Precautions and known issues with application upgrades

If you are using the Table API, Apache Flink doesn't guarantee state compatibility between Flink versions. For more information, see Stateful Upgrades and Evolution in the Apache Flink documentation.

Flink 1.6 states are not compatible with Flink 1.18. The API rejects your request if you try to upgrade from 1.6 to 1.18 and later with state. You can upgrade to 1.8, 1.11, 1.13 and 1.15 and take a snapshot, and then upgrade to 1.18 and later. For more information, see Upgrading Applications and Flink Versions in the Apache Flink documentation.

If you are using Flink 1.11 or earlier and using the amazon-kinesis-connector-flink connector for Enhanced-fan-out (EFO) support, you must take extra steps for a stateful upgrade to Flink 1.13 or later. This is because of the change in the package name of the connector. For more information, see amazon-kinesis-connector-flink.

The amazon-kinesis-connector-flink connector for Flink 1.11 and earlier uses the packaging software.amazon.kinesis, whereas the Kinesis connector for Flink 1.13 and later uses org.apache.flink.streaming.connectors.kinesis. Use this tool to support your migration: amazon-kinesis-connector-flink-state-migrator.

If you are using Flink 1.13 or earlier with FlinkKinesisProducer and upgrading to Flink 1.15 or later, for a stateful upgrade you must continue to use FlinkKinesisProducer in Flink 1.15 or later, instead of the newer KinesisStreamsSink. However, if you already have a custom uid set on your sink, you should be able to switch to KinesisStreamsSink because FlinkKinesisProducer doesn't keep state. Flink will treat it as the same operator because a custom uid is set.

As of Flink 1.15, Apache Flink doesn't include Scala in the runtime. You must include the version of Scala you want to use and other Scala dependencies in your code JAR/zip when upgrading to Flink 1.15 or later. For more information, see Amazon Managed Service for Apache Flink for Apache Flink 1.15.2 release.

If your application uses Scala and you are upgrading it from Flink 1.11 or earlier (Scala 2.11) to Flink 1.13 (Scala 2.12), make sure that your code uses Scala 2.12. Otherwise, your Flink 1.13 application may fail to find Scala 2.11 classes in the Flink 1.13 runtime.

Downgrading Flink applications is possible, but limited to cases when the application was previously running with the older Flink version. For a stateful upgrade Managed Service for Apache Flink will require using a snapshot taken with matching or earlier version for the downgrade

If you are updating your runtime from Flink 1.13 or later to Flink 1.11 or earlier, and if your app uses the HashMap state backend, your application will continuously fail.