arifazmidd opened a new issue, #11412:
URL: https://github.com/apache/iceberg/issues/11412

   ### Apache Iceberg version
   
   1.6.1 (latest release)
   
   ### Query engine
   
   Spark
   
   ### Please describe the bug 🐞
   
   There seems to be some transient AWS connection issues with running Spark. I 
have workloads running Spark on both DBR and EMR which are interacting with 
Iceberg tables. They run fine most of the time but randomly will fail with the 
following error:
   ```
   software.amazon.awssdk.core.exception.SdkClientException: Unable to load 
credentials from any of the providers in the chain 
   ```
   
   On DBR it is randomly failing with the 
[overwritePartitions](https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.DataFrameWriterV2.overwritePartitions.html#pyspark.sql.DataFrameWriterV2.overwritePartitions)
 call from the DataFrameWriterV2 and on EMR it is randomly failing with the 
[spark sql procedure for expiring 
snapshots](https://iceberg.apache.org/docs/1.5.1/spark-procedures/#expire_snapshots)
   
   I believe the issue could be similar to this: 
https://github.com/aws/aws-sdk-js-v3/issues/4867. Basically that we need to be 
mindful of how many requests we send to IMDS to avoid throttling errors. I'm 
thinking that with Iceberg we are creating a new client for every call which 
could be causing this?
   
   I will provide my config details and the full error log as comments.
   
   ### Willingness to contribute
   
   - [ ] I can contribute a fix for this bug independently
   - [X] I would be willing to contribute a fix for this bug with guidance from 
the Iceberg community
   - [ ] I cannot contribute a fix for this bug at this time


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