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Possible Errors

Platform & Limits Errors

Common errors related to platform limits, parallel runs, execution time, and compute resources (CPU/RAM). For more on limits, see Platform limits.


Plug and Play balance empty

The built-in AI credits for plug-and-play AI nodes have run out (separate from subscription credits).

Message: AI Agent node error: 'plug and play balance is empty'

Cause: Token limit for plug-and-play nodes on your account is exhausted.

Fix

  • Top up your Plug and Play balance in Billing.
  • Or add your own API key in the node's connection settings.

Parallel execution limit

Too many scenario runs at once — plan's parallel execution limit exceeded (429).

Messages: Webhook responded 429: exceed limit of parallel executions, or that max simultaneous runs reached and requests are being rejected.

Cause: Multiple scenarios triggered at the same time and exceeded the plan limit.

Fix

  • Reduce trigger frequency.
  • Upgrade to a plan with a higher parallel execution limit.

Execution time exceeded

The scenario ran longer than the platform's maximum allowed execution time.

Message: Scenario execution time exceeded

Cause: Scenario execution duration limit hit; often due to iterating over too much data, slow APIs, or heavy processing.

Fix


CPU / RAM resource limits

The scenario needs more compute resources than the current engine tier allows.

Messages: resource limits exceeded, Insufficient CPU/RAM resources — switch Memory and CPU Limits to Engine Tier 1

Cause: JavaScript with large payloads in memory, Headless Browser on a low-resource tier, or large file/image processing.

Fix

  • Scenario settings → Memory and CPU LimitsEngine Tier 1 or higher. See Enhanced compute resources.
  • Avoid loading large arrays into memory at once; split heavy work into separate scenarios.

Scenario deployment limits

Unable to deploy or activate — node count or active scenario limit reached for your plan.

Messages: node count limit reached, Maximum active scenarios reached — cannot activate new scenario

Cause: Plan limits the number of active scenarios or nodes; too many scenarios are active at once.

Fix

  • Deactivate unused scenarios.
  • Simplify large scenarios (split into sub-scenarios).
  • Upgrade to a plan with higher limits.