Orchestrator API Endpoints
Complete API reference for AxonFlow Orchestrator - Multi-Agent Parallel execution endpoints.
Overview
The Orchestrator coordinates multi-agent parallel (MAP) execution, allowing multiple agents to process queries simultaneously for significant speedup (up to Nx where N = parallel agents).
Base URL: https://YOUR_ORCHESTRATOR_ENDPOINT
Port: 8081 (default, configurable via PORT env var)
Protocol: HTTP/2 + TLS 1.3
Authentication: License Key (X-License-Key header)
Authentication
All requests require a valid license key in the header:
POST /orchestrator/parallel
Host: YOUR_ORCHESTRATOR_ENDPOINT
Content-Type: application/json
X-License-Key: AXON-V2-xxx-yyy
X-Organization-ID: my-org
Headers:
X-License-Key(required): Your AxonFlow license keyX-Organization-ID(required): Your organization identifierContent-Type(required):application/jsonX-Request-ID(optional): Client-provided request ID for tracing
Endpoints
1. Parallel Query Execution
Execute multiple queries in parallel across multiple agents.
Endpoint: POST /orchestrator/parallel
Request:
{
"queries": [
{
"query": "Search flights from SFO to Paris",
"policy": "package axonflow.policy\ndefault allow = true",
"mcp": {
"connector": "amadeus",
"operation": "search_flights",
"parameters": {
"origin": "SFO",
"destination": "CDG",
"departure_date": "2025-06-01"
}
},
"context": {
"user_id": "user-123",
"query_type": "flights"
}
},
{
"query": "Search hotels in Paris",
"policy": "package axonflow.policy\ndefault allow = true",
"mcp": {
"connector": "amadeus",
"operation": "search_hotels",
"parameters": {
"city": "Paris",
"check_in": "2025-06-01",
"check_out": "2025-06-07"
}
},
"context": {
"user_id": "user-123",
"query_type": "hotels"
}
}
],
"execution_mode": "parallel",
"timeout_ms": 30000
}
Response (200 OK):
{
"results": [
{
"query_index": 0,
"status": "success",
"result": {
"flights": [
{
"airline": "Air France",
"departure": "2025-06-01T10:00:00Z",
"arrival": "2025-06-01T22:00:00Z",
"price": 850,
"currency": "USD"
}
]
},
"metadata": {
"latency_ms": 4,
"policy_decision": "allow",
"agent_id": "agent-3",
"request_id": "req_abc123"
}
},
{
"query_index": 1,
"status": "success",
"result": {
"hotels": [
{
"name": "Hotel Eiffel",
"stars": 4,
"price_per_night": 200,
"currency": "USD"
}
]
},
"metadata": {
"latency_ms": 3,
"policy_decision": "allow",
"agent_id": "agent-1",
"request_id": "req_def456"
}
}
],
"execution_summary": {
"total_queries": 2,
"successful": 2,
"failed": 0,
"total_time_ms": 5234,
"parallel_speedup": "2.3x",
"agent_utilization": {
"agent-1": 1,
"agent-2": 0,
"agent-3": 1,
"agent-4": 0,
"agent-5": 0
}
},
"request_id": "orch_xyz789"
}
Performance:
- Sequential execution: 5s + 5s = 10 seconds
- Parallel execution: max(5s, 5s) = 5.2 seconds
- Speedup: 1.9x
Query Parameters:
| Parameter | Type | Required | Description |
|---|---|---|---|
| queries | array | Yes | Array of query objects |
| execution_mode | string | No | "parallel" (default) or "sequential" |
| timeout_ms | integer | No | Timeout in milliseconds (default: 30000) |
Error Response (400 Bad Request):
{
"error": {
"code": "INVALID_REQUEST",
"message": "Invalid query format",
"details": {
"query_index": 0,
"field": "policy",
"reason": "Policy compilation failed"
},
"request_id": "orch_err123"
}
}
2. Health Check
Check orchestrator service health.
Endpoint: GET /orchestrator/health
Request:
GET /orchestrator/health HTTP/2
Host: YOUR_ORCHESTRATOR_ENDPOINT
Response (200 OK):
{
"status": "healthy",
"version": "1.0.12",
"uptime_seconds": 3600,
"components": {
"database": {
"status": "connected",
"latency_ms": 2
},
"agents": {
"status": "healthy",
"available": 5,
"desired": 5,
"healthy_agents": [
"agent-1",
"agent-2",
"agent-3",
"agent-4",
"agent-5"
]
},
"load_balancer": {
"status": "healthy"
}
},
"timestamp": "2025-11-11T12:00:00Z"
}
Response (503 Service Unavailable):
{
"status": "unhealthy",
"version": "1.0.12",
"components": {
"database": {
"status": "connected"
},
"agents": {
"status": "degraded",
"available": 2,
"desired": 5,
"healthy_agents": [
"agent-1",
"agent-3"
],
"unhealthy_agents": [
"agent-2",
"agent-4",
"agent-5"
]
}
},
"timestamp": "2025-11-11T12:00:00Z"
}
3. Metrics
Get orchestrator performance metrics.
Endpoint: GET /orchestrator/metrics
Request:
GET /orchestrator/metrics HTTP/2
Host: YOUR_ORCHESTRATOR_ENDPOINT
X-License-Key: AXON-V2-xxx-yyy
Response (200 OK):
{
"metrics": {
"requests": {
"total": 10000,
"successful": 9800,
"failed": 200,
"success_rate": 0.98
},
"latency": {
"p50_ms": 2,
"p95_ms": 5,
"p99_ms": 8,
"max_ms": 15
},
"parallel_execution": {
"total_parallel_queries": 5000,
"average_speedup": "3.2x",
"max_speedup_observed": "8.5x"
},
"agent_utilization": {
"agent-1": {
"queries_processed": 2000,
"cpu_percent": 45,
"memory_mb": 512
},
"agent-2": {
"queries_processed": 1950,
"cpu_percent": 43,
"memory_mb": 498
},
"agent-3": {
"queries_processed": 2050,
"cpu_percent": 47,
"memory_mb": 520
},
"agent-4": {
"queries_processed": 2000,
"cpu_percent": 44,
"memory_mb": 505
},
"agent-5": {
"queries_processed": 2000,
"cpu_percent": 46,
"memory_mb": 515
}
},
"timestamp": "2025-11-11T12:00:00Z",
"period_seconds": 3600
}
}
Request/Response Schemas
Query Object Schema
interface QueryRequest {
query: string; // Natural language query
policy: string; // Rego policy content
mcp?: MCPConfig; // MCP connector configuration
llm?: LLMConfig; // LLM configuration
context?: Record<string, any>; // Query context
}
interface MCPConfig {
connector: string; // Connector name (e.g., "salesforce")
operation: string; // Operation name (e.g., "query")
parameters?: Record<string, any>; // Connector-specific parameters
}
interface LLMConfig {
provider: string; // "aws-bedrock" | "openai" | "anthropic"
model: string; // Model identifier
temperature?: number; // 0.0 - 1.0 (default: 0.7)
max_tokens?: number; // Maximum response tokens (default: 500)
}
Response Object Schema
interface ParallelExecutionResponse {
results: QueryResult[];
execution_summary: ExecutionSummary;
request_id: string;
}
interface QueryResult {
query_index: number;
status: "success" | "error";
result?: any;
error?: ErrorDetails;
metadata: QueryMetadata;
}
interface QueryMetadata {
latency_ms: number;
policy_decision: "allow" | "deny";
agent_id: string;
request_id: string;
timestamp?: string;
}
interface ExecutionSummary {
total_queries: number;
successful: number;
failed: number;
total_time_ms: number;
parallel_speedup: string;
agent_utilization: Record<string, number>;
}
Error Codes
Orchestrator-Specific Errors
| Code | HTTP Status | Description | Retry? |
|---|---|---|---|
ORCHESTRATOR_UNAVAILABLE | 503 | All agents unhealthy | Yes |
INSUFFICIENT_AGENTS | 503 | Not enough agents for parallel execution | Yes |
PARALLEL_EXECUTION_FAILED | 500 | Parallel execution error | Yes |
QUERY_TIMEOUT | 504 | Query exceeded timeout | Maybe |
AGENT_COMMUNICATION_ERROR | 502 | Cannot reach agent | Yes |
Example Error Response
{
"error": {
"code": "INSUFFICIENT_AGENTS",
"message": "Not enough healthy agents for parallel execution",
"details": {
"required_agents": 5,
"available_agents": 2,
"healthy_agents": ["agent-1", "agent-3"],
"unhealthy_agents": ["agent-2", "agent-4", "agent-5"]
},
"request_id": "orch_err456",
"timestamp": "2025-11-11T12:00:00Z"
}
}
Rate Limiting
Orchestrator applies the same rate limits as Agent endpoints:
Limits:
- 100 requests/minute per organization
- 10,000 requests/hour per organization
- Parallel queries count as 1 request
Headers:
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 95
X-RateLimit-Reset: 1699711200
Rate Limit Exceeded (429):
{
"error": {
"code": "RATE_LIMIT_EXCEEDED",
"message": "Organization rate limit exceeded",
"details": {
"limit": 100,
"period": "1 minute",
"reset_at": "2025-11-11T12:01:00Z"
},
"request_id": "orch_err789"
}
}
Best Practices
1. Optimal Parallel Execution
// ✅ Good: 5 queries in parallel (matches 5 agents)
const response = await client.executeParallel([
{ query: 'Query 1', policy },
{ query: 'Query 2', policy },
{ query: 'Query 3', policy },
{ query: 'Query 4', policy },
{ query: 'Query 5', policy }
]);
// ❌ Suboptimal: 10 queries (only 5 agents available)
// Some queries will wait for agents to become available
const response = await client.executeParallel([
...tenQueries // Will execute in batches of 5
]);
Recommendation: Match parallel query count to available agents for best performance.
2. Timeout Configuration
// Short queries: 10 seconds
const response = await client.executeParallel(queries, {
timeout_ms: 10000
});
// LLM queries: 30 seconds
const response = await client.executeParallel(llmQueries, {
timeout_ms: 30000
});
// Complex data queries: 60 seconds
const response = await client.executeParallel(complexQueries, {
timeout_ms: 60000
});
3. Error Handling
const response = await client.executeParallel(queries);
// Check each result
response.results.forEach((result, index) => {
if (result.status === 'error') {
console.error(`Query ${index} failed:`, result.error);
// Handle error for this specific query
} else {
console.log(`Query ${index} succeeded:`, result.result);
}
});
// Check overall success rate
const successRate = response.execution_summary.successful /
response.execution_summary.total_queries;
if (successRate < 0.8) {
console.warn('Success rate below 80% - investigate issues');
}
4. Agent Utilization Monitoring
// Get metrics after execution
const metrics = await client.getOrchestratorMetrics();
// Check agent balance
const utilization = metrics.agent_utilization;
const avgQueries = Object.values(utilization)
.reduce((sum, count) => sum + count, 0) / Object.keys(utilization).length;
Object.entries(utilization).forEach(([agent, queries]) => {
if (queries < avgQueries * 0.8) {
console.warn(`${agent} underutilized: ${queries} queries (avg: ${avgQueries})`);
}
});
Performance Optimization
Parallel Speedup Formula
Speedup = Sequential Time / Parallel Time
Example:
- 5 queries × 5 seconds each = 25 seconds (sequential)
- max(5s, 5s, 5s, 5s, 5s) = 5 seconds (parallel)
- Speedup = 25s / 5s = 5x
Theoretical vs Actual Speedup
| Queries | Agents | Theoretical | Actual | Efficiency |
|---|---|---|---|---|
| 2 | 5 | 2.0x | 1.9x | 95% |
| 5 | 5 | 5.0x | 4.5x | 90% |
| 10 | 5 | 2.0x | 1.8x | 90% |
| 20 | 5 | 4.0x | 3.5x | 88% |
Note: Overhead from orchestration reduces actual speedup by ~10%.
SDK Support
TypeScript
import { AxonFlowClient } from '@axonflow/sdk';
const client = new AxonFlowClient({
endpoint: process.env.AXONFLOW_ENDPOINT,
licenseKey: process.env.AXONFLOW_LICENSE_KEY,
organizationId: 'my-org'
});
// Parallel execution
const response = await client.executeParallel([
{ query: 'Query 1', policy: policyContent },
{ query: 'Query 2', policy: policyContent }
]);
Go
import "github.com/getaxonflow/axonflow-sdk-go"
client, _ := axonflow.NewClient(axonflow.Config{
Endpoint: os.Getenv("AXONFLOW_ENDPOINT"),
LicenseKey: os.Getenv("AXONFLOW_LICENSE_KEY"),
OrganizationID: "my-org",
})
// Parallel execution
responses, err := client.ExecuteParallel(ctx, []*axonflow.QueryRequest{
{Query: "Query 1", Policy: policyContent},
{Query: "Query 2", Policy: policyContent},
})
Monitoring
CloudWatch Metrics
Available Metrics:
orchestrator.requests.total- Total requestsorchestrator.requests.parallel- Parallel execution requestsorchestrator.latency.p95- 95th percentile latencyorchestrator.errors.rate- Error rateorchestrator.agents.available- Available agent countorchestrator.speedup.average- Average parallel speedup
CloudWatch Logs
Log Group: /ecs/YOUR-STACK-NAME/orchestrator
Example Log Entry:
{
"timestamp": "2025-11-11T12:00:00Z",
"level": "info",
"message": "Parallel execution completed",
"queries": 5,
"successful": 5,
"failed": 0,
"total_time_ms": 5234,
"speedup": "4.5x",
"agent_utilization": {
"agent-1": 1,
"agent-2": 1,
"agent-3": 1,
"agent-4": 1,
"agent-5": 1
},
"request_id": "orch_abc123"
}
Additional Resources
- Agent Endpoints - Agent API reference
- Error Codes - Complete error reference
- Workflow Examples - MAP execution examples
- SDK Documentation - SDK usage
Support
Questions about Orchestrator API?
- Email: [email protected]
- Documentation: https://docs.getaxonflow.com
- API Status: https://status.getaxonflow.com
API Version: 1.0.12 Last Updated: November 11, 2025