CONNECTS_TO",
        "properties": {"port": 5432}
    }
]

# Batch ingest relationships
result = client.ingestion.ingest_relationships_batch(
    relationships=relationships,
    skip_missing_nodes=False,  # Fail if nodes don't exist
    transactional=True  # All or nothing
)

print(f"Success: {result['summary']['success']}/{result['summary']['total']}")

Practical Examples

1. Import AWS Infrastructure

Import AWS resources into the graph:

from kubiya import ControlPlaneClient
import boto3

def import_aws_infrastructure(client: ControlPlaneClient, region: str = "us-east-1"):
    """Import AWS EC2 instances and relationships."""

    # Initialize AWS client
    ec2 = boto3.client('ec2', region_name=region)

    # Fetch instances
    response = ec2.describe_instances()

    nodes = []
    relationships = []

    for reservation in response['Reservations']:
        vpc_id = reservation['Instances'][0].get('VpcId')

        for instance in reservation['Instances']:
            # Create node for instance
            nodes.append({
                "id": instance['InstanceId'],
                "labels": ["EC2Instance", "AWS", "Compute"],
                "properties": {
                    "name": next((tag['Value'] for tag in instance.get('Tags', []) if tag['Key'] == 'Name'), instance['InstanceId']),
                    "instance_type": instance['InstanceType'],
                    "state": instance['State']['Name'],
                    "region": region,
                    "availability_zone": instance['Placement']['AvailabilityZone'],
                    "private_ip": instance.get('PrivateIpAddress'),
                    "public_ip": instance.get('PublicIpAddress')
                }
            })

            # Create relationship to VPC
            if vpc_id:
                relationships.append({
                    "source_id": instance['InstanceId'],
                    "target_id": vpc_id,
                    "relationship_type": "RUNS_IN",
                    "properties": {}
                })

    # Ingest nodes in batch
    print(f"Ingesting {len(nodes)} EC2 instances...")
    node_result = client.ingestion.ingest_nodes_batch(
        nodes=nodes,
        dataset_id="aws-infrastructure",
        duplicate_handling="update"
    )

    print(f"✅ Nodes: {node_result['summary']['success']}/{node_result['summary']['total']}")

    # Ingest relationships
    if relationships:
        print(f"Creating {len(relationships)} relationships...")
        rel_result = client.ingestion.ingest_relationships_batch(
            relationships=relationships,
            skip_missing_nodes=True
        )

        print(f"✅ Relationships: {rel_result['summary']['success']}/{rel_result['summary']['total']}")

    return node_result

# Usage
client = ControlPlaneClient(api_key="your-api-key")
result = import_aws_infrastructure(client, region="us-east-1")

2. Import Kubernetes Resources

Import Kubernetes cluster data:

from kubiya import ControlPlaneClient
from kubernetes import client as k8s_client, config

def import_kubernetes_cluster(cp_client: ControlPlaneClient, cluster_name: str):
    """Import Kubernetes deployments and services."""

    # Load kubeconfig
    config.load_kube_config()
    v1 = k8s_client.CoreV1Api()
    apps_v1 = k8s_client.AppsV1Api()

    nodes = []
    relationships = []

    # Import deployments
    deployments = apps_v1.list_deployment_for_all_namespaces()

    for dep in deployments.items:
        deployment_id = f"{dep.metadata.namespace}/{dep.metadata.name}"

        nodes.append({
            "id": deployment_id,
            "labels": ["Deployment", "Kubernetes"],
            "properties": {
                "name": dep.metadata.name,
                "namespace": dep.metadata.namespace,
                "replicas": dep.spec.replicas,
                "cluster": cluster_name,
                "image": dep.spec.template.spec.containers[0].image if dep.spec.template.spec.containers else None
            }
        })

    # Import services
    services = v1.list_service_for_all_namespaces()

    for svc in services.items:
        service_id = f"{svc.metadata.namespace}/{svc.metadata.name}"

        nodes.append({
            "id": service_id,
            "labels": ["Service", "Kubernetes"],
            "properties": {
                "name": svc.metadata.name,
                "namespace": svc.metadata.namespace,
                "type": svc.spec.type,
                "cluster": cluster_name,
                "ports": [p.port for p in svc.spec.ports] if svc.spec.ports else []
            }
        })

        # Create relationships between services and deployments
        if svc.spec.selector:
            for dep in deployments.items:
                if dep.metadata.namespace == svc.metadata.namespace:
                    deployment_id = f"{dep.metadata.namespace}/{dep.metadata.name}"

                    relationships.append({
                        "source_id": service_id,
                        "target_id": deployment_id,
                        "relationship_type": "ROUTES_TO",
                        "properties": {"selector": svc.spec.selector}
                    })

    # Batch ingest
    print(f"Ingesting {len(nodes)} Kubernetes resources...")
    node_result = cp_client.ingestion.ingest_nodes_batch(
        nodes=nodes,
        dataset_id=f"k8s-{cluster_name}",
        duplicate_handling="update"
    )

    print(f"✅ Nodes: {node_result['summary']['success']}/{node_result['summary']['total']}")

    if relationships:
        rel_result = cp_client.ingestion.ingest_relationships_batch(
            relationships=relationships,
            skip_missing_nodes=True
        )

        print(f"✅ Relationships: {rel_result['summary']['success']}/{rel_result['summary']['total']}")

    return node_result

# Usage
client = ControlPlaneClient(api_key="your-api-key")
result = import_kubernetes_cluster(client, cluster_name="prod-cluster")

3. Import Service Dependencies

Import application service dependencies:

from kubiya import ControlPlaneClient
import yaml

def import_service_dependencies(client: ControlPlaneClient, dependency_file: str):
    """Import service dependencies from YAML file."""

    # Load dependency configuration
    with open(dependency_file, 'r') as f:
        config = yaml.safe_load(f)

    nodes = []
    relationships = []

    # Create nodes for services
    for service in config['services']:
        nodes.append({
            "id": service['name'],
            "labels": ["Service", "Application"],
            "properties": {
                "name": service['name'],
                "type": service.get('type', 'unknown'),
                "owner": service.get('owner'),
                "repository": service.get('repository'),
                "environment": service.get('environment', 'production')
            }
        })

        # Create dependency relationships
        for dep in service.get('dependencies', []):
            relationships.append({
                "source_id": service['name'],
                "target_id": dep['name'],
                "relationship_type": "DEPENDS_ON",
                "properties": {
                    "type": dep.get('type', 'api'),
                    "required": dep.get('required', True)
                }
            })

    # Batch ingest
    print(f"Ingesting {len(nodes)} services...")
    node_result = client.ingestion.ingest_nodes_batch(
        nodes=nodes,
        dataset_id="service-catalog",
        duplicate_handling="merge"
    )

    print(f"✅ Services: {node_result['summary']['success']}/{node_result['summary']['total']}")

    if relationships:
        print(f"Creating {len(relationships)} dependencies...")
        rel_result = client.ingestion.ingest_relationships_batch(
            relationships=relationships
        )

        print(f"✅ Dependencies: {rel_result['summary']['success']}/{rel_result['summary']['total']}")

    return node_result

# Usage
client = ControlPlaneClient(api_key="your-api-key")
result = import_service_dependencies(client, "services.yaml")

Example services.yaml:

services:
  - name: auth-service
    type: api
    owner: platform-team
    repository: github.com/company/auth-service
    dependencies:
      - name: user-database
        type: database
        required: true
      - name: redis-cache
        type: cache
        required: false

  - name: api-gateway
    type: gateway
    owner: platform-team
    dependencies:
      - name: auth-service
        type: api
        required: true

4. Sync from External System

Continuously sync data from external system:

from kubiya import ControlPlaneClient
import time

class GraphSyncer:
    """Sync external data to context graph."""

    def __init__(self, client: ControlPlaneClient, dataset_id: str):
        self.client = client
        self.dataset_id = dataset_id

    def sync_resources(self, resources: list):
        """Sync a batch of resources."""

        nodes = []

        for resource in resources:
            nodes.append({
                "id": resource['id'],
                "labels": resource['labels'],
                "properties": resource['properties']
            })

        # Use update strategy to keep data fresh
        result = self.client.ingestion.ingest_nodes_batch(
            nodes=nodes,
            dataset_id=self.dataset_id,
            duplicate_handling="update",
            transactional=False
        )

        return result

    def continuous_sync(self, fetch_func, interval_seconds: int = 300):
        """Continuously sync data at intervals."""

        print(f"Starting continuous sync (interval: {interval_seconds}s)")

        while True:
            try:
                # Fetch latest data
                resources = fetch_func()

                # Sync to graph
                result = self.sync_resources(resources)

                print(f"✅ Synced {result['summary']['success']}/{result['summary']['total']} resources")

                # Wait before next sync
                time.sleep(interval_seconds)

            except Exception as e:
                print(f"❌ Sync failed: {e}")
                time.sleep(60)  # Wait 1 minute on error

# Usage
client = ControlPlaneClient(api_key="your-api-key")
syncer = GraphSyncer(client, dataset_id="external-system")

def fetch_external_resources():
    """Fetch resources from external system."""
    # Your external API call here
    return []

# Start continuous sync
# syncer.continuous_sync(fetch_external_resources, interval_seconds=300)

Error Handling

from kubiya import ControlPlaneClient
from kubiya.resources.exceptions import GraphError

client = ControlPlaneClient(api_key="your-api-key")

# Handle validation errors
try:
    result = client.ingestion.ingest_node(
        id="",  # Empty ID - invalid
        labels=[],  # Empty labels - invalid
        properties={}
    )
except GraphError as e:
    print(f"Validation failed: {e}")

# Handle batch errors
result = client.ingestion.ingest_nodes_batch(
    nodes=[...],
    transactional=False
)

if result['summary']['failed'] > 0:
    print(f"Some imports failed:")
    for error in result.get('errors', []):
        print(f"  - {error}")

# Handle missing nodes in relationships
try:
    result = client.ingestion.ingest_relationship(
        source_id="non-existent-node",
        target_id="another-missing-node",
        relationship_type="CONNECTS_TO"
    )
except GraphError as e:
    if "not found" in str(e).lower():
        print("Source or target node doesn't exist")

Best Practices

1. Use Batch Operations

# ❌ BAD - Individual imports in loop
for node in nodes:
    client.ingestion.ingest_node(
        id=node['id'],
        labels=node['labels'],
        properties=node['properties']
    )

# ✅ GOOD - Batch import
client.ingestion.ingest_nodes_batch(nodes=nodes)

2. Choose Appropriate Duplicate Handling

# Initial import - fail on duplicates
client.ingestion.ingest_nodes_batch(
    nodes=nodes,
    duplicate_handling="error"
)

# Sync/Update - skip or update
client.ingestion.ingest_nodes_batch(
    nodes=nodes,
    duplicate_handling="update"  # or "skip"
)

3. Use Datasets for Organization

# Organize by source/purpose
client.ingestion.ingest_nodes_batch(
    nodes=aws_nodes,
    dataset_id="aws-infrastructure"
)

client.ingestion.ingest_nodes_batch(
    nodes=k8s_nodes,
    dataset_id="kubernetes-cluster"
)

4. Handle Large Imports

def chunked_import(client, nodes, chunk_size=1000):
    """Import large datasets in chunks."""

    for i in range(0, len(nodes), chunk_size):
        chunk = nodes[i:i + chunk_size]

        result = client.ingestion.ingest_nodes_batch(
            nodes=chunk,
            duplicate_handling="skip",
            transactional=False
        )

        print(f"Chunk {i // chunk_size + 1}: {result['summary']['success']} succeeded")

API Reference

Node Ingestion Methods

Method	Description	Parameters	Returns
`ingest_node()`	Ingest single node	`id`, `labels`, `properties`, `dataset_id`, `duplicate_handling`	`Dict`
`ingest_nodes_batch()`	Ingest multiple nodes	`nodes`, `dataset_id`, `duplicate_handling`, `transactional`	`Dict` with summary

Relationship Ingestion Methods

Method	Description	Parameters	Returns
`ingest_relationship()`	Ingest single relationship	`source_id`, `target_id`, `relationship_type`, `properties`, `dataset_id`	`Dict`
`ingest_relationships_batch()`	Ingest multiple relationships	`relationships`, `dataset_id`, `skip_missing_nodes`, `transactional`	`Dict` with summary

Batch Response Structure

{
    "summary": {
        "total": int,
        "success": int,
        "failed": int,
        "skipped": int
    },
    "results": List[Dict],
    "errors": List[Dict]
}

Next Steps

Datasets

Manage cognitive datasets

Context Graph

Query and explore the graph

Intelligent Search

AI-powered graph search

Best Practices

SDK best practices guide

​Overview

​Quick Start

​Core Concepts

​Nodes

​Relationships

​Duplicate Handling Strategies

​Transactional Mode

​Basic Usage

​Ingest Single Node

​Ingest Node with Dataset

​Ingest Nodes in Batch

​Ingest Single Relationship

​Ingest Relationships in Batch

​Practical Examples

​1. Import AWS Infrastructure

​2. Import Kubernetes Resources

​3. Import Service Dependencies

​4. Sync from External System

​Error Handling

​Best Practices

​1. Use Batch Operations

​2. Choose Appropriate Duplicate Handling

​3. Use Datasets for Organization

​4. Handle Large Imports

​API Reference

​Node Ingestion Methods

​Relationship Ingestion Methods

​Batch Response Structure

​Next Steps

Datasets

Context Graph

Intelligent Search

Best Practices

Overview

Quick Start

Core Concepts

Nodes

Relationships

Duplicate Handling Strategies

Transactional Mode

Basic Usage

Ingest Single Node

Ingest Node with Dataset

Ingest Nodes in Batch

Ingest Single Relationship

Ingest Relationships in Batch

Practical Examples

1. Import AWS Infrastructure

2. Import Kubernetes Resources

3. Import Service Dependencies

4. Sync from External System

Error Handling

Best Practices

1. Use Batch Operations

2. Choose Appropriate Duplicate Handling

3. Use Datasets for Organization

4. Handle Large Imports

API Reference

Node Ingestion Methods

Relationship Ingestion Methods

Batch Response Structure

Next Steps