Home/Agentic AI/Error Recovery/Introduction
←
Previous Module
Workflow Monitoring

Error Recovery Strategies

Build resilient agentic systems that gracefully handle failures and recover intelligently

Your Progress

0 / 5 completed
1
2
3
4
5

Why Error Recovery Matters

In production, failures are inevitable. APIs time out. Networks hiccup. Rate limits hit. Services go down. The difference between a robust system and a fragile one isn't whether errors occur—it's how gracefully you recover from them.

The Reality of Distributed Systems

•APIs fail 0.1-1% of the time even when "healthy"
•Network latency spikes cause unpredictable timeouts
•Rate limits hit during traffic bursts
•Transient errors resolve themselves within seconds

Four Categories of Errors

⏱️

Transient Errors

Temporary issues that resolve on their own. Retry often succeeds.

Examples: Rate limits, temporary service unavailability, network blips
⌛

Timeout Errors

Operation took too long. May be transient or indicate a deeper issue.

Examples: Slow API responses, database query timeouts, network delays
🔒

Permanent Errors

Won't resolve with retries. Requires human intervention or code changes.

Examples: Invalid credentials, resource not found, permission denied
❌

Validation Errors

Input doesn't meet requirements. Fix data, don't retry blindly.

Examples: Invalid format, missing fields, constraint violations

Interactive: Error Classification

Click on different error scenarios to see if they're retryable and explore recovery strategies:

Error Scenarios

💡
Key Principle

Good error recovery isn't about eliminating failures—it's about making them invisible to users. A well-designed system fails gracefully, retries intelligently, and falls back smoothly.