# Release Notes ## AI-3.4-9.1.0 Alluxio Enterprise AI 3.4-9.1.0 raises the security bar by fixing critical vulnerabilities and improves the functionality of uploading large files through multipart upload (MPU) of the northbound S3 API.\ This release deprecates the previous `log4j.properties`, replacing it with `log4j2.xml` as part of upgrading the log4j integration. Please note this is a disruptive change for deployments that were previously configuring logging through `conf/log4j.properties`; these configurations will be ignored and need to be migrated over to the new xml format for log4j2 in `conf/log4j2.xml` to take effect. It is required to use Alluxio operator 2.1.2 or later versions when deploying Alluxio with operator. ## AI-3.4-9.0.1 Alluxio AI 3.4-9.0.1 adds a configurable retry for operations to S3 UFS and adds compatibility to configure a seaweedfs storage as a S3-like UFS. ## AI-3.4-9.0.0 We are excited to announce the release of Alluxio AI 3.4! This version introduces several new features designed to enhance performance, improve resource management, and optimize data caching strategies. ### New Features #### Directory-Based Quota Management Updates The previous release first introduced Directory-Based Quota Management, enabling users to set resource limits at the directory level. This feature allowed administrators to enforce quotas on specific directories, but was previously restricted to only setting quotas on the top level directories directly under the filesystem root. The feature is now updated to allow quota settings on any directory as well as nested quota definitions. See more information in the [Directory-Based Quota documentation](/ee-ai-en/ai-3.4/feature/directory-based-quota.md). #### Directory-Based TTL Cache Evicting The new Directory-Based TTL Cache Evicting feature enables users to apply time-to-live (TTL) policies for cache entries based on specific directories. This functionality allows for more granular control over caching, ensuring that data in less frequently accessed directories can be automatically evicted after a designated time period. This feature helps maintain a fresh and relevant cache, optimizing memory usage while prioritizing the retention of important data. For more details, refer to the [Directory-Based TTL Cache Evicting documentation](/ee-ai-en/ai-3.4/feature/cache-evicting/ttl-cache-evicting.md). #### Priority-Based Cache Evicting The Priority-Based Cache Evicting feature enhances the cache management capabilities in Alluxio AI 3.4 by assigning a priority level to specific directories. This feature ensures that the more critical data remains in the cache while the less important data can be evicted when memory is needed. This manual demarcation of cached data helps maintain optimal performance for high-priority workloads. Learn more about this feature in the [Priority-Based Cache Evicting documentation](/ee-ai-en/ai-3.4/feature/cache-evicting/priority-eviction.md). ### Conclusion Alluxio AI 3.4 brings powerful new features to enhance data management and caching strategies. We encourage users to explore these enhancements to improve their data workflows. Thank you for your continued support! --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://documentation.alluxio.io/ee-ai-en/ai-3.4/release-notes.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.