Genesys Cloud - Main

We transitioned from PureConnect to Genesys Cloud on 10/24/23. We tried to run a basic queue performance report using a date range of 10/24/23 - 3/29/24, and we are receiving a 503 error message and the data refuses to load. If we run the report individually for each month, the data will load without any issues. We are not a big call center. We only handle appx. 35,000 interactions each month, so it's not like we are trying to run a massive amount of data. We also never had this issue in Pureconnect, and we could easily pull 12 months of data at once - it would take a few minutes to run, but it never timed out. The fact that we can't generate a basic queue performance report with only 5 months of data is absolutely mind-boggling to me. After reaching out for support, the "recommendation" we received was to pull the data in three-month increments. This is an absolutely unacceptable response to me. I am curious - has anyone else encountered this issue?  

#Reporting #Error       

 

#Reporting/Analytics

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Elizabeth Guthrie
Aramark Services Inc.
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I have a lot of issues pulling what I would consider basic reports.  I would love to be able to pull a time frame, like a year, with the display being totals by Monthly and it just doesn't work. 

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Gina Palmer
Manager, Workforce Management
Papa, Inc.
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Hello Elizabeth!

I'm sorry for your experience and rest assured it's on our roadmap to improve this functionality.  Genesys Cloud runs off a true big data architecture model which carries the huge benefit of being able to centralize the infrastructure in a way that allows rapid deployment, cost effective solutions, and centralized management.  High level, big data infrastructure achieves this by spreading data across many server nodes and gathering data in strategic chunks.

One immediate drawback to this is gathering wide spans of data at one time like a YTD report increases the amount of "chunks" it has to pull together.  When you had a dedicated database on your old solution, even if it was process intensive for the database to pull that data together, it was less impactful in the moment to run that report.  It also came with server costs, maintenance costs, internal security teams (or lack of security), lack of cloud access, difficulty to upgrade, etc.  There's a reason why the industry is moving on from this model. 

All that to say that it's not an excuse.  You are correct that the platform should support this and we have a plan in the works.  On a shared big data solution, long running jobs that leverage wide spans of data need special consideration to ensure it doesn't affect the platform as a whole.  We have two projects in development that will release at the same time to support larger report runs in our exports.

On the backend, we're adding a new API endpoint that will take in a large interval and run those queries in batch. 

https://genesyscloud.ideas.aha.io/ideas/ANLS-I-974

Within the export service, we're restructuring that service to work with the new API endpoint and increase our abilities to run more simultaneous exports.

https://genesyscloud.aha.io/ideas/ideas/DARAR-I-1776

We expect to be able to deliver much improved abilities to export wider date ranges in the back half of this year.

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Ryan Legner
Staff Product Manager, Genesys Cloud CX
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Thanks for the detailed explanation and the transparency, Ryan. This is a massive pain point for us, so eagerly awaiting the improved functionality scheduled for release later this year. 

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Elizabeth Guthrie
Aramark Services Inc.
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Original Message:
Sent: 04-25-2024 09:58
From: Ryan Legner
Subject: Reporting 503 Error Message > Queue Performance Report

Hello Elizabeth!

I'm sorry for your experience and rest assured it's on our roadmap to improve this functionality.  Genesys Cloud runs off a true big data architecture model which carries the huge benefit of being able to centralize the infrastructure in a way that allows rapid deployment, cost effective solutions, and centralized management.  High level, big data infrastructure achieves this by spreading data across many server nodes and gathering data in strategic chunks.

One immediate drawback to this is gathering wide spans of data at one time like a YTD report increases the amount of "chunks" it has to pull together.  When you had a dedicated database on your old solution, even if it was process intensive for the database to pull that data together, it was less impactful in the moment to run that report.  It also came with server costs, maintenance costs, internal security teams (or lack of security), lack of cloud access, difficulty to upgrade, etc.  There's a reason why the industry is moving on from this model. 

All that to say that it's not an excuse.  You are correct that the platform should support this and we have a plan in the works.  On a shared big data solution, long running jobs that leverage wide spans of data need special consideration to ensure it doesn't affect the platform as a whole.  We have two projects in development that will release at the same time to support larger report runs in our exports.

On the backend, we're adding a new API endpoint that will take in a large interval and run those queries in batch. 

https://genesyscloud.ideas.aha.io/ideas/ANLS-I-974

Within the export service, we're restructuring that service to work with the new API endpoint and increase our abilities to run more simultaneous exports.

https://genesyscloud.aha.io/ideas/ideas/DARAR-I-1776

We expect to be able to deliver much improved abilities to export wider date ranges in the back half of this year.

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Ryan Legner
Staff Product Manager, Genesys Cloud CX
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