Summary of Alerts
|
Alert ID
| Product & Versions Affected | Explicit Requirements |
| DP-439207 | InterSystems IRIS® data platform 2024.3 (AIX) | AIX installations Using JSON processing and Unicode non-Latin-1 character sets |
| DP-439280 | InterSystems IRIS 2024.3 (containers with IntegratedML) | IntegratedML Containers using TensorFlow |
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
- 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.
- 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.
containers.intersystems.com/intersystems/iris-ml:2024.3
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).