Ticket Lifecycle {{ currentPage ? currentPage.title : "" }}


  • Improve the matching and suggestion flows 

  • Boost database performance

  • Provide access to real time data about agents availability, suggestion queue, active assignments

Main changes

  • Re-implemented the ticket lifecycle in two main services- Matching Service, Suggestion Service and Assignments Service

  • Introduced Different types and number of databases 

  • No UI changes


The ticket flow from the point it was triggered by the user- requesting a service through the app, going through the phase where its been matched and suggested to agents who can handle based on their tiers and certification, till the point the ticket is completed and closed.

below is a diagram to show the ticket lifecycle nodes.

  • Trigger: trigger the ticket from multiple sources (system, app-x [stuff app, web app, etc...]), the trigger should carry the needed data to create the ticket based on the request<>user details

  • Create: after triggering the ticket, the system generate a new ticket inside the system, with the relevant ticket type, and user request request to move it to the matching step

  • Match: in this step, the created ticket will be matched to the relevant available (online) agents that holds certificate/s that make them eligible to handle this ticket type

  • Suggest: ticket will be stored in the suggestion databases according to the matching results, and these tickets will be suggested to agents based on some configurations

  • Assign: ticket will be assigned to a specific agent to handle it and start working on it

  • Close: last step of handling the ticket, based on multiple triggers to close it, including User marking ticket as complete.

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