Summary
v1.124.0 adds Terraform resources and data sources for three AI Gateway components: model service, model provider service, and MCP service. This enables infrastructure-as-code management of AI Gateway deployments through Terraform.
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More from databricks/terraform-provider-databricks
Bump Go toolchain from 1.26.8 to 1.26.10 to pick up updated certificates.
Bump Go toolchain from 1.26.8 to 1.26.10 to pick up updated certificates.
Release v1.139.0 removes six resources and data sources as breaking changes: the databricks_mason_* managed memory store, managed memory entry, session store, and session types, plus databricks_feature_engineering_materialized_feature and databricks_feature_engineering_kafka_config. It adds resources and data sources for databricks_agent_kit_managed_memory_store, databricks_agent_kit_managed_memory_entry, databricks_agent_kit_session_store, and databricks_agent_kit_session.
All Mason resources and data sources have been removed following the underlying API rename to AgentKit. Additionally, the provider has removed the feature engineering Kafka config and materialized feature resources and data sources.
This release adds resources and data sources for private network gateways alongside Mason sessions and managed memory components. The resource exporter expands dependency support to include Lakeflow pipeline settings, model serving endpoints, Databricks Apps, cross-cloud cluster policies, and several new job task types.