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Error Handling

基础设施

3 分钟阅读

什么是 Error Handling？

Error handling is the practice of anticipating, detecting, and responding to errors in software execution, including catching exceptions, logging failures, and implementing fallback logic to keep automated workflows running reliably.

What is Error Handling?

Error handling encompasses all the techniques and patterns used to detect, respond to, and recover from errors during program execution. In automation, robust error handling means the difference between a workflow that silently breaks and one that adapts, retries, logs the issue, and alerts the operator.

Types of Errors in Automation

Automated workflows encounter several categories of errors:

  • Network errors — Timeouts, DNS failures, connection resets, SSL certificate issues.
  • Application errors — HTTP 4xx/5xx responses, malformed API responses, unexpected page structures.
  • Data errors — Missing fields, type mismatches, validation failures, encoding issues.
  • Resource errors — Out of memory, disk full, CPU throttling, container limits exceeded.
  • Logic errors — Incorrect selectors, wrong assumptions about page state, stale element references.

    • Error Handling Strategies

    Effective error handling uses multiple strategies in combination:

  • Try-catch blocks — Wrap risky operations in exception handlers that catch specific error types and respond appropriately.
  • Fallback logic — When the primary approach fails, switch to an alternative method (e.g., try a different CSS selector, use a backup API endpoint).
  • Graceful degradation — Continue the workflow with partial results rather than failing completely. A scraper that cannot extract one field should still capture the others.
  • Structured logging — Record error details including timestamps, stack traces, input values, and context for debugging.
  • Alerting — Notify operators of critical failures via email, Slack, or webhook so they can intervene quickly.

    • Error Handling Best Practices

  • Be specific — Catch specific error types rather than catching all exceptions. This prevents masking unexpected bugs.
  • Fail fast for unrecoverable errors — Do not retry authentication failures or malformed requests. Report them immediately.
  • Preserve context — Log what the workflow was doing when the error occurred, not just the error message.
  • Design for partial failure — In multi-step workflows, isolate failures so one broken step does not cascade to unrelated steps.

    • 为什么重要

    Error handling determines the reliability of any automation system. Workflows without proper error handling fail silently, produce corrupt data, and require constant manual monitoring. Good error handling makes automation truly autonomous.

    Autonoly 如何解决

    Autonoly provides built-in error handling at every level. Browser automation steps automatically catch and report selector failures, navigation errors, and timeout issues. The workflow engine supports conditional error branches, automatic retries, and real-time failure alerts so your automations recover gracefully.

    了解更多

    示例

    • A data extraction workflow that catches selector-not-found errors, falls back to an alternative CSS selector, and logs the discrepancy for future investigation.

    • A multi-site scraping pipeline that isolates failures per site, continues processing remaining sites, and generates a summary report of which sites succeeded and which failed.

    • An API integration workflow that catches 401 errors, refreshes the OAuth token, and retries the request before escalating to the user.

    常见问题

    Exception handling is a specific mechanism (try-catch-finally) for dealing with runtime exceptions in code. Error handling is the broader practice that includes exception handling plus logging, alerting, retry logic, fallback strategies, and recovery procedures. Exception handling is one tool within the error handling toolbox.

    Automated workflows should categorize errors as retryable or terminal, implement automatic retries with backoff for transient failures, log all errors with full context, alert operators for critical failures, and use fallback paths when available. The goal is to maximize the amount of useful work completed even when individual steps fail.

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