Understanding advanced action flows (EAP)

Advanced action flows provide a more powerful way to build automation for service by supporting workflows that can branch, pause for human input, connect across systems, and adapt as business rules evolve. This allows teams to automate more of their work, reducing manual effort and increasing scalability and control.


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Summary: ◀▼
Advanced action flows let you automate complex, long-running workflows with branching, pauses, and integrations across many systems using code. They support custom API calls, detailed error tracking, version control, and reuse across workflows. Use them for workflows needing complex logic, human approvals, or attachment processing. They run in secure sandboxes with execution limits and require authentication for external APIs.




Advanced action flows provide a more powerful way to build automation for service by
supporting workflows that can branch, pause for human input, connect across systems, and
adapt as business rules evolve. This allows teams to automate more of their work,
reducing manual effort and increasing scalability and control.
This article contains the following topics:
Understanding the difference between action flows and advanced action flows
Choosing the best automated workflow for your use cases
Essential facts about advanced action flows



Related articles
Creating advanced action flows
Advanced action flows API
reference
Editing and managing advanced action
flows
Monitoring and troubleshooting advanced
action flows




Understanding the difference between action flows and advanced action flows

Action flows and advanced action flows
both address the same class of use case: automated sequences of steps that can
perform actions in Zendesk and external systems. In general, action flows are best
for no or low-code repeatable automated workflows that are simple or moderately
complex, while advanced action flows are code-based and designed for more complex
and variable workflows.
The following table provides an in-depth comparison of action flows and advanced
action flows:










Action flows
Advanced action flows




Creation method
Drag-and-drop components in visual builder
Conversational AI prompt that generates editable code


Visual diagram
Built by the user in the action builder
Generated based on the code


Complexity
Low to medium complexity workflows
Low to high complexity workflows


Automation style
Structured, repeatable process automation
Flexible orchestration to support complex business
logic


Extending to new APIs
Must be predefined as an action
All REST APIs supported


Troubleshooting, drafts, and version control
Visual review, testing, and step-based editing.
Direct access to code, execution traces, and version history,
including visual review of the generated flowchart.


Typical user
Admins and process owners who prefer not to write
code
Technical admins, developers, and process owners


Ownership model
Better for broad admin adoption and ease of use
Better for precision and control








Choosing the best automated workflow for your use cases

Because action flows and advanced action flows have overlapping capabilities, it's
important to understand when they can both accomplish your goals and when one is a
better choice over the other.


When to use advanced action flows

Advanced action flows are typically the best choice if your workflow requires:

Long-running processes over days or weeks, often with human
approval steps in the middle.

Complex business logic, such as nested conditions, loops, regular
expressions, parsing JSON or custom objects, handling exceptions, or
sharing states across steps.

Attachment processing, such as reading data out of invoices, IDs,
spreadsheets, or archives.

Integrations with many systems, particularly internal, legacy, or
niche APIs that aren't supported as pre-built connectors for action
builder.


Examples that are well-suited to advanced action flows include: dynamic API
calls, advanced data transformations, multi-branching logic, and retries.
Other benefits of advanced action flows include:
Unlike action flows, you aren't limited to pre-built connectors.
Instead, you can use new, internal, or legacy REST API endpoints
immediately without having to manually create custom actions.
Additionally, every endpoint and parameter the service supports is
available for use in your advanced action flows, including endpoints
released after your workflow is created.
Because advanced action flows call APIs directly, you don't have to
maintain connectors.
Every time you save an advanced action flow, a version is saved in the
version history, making it easy to track changes and revert to an
earlier version if necessary. Each advanced action flow has a currently
published version as well as read-only snapshots of all prior
versions.
Every time an advanced action flow runs, every execution records console
outputs, network requests and responses, inputs, outputs, and errors.
This information makes it possible to quickly identify the problem if
failures occur.
Advanced action flows have predictable behavior and cost at scale,
consuming neither action credits nor model tokens unless you add an AI
step.
Advanced action flows can be invoked by AI agents and other workflows,
making them reusable across the Zendesk platform.


It's also important to understand what you can't do with advanced action flows.
You can't:
Install or import third-party packages
Access the system
Open raw sockets
Use the following JavaScript features: eval,
Proxy, Reflect,
WeakMap, WeakSet,
WeakRef, SharedArrayBuffer, and
WebAssembly

Rely on variables after the workflow is paused


If advanced action flows are a good fit for your workflow, see Creating advanced action flows.



When to use action flows

Action flows are typically the best choice if your workflow requires:

No code or low-code workflow creation and management.

Lower complexity logic for the workflow.

Highly repeatable and structured steps that are defined with the
supported Zendesk steps and pre-built connector steps.


Examples that are well-suited to action flows include: ticket routing, approvals,
status updates, and other standard workflow automations.
For more information, see Creating action flows to automate processes
across Zendesk and external systems.




Essential facts about advanced action flows

Consider the following key concepts and details before creating advanced action
flows:
Advanced action flows consist of the following parts:

Advanced action flow trigger: The condition under which the
workflow is initiated. This could be a Zendesk event (ticket, user,
organization, asset, or custom object is created, updated, or
deleted), a recurring schedule, manual initiation, a webhook called
by an external system, or invocation by an AI agent or other
workflow.

Actions: Each action is an annotated section of your code
that appears as a node in the flowchart and as a boundary in the
execution interface. Steps can include a Pause, which
causes the workflow to stop and wait for a specified duration of
time, an event to occur, an approval to be received, or for
another workflow to finish.



Generally speaking, advanced action flows use AI during the workflow
creation process to generate the code and a flowchart, but not when the
workflow itself is running. However, it is possible to incorporate AI
actions into the workflow, in which case AI is used for that process as
well. To incorporate AI into your advanced action flows, use the
agents.run() call.

Advanced action flows run in isolated environments with platform globals
instead of Node.js or browser APIs. The isolated environment is referred to
as a sandbox. This means there is no file system, raw sockets, or
packages to import. Each capability your workflow uses, whether that's
making an HTTP request, reading a ticket, or storing a value, is a
request to the host platform, which validates the request before acting.
Several isolation layers sit between your code and Zendesk
infrastructure, including separate runner processes, dedicated virtual
machine instance per execution with its own memory ceiling, a container
with no network egress permitted, and a read-only file system running as
a non-privileged user. Because of these precautions, advanced action
flows can't reach anything they haven't been explicitly granted access
to and can't affect the data or workflows of other accounts.
Note: The sandboxes used to isolate the advanced
action flows are not the same as Zendesk sandboxes, which
are used by admins and agents with permission to test features and
configurations outside of their production
environment.


All API calls made by an advanced action flow are attributed to the
administrator who created the workflow. This means the workflow has the same
permissions and access as the creator and are constrained by your account's
normal rate limits. In the code, user.creator identifies
the workflow's author and user.runner identifies the user
or system that triggered the latest execution.
When defining an advanced action flow that calls APIs in external systems,
you must authenticate the connection as required by the system. This could
be through a registered OAuth connection or providing an API key or bearer
token that is stored as an encrypted Secret within the workflow. It
is also possible to use APIs that have no authentication requirements.
Zendesk API access is deny-by-default against an allowlist. Advanced action
flows run with the permissions and account rate limits associated with the
admin who created the workflow.
Local variables don't persist through pause steps in advanced action flows.
Any variables needed after a pause step must be in
storage.




Understanding advanced action flow limits

The following execution limits are enforced by Zendesk. Exceeding these limits
results in runtime errors that are recorded in the execution trace.


Execution limits









Limit
Value




Execution timeout
Default of 5 minutes, but can be configured between 1
second and 10 minutes. pause() isn't
counted aggainst the execution timeout, but
sleep() is counted.



Memory
128 MB per execution


Maximum pause duration
30 days


Concurrent HTTP requests within one execution
8


Concurrent AI steps within one execution
4


Recorded operations per execution
100,000


Automatic retries on failed requests
Up to 5 for server errors and rate-limit
responses







Data size limits









Limit
Value




Flow output
2 MB


HTTP request body
48 MB



agent.run() text input
20 KiB


Rows per parse operation (CSV, TSV, XLSX)
10,000


Storage value
4 KB


Storage keys per scope
1,000


Storage key length
255 characters


Flow code size
512 KB








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