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Getting Started

This guide will help you set up Autoheal and run your first AI-powered incident investigation.

Prerequisites​

Before you begin, ensure you have:

  • An Autoheal account (contact support@autoheal.ai for access)
  • Admin role in your organization
  • Credentials for at least one observability tool (Datadog, Grafana, etc.)

Step 1: Log In to Autoheal​

1
Access the Dashboard

Navigate to your Autoheal instance URL (e.g., https://<tenant>.autoheal.ai) and click Log In.

2
Authenticate

Sign in using your Email / Password or your organization's SSO provider.

Step 2: Connect Your First Integration​

Integrations allow the AI agent to query your observability tools. Let's connect your first one.

1
Navigate to Integrations

From the sidebar, click Integrations.

2
Choose an Integration

Select the integration you want to connect. We recommend starting with your primary monitoring tool (e.g., Datadog, Grafana).

3
Enter Credentials

Provide the required API credentials. See Integrations for detailed instructions for each integration.

tip

Start with an observability tool as your first integration - they provide the richest context for incident investigation.

Step 3: Set Up Your Knowledge Base​

The Knowledge Base stores runbooks, procedures, and learnings that the AI agent can reference during investigations.

1
Navigate to Knowledge Base

From the sidebar, click Knowledge.

2
Create Your First Runbook

Click New Document and select Runbook as the template.

3
Add Content

Document a common incident type your team handles. Include:

  • Symptoms and how to identify the issue
  • Step-by-step remediation procedures
  • Escalation paths if needed
4
Save and Publish

Save your runbook. It's now available to the AI agent.

Step 4: Start an Investigation​

Now you're ready to use the AI OnCall Agent!

1
Open the Investigations Panel

From the sidebar, click Investigations.

2
Describe the Issue

Type a description of the incident you want to investigate. For example:

High latency alerts firing on the checkout service.
Started around 2:30 PM UTC.
3
Let the Agent Investigate

The AI agent will:

  • Query your connected integrations for relevant data
  • Search your knowledge base for related runbooks
  • Analyze patterns and correlations
  • Present findings and recommendations
4
Follow Up

Ask follow-up questions to dive deeper:

Can you check the database metrics during that time?
Are there any similar incidents in the past week?

Example Investigation​

Here's what a typical investigation looks like:

User Query

"We're seeing 5xx errors spike on the payment service. Can you investigate?"

Agent Response

The agent will:

  1. Query Datadog/Grafana for error rates and latency metrics
  2. Pull recent logs from the payment service
  3. Check for recent deployments or changes
  4. Search the knowledge base for payment service runbooks
  5. Present a summary with potential root causes
Follow-up Questions

You can then ask:

  • "What changed in the last deployment?"
  • "Show me the database connection pool metrics"
  • "Are other services affected?"

Next Steps​

Connect More Integrations

Add more observability tools for richer investigations.

Build Your Knowledge Base

Document your runbooks and procedures.

Invite Team Members

Add your team and configure permissions.

Explore Integrations

See all available integrations.

Getting Help​

note

Need assistance? Contact our support team at support@autoheal.ai or check the detailed guides in this documentation.