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50002 - What is considered statistically normal versus high frequency of these errors?

50002 errors can never be eliminated entirely, but how do you know you have done enough to eliminate them?  What is normal vs excessive?  We have developed a metric that can be shared across Cisco partners and customers that will help us all determine where we stand in the industry.

 

Run the query below against your UCCE instance and share the results.  This query basically provides statistics and ultimately a ratio of 50002 errors per agent hour logged in (50002dedups_Hours_%).

 

select

convert(date, Date) Date,

count(1) Agents,

1.0*nullif(sum([50002_dedups]), 0) / nullif(sum(HoursLoggedIn), 0) [50002dedups_Hours_%],

sum(Logins) Logins,

sum(HoursLoggedIn) HoursLoggedIn,

sum([50002_dedups]) [50002_dedup],

sum([50002s]) [50002s]

from

(

       select

       *,

       datediff(HH, LoginDate, LogoutDate) HoursLoggedIn      -- hours logged in

       from (

             select

             SkillTargetID,

             convert(date, DateTime) Date,

             max(case when Event=1 then 1 else 0 end) Logins,       -- only count 1 login per agent per day

             min(case when Event=1 then aed.DateTime else null end) LoginDate,

             max(case when Event=2 then aed.DateTime else null end) LogoutDate,

             sum(case when Event=3 and ReasonCode=50002 then 1 else 0 end) [50002s],

             sum(case when Event=3 and ReasonCode=50002 and Duration<>900 and Duration<>1800 then 1 else 0 end) [50002_dedups]       -- remove duplicate 50002 (15 min interval = 900 seconds, 30 min interval = 1800 seconds)

             from Agent_Event_Detail aed

             where aed.DateTime >= convert(date, getdate()-14)      -- last 14 days

             group by aed.SkillTargetID, convert(date, DateTime)    -- group by agent, then day

       ) A

) B

group by convert(date, Date)

order by convert(date, Date)

 

I get asked about this error code everywhere I go, and when it is not correlated to a server-side or network event, it is often a rat hole that never seems to end.  Use the results of this query to help determine if it is worth the effort or not to investigate causes of 50002 in your environment.  The power of this data is when you share your results with the community.  Thanks for participating.

Everyone's tags (4)
20 REPLIES 20
Enthusiast

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

I am not a partner but a customer. However I have recently opened my second TAC case for this very issue. During the first, I engaged the network team who applied a QOS policy to prioritize the Finesse traffic between the call centers and the DC's. At the time we thought the problem was solved. Unfortunately one of our centers recently complained about this issue and I had to open Pandora's box again. I ran a similar query against our Aceyus DB event detail table and grabbed all of the 50002 events by call center, along with the durations. I totaled over six thousand hours of lost productivity due to the random  not ready issue. I have engaged my Cisco team to hopefully work with the BU and TAC on this because I feel like it might be a major issue that is just being swept under the rug...

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

I have updated my original post to make this thread more efficient.

Highlighted

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

Results from three customers:

 

Customer ONE:

Date    Agents    50002dedups_Hours_%    Logins    HoursLoggedIn    50002_dedup    50002s
2018-10-22    219    0.097285067873    191    1326    129    1082
2018-10-23    213    0.080704328686    189    1363    110    923
2018-10-24    213    0.126013264554    189    1357    171    1127
2018-10-25    217    0.146994931209    192    1381    203    1291
2018-10-26    215    0.097451274362    187    1334    130    1244
2018-10-27    36    1.116279069767    7    43    48    1296
2018-10-28    30    22.000000000000    1    3    66    1276
2018-10-29    226    0.128401953942    204    1433    184    1207
2018-10-30    225    0.068868587491    198    1423    98    1106
2018-10-31    227    0.091718001368    203    1461    134    1002
2018-11-01    217    0.082327892122    207    1409    116    709
2018-11-02    206    0.091269841269    183    1260    115    1043
2018-11-03    41    0.812500000000    9    64    52    1381
2018-11-04    31    18.000000000000    3    3    54    1350
2018-11-05    28    NULL    0    NULL    5    162

 

Dates with data out of range are weekends were with unusual traffic or planned maintenance, so should be ignored.  Looks like this Customer hovers around 8.5% 50002 errors per hour logged in.  This query focuses only on the initial occurrence and filters out repeats at the interval.

 

Customer sample 2 (this customer uses WFM and adherence is important to them, hence lower numbers than Customer sample 1 above)  around 4% 50002 per hour logged in.

Date    Agents    50002dedups_Hours_%    Logins    HoursLoggedIn    50002_dedup    50002s
2018-10-22    949    0.048904296149    898    8077    395    3544
2018-10-23    955    0.037229641886    942    8461    315    1872
2018-10-24    991    0.038420236248    975    8381    322    1946
2018-10-25    886    0.134738899748    878    7162    965    3620
2018-10-26    889    0.041318681318    863    6825    282    3549
2018-10-27    244    0.056478405315    190    1505    85    4105
2018-10-28    35    NULL    0    NULL    0    3360
2018-10-29    960    0.044881125667    928    8244    370    3149
2018-10-30    994    0.033484963356    981    7914    265    2470
2018-10-31    1003    0.041812333939    959    7151    299    4116
2018-11-01    974    0.046942400405    915    7882    370    5276
2018-11-02    905    0.063762909744    835    6681    426    5861
2018-11-03    307    0.058593750000    232    1792    105    6246
2018-11-04    58    NULL    0    NULL    0    5700
2018-11-05    58    NULL    0    NULL    0    57

 

Customer Sample 3:  Customer appears around 6% per hour logged in.

Date    Agents    50002dedups_Hours_%    Logins    HoursLoggedIn    50002_dedup    50002s
2018-10-22    93    0.071216617210    93    674    48    67
2018-10-23    89    0.072164948453    89    679    49    86
2018-10-24    93    0.059405940594    92    707    42    103
2018-10-25    90    0.054054054054    89    666    36    77
2018-10-26    86    0.057722308892    85    641    37    66
2018-10-27    1    NULL    1    7    0    0
2018-10-29    93    0.041786743515    93    694    29    59
2018-10-30    92    0.059574468085    91    705    42    65
2018-10-31    87    0.029411764705    87    646    19    26
2018-11-01    84    0.062500000000    84    640    40    61
2018-11-02    84    0.053833605220    84    613    33    42
2018-11-03    2    NULL    2    14    0    0

Enthusiast

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

Here are the results from one of my systems:

 

Date Agents 50002dedups_Hours_% Logins HoursLoggedIn 50002_dedup 50002s
10/22/2018 641 0.069073783 640 5096 352 416
10/23/2018 634 0.06993007 633 5005 350 439
10/24/2018 623 0.07115869 619 4764 339 438
10/25/2018 598 0.067743383 595 4458 302 382
10/26/2018 570 0.09506705 569 4176 397 463
10/27/2018 218 0.100123609 216 1618 162 180
10/28/2018 77 0.075645756 75 542 41 44
10/29/2018 627 0.05625879 627 4977 280 328
10/30/2018 621 0.055180871 619 4893 270 345
10/31/2018 613 0.065718947 611 4291 282 356
11/1/2018 583 0.051089759 580 4267 218 249
11/2/2018 547 0.047793221 545 4101 196 223
11/3/2018 211 0.038961039 210 1540 60 77
11/4/2018 75 0.033149171 74 543 18 18
11/5/2018 595 0.087250712 592 2808 245 262
Beginner

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

Thanks for posting this thread. This is an issue we've had for years from back in CAD 7.5 until now on Finesse 11.6. We've recently started testing a Finesse gadget that will change the user state back to the previous state if the not ready reason code is undefined. Has anyone tried this before?

 

Date Agents 50002dedups_Hours_% Logins HoursLoggedIn 50002_dedup 50002s
2018-10-29 538 0.052606060606 537 4125 217 405
2018-10-30 518 0.061866125760 505 3944 244 618
2018-10-31 494 0.073849545329 482 3629 268 700
2018-11-01 501 0.085490830636 483 3708 317 910
2018-11-02 514 0.079461457233 496 3788 301 868
2018-11-03 133 0.043478260869 115 690 30 797
2018-11-04 57 0.128318584070 38 226 29 811
2018-11-05 538 0.085023210359 522 4093 348 913
2018-11-06 505 0.056967103503 489 3739 213 947
2018-11-07 512 0.061830835117 508 3736 231 472
2018-11-08 509 0.046113306982 489 3795 175 723
2018-11-09 507 0.040619989310 490 3742 152 699
2018-11-10 121 0.066978193146 107 642 43 697
2018-11-11 61 0.007662835249 44 261 2 722
2018-11-12 512 0.083458646616 495 2660 222 503

 

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

We've also been discussing this option.

Beginner

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

I have been testing the below in my test environment and had good results. I am forcing a CTI failure by restarting the Cisco Finesse Tomcat service on the Finesse server with this command. I am planning on testing this with live users on Thursday and will let you know how it goes.

utils service restart Cisco Finesse Tomcat

Let me know if you have any feedback on this.

/* need to define oldState and oldReason as global variables at top of gadget */

/**
 *  Handler for all User updates
 */
handleUserChange = function(userevent) {		
	//log current state and reason code
	clientLogs.log("handleUserChange, current state is: " + user.getState() + " reason is: " + user.getNotReadyReasonCodeId());	
	
	if (currentState == "NOT_READY") {
		var NotReadyCode = user.getNotReadyReasonCodeId();			
		
		if (NotReadyCode == "50002" || NotReadyCode == "undefined" || NotReadyCode == null) {
			//log new state we are trying to set
			clientLogs.log("setState, new state is: " + oldState + " reason is: " + oldReason);
			
			if (oldState == "NOT_READY") {
				var rc = { id: oldReason };
				user.setState(oldState, rc, {success: makeStateSuccess, error: makeStateError});
				function makeStateSuccess(){
					clientLogs.log("setState, success");
				}
				function makeStateError(){
					clientLogs.log("setState, error");
				}
			} else {
				user.setState("READY", null, {success: makeStateSuccess, error: makeStateError});
				function makeStateSuccess(){
					clientLogs.log("setState, success");
				}
				function makeStateError(){
					clientLogs.log("setState, error");
				}
			}
		}
	}
	
	//always gather the old state and old reason code
	oldState = user.getState();
	oldReason = user.getNotReadyReasonCodeId();
}; 
Beginner

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

Just an update from a few weeks of testing this gadget with live users. The amount of 50002 occurrences and time spent in 50002 have stayed around average.
Collaborator

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

@Joe Gilbert I'm trying to understand why you want to do this? Is this just so the agent to not see an unnecessary error on their Finesse?

 

david

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

I don't know about Joe, but our reason would be simple. WFM- Adherence.
Collaborator

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

Hey Jason. Ok, so tell me more about this as I'm not following the use case. Group of agents are logged in and all of a sudden someone kicks their network segments and puts them all offline. It takes them about 30 minutes to figure out the issue and get back into CCE. Adherencewise, these agents were not online and receiving calls, so they would be out of compliance during that span.

 

david

Re: 50002 - What is considered statistically normal versus high frequency of these errors?

Your use case is valid. Use Case #2. Agent is momentarily disconnected from Finesse while their browser is backgrounded for whatever client side reason. They think they are still ready but they are not.
Beginner

Re: 50002 - What is considered statistically normal versus high frequency of these errors?


jasondurie@moonjet.com wrote:
Your use case is valid. Use Case #2. Agent is momentarily disconnected from Finesse while their browser is backgrounded for whatever client side reason. They think they are still ready but they are not.

This would be our use case as well. The end user is in the ready state in Finesse but working on something else in a different system. There is no pop up or notification when they get put into Not Ready - CTI Failure so they may sit in this state for a long time before changing back to ready.

The goal of the gadget I posted above is to store the user's state in a global variable. When the user's state changes to CTI Failure (not ready with undefined code), change the user back to the previous state.

Beginner

Re: 50002 - What is considered statistically normal versus high frequency of these errors?


@Joe Gilbert wrote:

jasondurie@moonjet.com wrote:
Your use case is valid. Use Case #2. Agent is momentarily disconnected from Finesse while their browser is backgrounded for whatever client side reason. They think they are still ready but they are not.

This would be our use case as well. The end user is in the ready state in Finesse but working on something else in a different system. There is no pop up or notification when they get put into Not Ready - CTI Failure so they may sit in this state for a long time before changing back to ready.

The goal of the gadget I posted above is to store the user's state in a global variable. When the user's state changes to CTI Failure (not ready with undefined code), change the user back to the previous state.


Joe, it would really help if you could please provide a snapshot of the updated gadget and code. We have a similar use case where agent goes to not ready connection failure and we need to put them back to not ready or ready state. if you have code or script that automatically assigns this then it would be of great help. Kindly share

Best Regards

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