2023.2 Release Overview
We are pleased to announce the following product improvements in our 2023.2 release:
- ML Workload Orchestration: Wallaroo platform users (data scientists or ML Engineers) have the ability to deploy, automate and scale recurring production ML workloads that can ingest data from predefined data sources to run inferences in Wallaroo, chain pipelines, and send inference results to predefined destinations to analyze model insights and assess business outcomes. The following resources are available:.
- ML Workload Orchestration Configuration Guide to enable orchestrations in a Wallaroo 2023.2 instance.
- Wallaroo SDK Essentials Guide: ML Workload Orchestration for instructions on orchestration requirements, how to upload them and schedule them for use.
- ML Workload Orchestration Tutorials: An expanding list of tutorials showing how to automate processes and integrations with systems such as Google Big Query, etc.
- Default Apache Arrow support: Apache arrow is now enabled by default for inference requests and results. Inference requests are submitted as pandas DataFrames, Apache Arrow tables, or custom JSON. Inference requests are sent via the Wallaroo SDK or through the Wallaroo API.
- Wallaroo Data Connections: MLOps Engineers can define data connection configurations, then relate them to Wallaroo workspaces for others users to access. This allows organizations to define connections to data stores, then make them available to other users to automate data retrieval and storage needs during ML operations. See the following guides for details:
- Drift Detection Assays on multiple inputs and outputs: Data scientists in Wallaroo can run drift detection assays to monitor specific model inputs or outputs, with their specific fields and their indexes for ML pipelines deployed in Wallaroo. For more details, see the following: