v0.184.0
Summary
The SDK introduces environment variable configurations and maintenance window notifications across Jobs and Tasks, along with new skill management APIs in AI Gateway. It also adds the Mason workspace service and makes CommandPath in job deployments and ApiSecretRef in ML schema registries optional.
Summary generated by brickster.ai. For the full changelog and any code/binary attachments, follow the GitHub link above.
More from databricks/databricks-sdk-go
The Databricks SDK for Go now supports Config.Headers to configure custom HTTP headers on all client requests in addition to normal authentication. Practitioners can use the new StaticHeaders helper to easily apply a fixed set of headers.
This release adds AI Gateway credential management APIs for MCP services and expands data pipeline connectors to include TikTok Ads and Smartsheet as ingestion sources. It also introduces Avro and Protobuf transformer format support for pipelines, timezone configuration for ML job scheduling, and new securable types for agent services and skills.
Reduce integration test cluster usage by replacing waiter coverage with HTTP fixtures and removing redundant live tests.
The SDK adds support for new fields across multiple services: AI Runtime jobs can now specify image paths and priority classes, ML models support budget policies and tags during publishing, and serving configurations gain workspace credential options including new GPU accelerator types. Pipelines add development mode configuration and workspace settings gain ingress network policy controls.
Release introduces three new workspace services (AI Functions, Domains, Sandbox), extends Feature Engineering with new backfill and operation management methods, and adds AWS Secrets Manager and Azure Key Vault connection support. Multiple breaking changes remove fields from model serving and catalog configurations that may require code updates.