Monitoring

Overview

Monitor your agents through the dashboard or CLI to track performance, debug issues, and optimize execution.

Viewing Logs

Via Dashboard

Go to Runs

Navigate to Agents → my_agent → Runs

Select a run

Click on any run to view details

View logs

See execution timeline, logs, and results

What you’ll see:

Real-time execution logs
Action calls and results
Memory operations
Integration API calls
Errors and warnings
Final result
Execution time

Via CLI

# Stream logs for a specific run
ziet logs run_abc123

# Follow logs in real-time
ziet logs run_abc123 --follow

# View recent logs for an agent
ziet logs my_agent --limit 100

# Filter by level
ziet logs my_agent --level error
ziet logs my_agent --level warning

# Filter by date
ziet logs my_agent --since "1 hour ago"
ziet logs my_agent --since "2024-01-15"

Via API

curl https://api.ziet.ai/runs/run_abc123/logs \
  -H "Authorization: Bearer YOUR_API_KEY"

Response:

{
  "logs": [
    {
      "timestamp": "2024-01-15T10:30:00.123Z",
      "level": "info",
      "message": "Starting agent execution"
    },
    {
      "timestamp": "2024-01-15T10:30:01.456Z",
      "level": "info",
      "message": "Calling action: search_flights"
    },
    {
      "timestamp": "2024-01-15T10:30:05.789Z",
      "level": "info",
      "message": "Memory added: key=search_results"
    }
  ]
}

Metrics

Agent Performance

View metrics in the dashboard for any agent: Execution Metrics:

Average execution time
P50, P95, P99 latency
Success rate
Error rate

Resource Metrics:

Action calls per run
Memory operations (reads/writes)
Integration API calls
Memory usage

Volume Metrics:

Total runs
Runs per day/hour
Active users

Example Dashboard View

my_agent
├── Success Rate: 98.5%
├── Avg Execution Time: 12.3s
├── Total Runs: 1,234
├── Error Rate: 1.5%
└── Last 24h: 87 runs

Run Status

Check Run Status

CLI
API
Python SDK

ziet status run_abc123

Output:

Run: run_abc123
Agent: my_agent
Status: completed
Started: 2024-01-15 10:30:00
Duration: 12.3s
Result: {"flights_found": 42}

curl https://api.ziet.ai/runs/run_abc123/status \
  -H "Authorization: Bearer YOUR_API_KEY"

from ziet import Client

client = Client(api_key="your_key")
status = client.get_run_status("run_abc123")

print(status["status"])  # "running" | "completed" | "failed"

Run Statuses

running - Currently executing
completed - Finished successfully
failed - Encountered an error
cancelled - Manually cancelled
timeout - Exceeded time limit

Recent Runs

List Runs

CLI
Python SDK
Dashboard

# List recent runs
ziet runs my_agent --limit 10

# Filter by status
ziet runs my_agent --status failed
ziet runs my_agent --status completed

# Filter by date
ziet runs my_agent --since "1 day ago"

# List runs
runs = client.list_runs(
    agent_id="my_agent",
    limit=10,
    status="completed"
)

for run in runs:
    print(f"{run['run_id']}: {run['status']}")

Webhooks

Get notified when agents complete or fail.

Setup Webhook

Add webhook in dashboard

Go to Settings → Webhooks
Click Add Webhook
Enter webhook URL
Select events: run.completed, run.failed, run.started
Click Save

Receive webhook

Your endpoint receives POST requests:

{
  "event": "run.completed",
  "run_id": "run_abc123",
  "agent_id": "my_agent",
  "status": "completed",
  "result": {
    "flights_found": 42
  },
  "timestamp": "2024-01-15T10:30:00Z"
}

Verify signature

import hmac
import hashlib

def verify_webhook(payload, signature, secret):
    expected = hmac.new(
        secret.encode(),
        payload.encode(),
        hashlib.sha256
    ).hexdigest()
    
    return hmac.compare_digest(signature, expected)

Webhook Events

run.started - Agent run started
run.completed - Agent run completed successfully
run.failed - Agent run failed
run.cancelled - Agent run was cancelled

Example Webhook Handler

from flask import Flask, request
import hmac
import hashlib

app = Flask(__name__)
WEBHOOK_SECRET = "your_webhook_secret"

@app.route('/webhook', methods=['POST'])
def handle_webhook():
    payload = request.data
    signature = request.headers.get('X-Ziet-Signature')
    
    # Verify signature
    if not verify_signature(payload, signature):
        return 'Invalid signature', 401
    
    data = request.json
    event = data['event']
    
    if event == 'run.completed':
        print(f"Run {data['run_id']} completed!")
        # Process result...
    
    elif event == 'run.failed':
        print(f"Run {data['run_id']} failed!")
        # Send alert...
    
    return 'OK', 200

def verify_signature(payload, signature):
    expected = hmac.new(
        WEBHOOK_SECRET.encode(),
        payload,
        hashlib.sha256
    ).hexdigest()
    return hmac.compare_digest(signature, expected)

Alerts

Email Alerts

Get notified via email when agents fail:

Go to Settings → Alerts
Enable Email Alerts
Select events: run.failed, run.timeout
Add email addresses
Save

Slack Alerts

Send notifications to Slack:

Go to Settings → Integrations → Slack
Connect your Slack workspace
Go to Settings → Alerts
Enable Slack Alerts
Select channel and events
Save

Best Practices

Monitor error rates

Check your agent’s error rate regularly:

# View failed runs
ziet runs my_agent --status failed --limit 10

# Check error logs
ziet logs my_agent --level error

Set up webhooks for critical agents

Get notified immediately when important agents fail:

Settings → Webhooks
Subscribe to run.failed events
Integrate with your alerting system

Review performance metrics

Check execution time trends:

Dashboard → Agents → my_agent → Metrics
Look for sudden increases in execution time
Optimize slow actions

Use log levels appropriately

import logging

logger = logging.getLogger(__name__)

# Info for normal operation
logger.info("Processing started")

# Warning for concerning but non-fatal
logger.warning("Rate limit approaching")

# Error for failures
logger.error("API call failed")

Debugging Failed Runs

View Error Details

# Get run details
ziet status run_abc123

# View full logs
ziet logs run_abc123

# View error logs only
ziet logs run_abc123 --level error

Common Issues

Timeout errors

Cause: Agent exceeded time limitSolution: Increase timeout or optimize actions

@Action(
    id="slow_action",
    name="Slow Action",
    description="...",
    timeout=300  # 5 minutes
)
def slow_action():
    ...

Integration errors

Cause: API call to integration failedSolution: Check logs for API errors, verify API keys

# Check integration status
ziet logs run_abc123 | grep "integration"

Memory errors

Cause: Missing memory keySolution: Ensure actions store data before retrieval

# Store first
memory.add(key="data", value=result)

# Then retrieve
data = memory.get("data")

Next Steps

Deploying

Deploy your agents

Invoking

Run your agents

API Reference

Full API documentation

Memory

Debug memory operations

Getting Started

Agentic

Application

Integrations

Deployment

Overview

Viewing Logs

Via Dashboard

Via CLI

Via API

Metrics

Agent Performance

Example Dashboard View

Run Status

Check Run Status

Run Statuses

Recent Runs

List Runs

Webhooks

Setup Webhook

Webhook Events

Example Webhook Handler

Alerts

Email Alerts

Slack Alerts

Best Practices

Debugging Failed Runs

View Error Details

Common Issues

Next Steps

Deploying

Invoking

API Reference

Memory

​Overview

​Viewing Logs

​Via Dashboard

​Via CLI

​Via API

​Metrics

​Agent Performance

​Example Dashboard View

​Run Status

​Check Run Status

​Run Statuses

​Recent Runs

​List Runs

​Webhooks

​Setup Webhook

​Webhook Events

​Example Webhook Handler

​Alerts

​Email Alerts

​Slack Alerts

​Best Practices

​Debugging Failed Runs

​View Error Details

​Common Issues

​Next Steps

Deploying

Invoking

API Reference

Memory

Overview

Viewing Logs

Via Dashboard

Via CLI

Via API

Metrics

Agent Performance

Example Dashboard View

Run Status

Check Run Status

Run Statuses

Recent Runs

List Runs

Webhooks

Setup Webhook

Webhook Events

Example Webhook Handler

Alerts

Email Alerts

Slack Alerts

Best Practices

Debugging Failed Runs

View Error Details

Common Issues

Next Steps