Summary of Alerts

Detail of Alerts

DP-439207 - AIX JSON Unicode Parsing Issue

A bug has been identified in InterSystems IRIS 2024.3.0 on AIX instances that affects the parsing of JSON Unicode strings. The issue arises when either the %FromJSON() or %FromJSONFile() method parses strings that contain characters with values less than $CHAR(256) followed by Unicode characters exceeding $CHAR(255). The conversion process incorrectly transforms the earlier characters into $CHAR(0), leading to silent data corruption. This issue only affects AIX version 2024.3 of the following products:

• InterSystems IRIS
• InterSystems IRIS for Health
• HealthShare® Health Connect

Impact Assessment

• When this occurs, incorrect characters may be stored in the database or passed to interfaces without triggering errors.
• The defect was introduced in IRIS 2024.3.0 and has been resolved with DP-439207.
• Affected Workflows: This issue only occurs on Unicode installations running AIX, affecting applications processing data that contain a mix of ASCII and Unicode characters.

Resolution

• If you are using InterSystems IRIS 2024.3.0 on AIX instances, then you should upgrade to InterSystems IRIS 2025.1.0 as soon as possible.

Customer Actions Required

1. Identify Impacted Systems:
   • Determine if you are running InterSystems IRIS 2024.3.0 on an AIX instance with Unicode databases and have a mix of Unicode and non-Unicode characters.
2. Upgrade Path:
   • Upgrade to InterSystems IRIS 2025.1.0 as soon as possible.

DP-439280 - IntegratedML Container TensorFlow Issues

Customers using either of the following containerized version of IRIS 2024.3 may encounter training errors when leveraging IntegratedML.

Impact Assessment

• Customers leveraging IntegratedML on the InterSystems-provided IRIS 2024.3 containers will experience model training failures due to compatibility issues with TensorFlow and related dependencies.

Resolution

• Customers wishing to use IntegratedML with IRIS or IRIS for Health in containers are encouraged to create your own containers by following the advice published on the Developer Community.

Customer Actions Required

• To continue using IntegratedML with AutoML, customers must manually manage dependencies using the pip package manager as described above. This ensures compatibility and proper functionality of AutoML components like scikit-learn within your IntegratedML Python environment.

For More Information If you have questions or need assistance, please contact the InterSystems Worldwide Response Center (WRC).

Trying to start investigating an error we are seeing with multiple of the same messages getting sent to the same vendor. We receive an HL7 message with an RTF embedded from our EMR, send it through a DTL to just update the Patient Class, and then send it onto the Operation which is TCP.

We are starting to see this error message...

ERROR <Ens>ErrBPTerminated: Terminating BP DocOutRptRouting3M360 # due to error: ERROR <Ens>ErrException: <INVALID OREF>zOutputToIOStream+6^EnsLib.HL7.Message.1 -- logged as '-' number - @''
> ERROR <Ens>ErrException: <INVALID OREF>zOutputToIOStream+6^EnsLib.HL7.Message.1 -- logged as '-' number - @''

which is causing the messages to be sent multiple times through the Operation

when trying to view the HL7 body metadata within the trace viewer we are even seeing

ERROR <Ens>ErrException: <INVALID OREF>zFullSizeGet+3^EnsLib.HL7.Message.1 -- logged as '-' number - @''

I am starting to think this has something to do with the HEAP size and or Max Per-Process Memory which is set at 262 MB per process. Looking at our top memory processes we aren't seeing anything hit this limitation.

My next stop is WRC but thought I would reach out first to see if there was anyone that had an idea of what is going on.