Debugging Customer API Issues

Scenario: A customer reports errors with your API. You need to investigate, identify the root cause, and provide them with transparency.

Features Used:

• Requests Dashboard
• Customer Dashboard
• Observability as a Service

Overview

When customers report API integration issues, you need to quickly:

1. Find their specific requests in your system
2. Analyze what went wrong
3. Understand their usage patterns
4. Empower them with self-service debugging tools

This workflow shows you how to use Treblle’s features together to efficiently debug customer issues while maintaining transparency.

Step 1: Identify the Customer’s Requests

When a customer reports an API error, start by filtering their requests in the Requests dashboard.

Navigate to Requests

1. Go to your API dashboard
2. Click Requests in the left navigation bar

Filter by Customer

1. Click the Filter button at the top of the requests list
2. Select User Information from the filter options
3. In the search field, enter the customer’s identifier:
   • Email address
   • Customer ID
   • Company name
   • Username

Review Request Patterns

Once filtered, look for:

• Error patterns: Multiple 4xx or 5xx responses
• Time clustering: Errors occurring at specific times
• Endpoint patterns: Issues with particular endpoints
• Frequency: How often errors occur vs. successful requests

In this example, we can see requests filtered by:

• Response code: 4xx (client errors)
• Response code: 5xx (server errors)
• Device: Android
• Customer: Microsoft

This gives us a focused view of problematic requests from this specific customer.

Step 2: Analyze Request Details

Click on any failed request to dig into the details.

Access Request Information

1. Click on a request with a 4xx or 5xx status code
2. The request details panel opens on the right side

Review the General Tab

The General tab shows the complete request/response cycle:

In this view, you can see:

• POST request to /auth/register endpoint
• 400 response code indicating a client error
• Load time: 24.54ms
• Response size: 0.17kb
• Complete request and response bodies for debugging

Check Security Status

1. Switch to the Security tab
2. Review the threat level assessment
3. Check for:
   • Authentication issues
   • Suspicious IP addresses
   • Rate limiting violations
   • SQL injection attempts

The Security tab shows:

• Security Audit breakdown with pass/fail percentages
• Threat categorization by impact level (High, Medium, Low)
• Specific security checks like API10 (Unsafe Consumption of APIs), API2 (Broken Authentication), etc.
• Impact assessment for each security issue

In this example, we can see:

• 61% of checks failed
• 39% passed
• 1 High impact threat
• 1 Medium impact threat
• 6 Low impact threats

Review Additional Context

1. Click the Info tab to see:

   • Customer’s device type
   • Geographic location
   • IP address
   • User agent information

2. Click the Metadata tab to see business context:

   • Customer ID
   • Plan tier
   • Custom business context
   • Environment information

The Metadata tab reveals critical business context:

• Customer: Microsoft
• Trace ID: 0pqS0xvax9 (for distributed tracing)
• Plan: Platinum Plan
• Region: US

Step 3: Track Customer’s API Usage History

Get the full picture of the customer’s integration health.

Navigate to Customer Dashboard

1. Click Customers in the left navigation bar
2. Use the search bar to find the specific customer
3. Click on their name to open their profile

The Customer Dashboard shows all customers in your system with key metrics:

• New Customers: 36
• Active Customers: 36
• Top Customer: Adobe (9.03% of traffic)
• Average Requests: 43.4K per customer

You can see a list of your top customers including Adobe, Netflix, Meta, Microsoft, Amazon, Apple, Google, Walmart, and Tesla.

Analyze Usage Patterns

Click on a specific customer (like Microsoft) to see their detailed profile:

The individual customer view displays:

• Total Requests: 12.0K
• Overall Percentage: 9.21% of all requests
• Request graph showing traffic trends over the selected time period
• Recent requests table with full details

Request History Table shows:

• HTTP Method (GET, POST, etc.)
• Response codes
• Endpoint names
• Load times
• Threat levels
• Device types
• AI Agent detection
• Geographic locations
• Timestamps

Identify Trends

Look for these patterns:

Step 4: Provide Self-Service Debugging Access

Empower customers to debug their own integrations with Observability as a Service.

Understanding Observability as a Service

Treblle’s Observability as a Service feature allows you to embed API request logs directly into your developer portal. Customers see only their own requests - nothing from other customers.

What Customers See

When customers access the embedded Observability portal, they can:

Monitor Real-Time:

• Live view of their API requests
• Request/response data for debugging
• Error messages and stack traces
• Performance metrics (load times)

The embedded portal shows:

• Total Requests: 18,707 for this customer
• Filter options to narrow down specific issues
• Sort capabilities to organize data
• Search functionality to find specific requests
• Open in Treblle button for deeper analysis
• Pagination through large request volumes

Filter and Search:

• By timeframe (last 24 hours, 7 days, custom)
• By HTTP method (GET, POST, etc.)
• By response code (success vs. errors)
• By specific endpoint

The detailed view shows each request with:

• HTTP method and response code
• Customer identifier (Amazon, andy, J.P. Morgan, Apple)
• Trace IDs for distributed tracing
• Response sizes
• Load times
• Device types (desktop, android, mobile)
• Geographic locations
• Threat levels
• Request bodies (with sensitive data masked)

Debug Independently:

• Identify malformed requests
• Verify authentication headers
• Check request payloads
• Understand error responses

Benefits for Support Teams

Embedding Observability as a Service reduces support burden:

• Fewer tickets: Customers self-serve for common issues
• Faster resolution: When customers do reach out, they’ve already investigated
• Better communication: Shared visibility into the same request data
• Trust building: Transparency shows you’re committed to their success

Workflow Summary

Here’s the complete debugging workflow at a glance:

Next Steps

Now that you’ve mastered debugging customer issues:

• Set up alerts: Create Custom Alerts for high error rates from specific customers
• Improve documentation: Update API docs based on common support issues you discover
• Automate responses: Build a knowledge base with common issues and solutions
• Train your team: Share this workflow with other support engineers
• Monitor proactively: Review the Customer Dashboard daily to catch issues before customers report them