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Historical execution data overview

Genesys Cloud offers access to comprehensive historical execution data for all Architect flow types. With advanced capabilities in historical data analysis, users can manage and analyze historical execution data effectively, and gain insights into user journeys to make improvements and troubleshoot. Users can enable or disable execution data storage and select from four distinct levels of execution data granularity:

  • Base: understand high-level user journeys through Architect actions and navigated menus, errors, and events.
  • Notes: optimize Architect flows using variable values (includes the Base level).
  • Verbose Notes: access conversation content with communication values (includes the Notes level).
  • All: troubleshoot through action input and output values (includes the Verbose Notes level).
Notes:
  • Historical execution data counts toward your organization’s data storage limit under the Genesys Cloud fair use policy. For more information, see Genesys Cloud fair use policy.
  • Execution data storage is disabled by default. To start capturing execution data, you must enable it and republish flows.

The following examples are possible scenarios that consumers of historical execution data can use the execution data for:

  • Listen for specific flow events, for example, when flows encounter an error
  • Watch events for a specific flow and analyze specific flow execution items, for example, when a flow runs a particular action and the action takes the failure or timeout path
  • See which flows are running more than others

Notes:
  • Genesys Cloud stores historical flow execution data for 10 days.
  • Genesys Cloud supports returning a maximum of 200 execution data instances per query. It is important to note that Genesys Cloud cannot guarantee that the query returns the most recent 200 execution instances.
  • Genesys Cloud does not store the historical execution data of flows that run longer than three days.
  • In call flows, Genesys Cloud reports only the first 4,500 action executions.
  • If a call flow has more than 350 variables, Genesys only records execution data at the base log level.
  • As common module flows are embedded in their parent flows and do not run on their own, you can get execution data for them only as part of the invoking (parent) flow’s historical execution data.
  • If a value of the following data types exceeds the size limit that Genesys Cloud can store in execution data, Genesys Cloud reports valueIsTooLarge:true:
    • JSON – maximum 1,000 characters
    • String – maximum 253 characters
    • Collection data types – maximum 20 items
  • Genesys Cloud only allows reporting data at the Base level for execution instances of secure flows, for example, bot flows that ran in a secure session, regardless of the execution data setting of your organization or the specific secure bot flows.
  • It is not possible to query execution data for flow instances by start or end date time. To narrow the scope of responses, Genesys Cloud recommends that you rely on conversationId instead.

The following video walks you through how to enable and configure historical execution data. The video also demonstrates how you can use the various data settings for advanced troubleshooting.

For more information about how to set the execution data level for an organization or override the organization-wide execution data level for an individual flow, see Manage historical execution data.

Features in Architect

Historical execution data is retrievable via the public API and the notification service for third-party access. For more information about the relevant endpoints in the public API, see Start a process (job) to prepare a download of a singular flow execution data instance by Id and Get the status and/or results of an asynchronous flow execution data retrieval job in the Genesys Cloud Developer Center.

Notes:
  • Aggregate data, such as counts of the number of times that an action runs during a flow, is not supported.
  • You can only view flow execution data for published flows. To ensure that you capture the most recent execution data, make sure that you republish the flow and send an interaction through it before you run a query.