MLflow 1.26.0 includes several major features and improvements:

Features:

• [CLI] Add endpoint naming and options configuration to the deployment CLI (#5731, @trangevi)
• [Build,Doc] Add development environment setup script for Linux and MacOS x86 Operating Systems (#5717, @BenWilson2)
• [Tracking] Update mlflow.set_tracking_uri to add support for paths defined as pathlib.Path in addition to existing str path declarations (#5824, @cacharle)
• [Scoring] Add custom timeout override option to the scoring server CLI to support high latency models (#5663, @sniafas)
• [UI] Add sticky header to experiment run list table to support column name visibility when scrolling beyond page fold (#5818, @hubertzub-db)
• [Artifacts] Add GCS support for MLflow garbage collection (#5811, @aditya-iyengar-rtl-de)
• [Evaluate] Add pos_label argument for eval_and_log_metrics API to support accurate binary classifier evaluation metrics (#5807, @yxiong)
• [UI] Add fields for latest, minimum and maximum metric values on metric display page (#5574, @adamreeve)
• [Models] Add support for input_example and signature logging for pyspark ml flavor when using autologging (#5719, @bali0019)
• [Models] Add virtualenv environment manager support for mlflow models docker-build CLI (#5728, @harupy)
• [Models] Add support for wildcard module matching in log_model_allowlist for PySpark models (#5723, @serena-ruan)
• [Projects] Add virtualenv environment manager support for MLflow projects (#5631, @harupy)
• [Models] Add virtualenv environment manager support for MLflow Models (#5380, @harupy)
• [Models] Add virtualenv environment manager support for mlflow.pyfunc.spark_udf (#5676, @WeichenXu123)
• [Models] Add support for input_example and signature logging for tensorflow flavor when using autologging (#5510, @bali0019)
• [Server-infra] Add JSON Schema Type Validation to enable raising 400 errors on malformed requests to REST API endpoints (#5458, @mrkaye97)
• [Scoring] Introduce abstract endpoint interface for mlflow deployments (#5378, @trangevi)
• [UI] Add End Time and Duration fields to run comparison page (#3378, @RealArpanBhattacharya)
• [Serving] Add schema validation support when parsing input csv data for model serving (#5531, @vvijay-bolt)

Bug fixes and documentation updates:

• [Models] Fix REPL ID propagation from datasource listener to publisher for Spark data sources (#5826, @dbczumar)
• [UI] Update ag-grid and implement getRowId to improve performance in the runs table visualization (#5725, @adamreeve)
• [Serving] Fix tf-serving parsing to support columnar-based formatting (#5825, @arjundc-db)
• [Artifacts] Update log_artifact to support models larger than 2GB in HDFS (#5812, @hitchhicker)
• [Models] Fix autologging to support lightgbm metric names with "@" symbols within their names (#5785, @mengchendd)
• [Models] Pyfunc: Fix code directory resolution of subdirectories (#5806, @dbczumar)
• [Server-Infra] Fix mlflow-R server starting failure on windows (#5767, @serena-ruan)
• [Docs] Add documentation for virtualenv environment manager support for MLflow projects (#5727, @harupy)
• [UI] Fix artifacts display sizing to support full width rendering in preview pane (#5606, @szczeles)
• [Models] Fix local hostname issues when loading spark model by binding driver address to localhost (#5753, @WeichenXu123)
• [Models] Fix autologging validation and batch_size calculations for tensorflow flavor (#5683, @MarkYHZhang)
• [Artifacts] Fix SqlAlchemyStore.log_batch implementation to make it log data in batches (#5460, @erensahin)

Small bug fixes and doc updates (#5858, #5859, #5853, #5854, #5845, #5829, #5842, #5834, #5795, #5777, #5794, #5766, #5778, #5765, #5763, #5768, #5769, #5760, #5727, #5748, #5726, #5721, #5711, #5710, #5708, #5703, #5702, #5696, #5695, #5669, #5670, #5668, #5661, #5638, @harupy; #5749, @arpitjasa-db; #5675, @Davidswinkels; #5803, #5797, @ahlag; #5743, @kzhang01; #5650, #5805, #5724, #5720, #5662, @BenWilson2; #5627, @cterrelljones; #5646, @kutal10; #5758, @davideli-db; #5810, @rahulporuri; #5816, #5764, @shrinath-suresh; #5869, #5715, #5737, #5752, #5677, #5636, @WeichenXu123; #5735, @subramaniam02; #5746, @akaigraham; #5734, #5685, @lucalves; #5761, @marcelatoffernet; #5707, @aashish-khub; #5808, @ketangangal; #5730, #5700, @shaikmoeed; #5775, @dbczumar; #5747, @zhixuanevelynwu)

Note: Version 1.26.0 of the MLflow R package has not yet been released. It will be available on CRAN within the next week.