Releasesby GlyphModal 1.5.3
- We've added new APIs for programmatically retrieving logs on several object types: Function, Server, and FunctionCall. Each object exposes three different methods, allowing you to stream() logs as they are generated, fetch() logs from a specific date/time range, or tail() the most recent logs.
Also shipped Jul 23, 2026Modal in July 2026 →
SQL environment variable and private Git package support for dbt Projects on Snowflake
Environment variable support for dbt Projects on Snowflake is now generally available. Manage per-developer schemas, dynamic runtime values, secrets, and multiple environments in a single, Git-versioned env.yml file that Snowflake resolves before each run.
SERVICE_AGENT user type (General availability)
With this release, the SERVICE_AGENT user type is generally available. Use this user type for automated AI agents that interact with Snowflake using their own identity and privileges.
SHOW CORTEX BASE MODELS command (General availability)
With this release, we are pleased to announce the general availability of the SHOW CORTEX BASE MODELS command. Use this command to list the Cortex Base Models available in your account, along with each model’s lifecycle status, regional availability, legacy date, and end-of-life date.
C++ SDK for the Zerobus Ingest connector is now available in Beta
A C++ SDK for the Zerobus Ingest connector in Lakeflow Connect is now available in Beta. The SDK provides a high-throughput gRPC client for ingesting records directly into Unity Catalog Delta tables, with support for JSON and Protocol Buffers. See Use Zerobus Ingest .
Genie Code scheduled tasks are in Beta
You can now schedule Genie Code to run a prompt on a recurring schedule. Each run executes your prompt as a full Genie Code session and produces a continuable Genie chat with the results, so you can turn recurring analysis into an unattended background task. Create a scheduled task by asking Genie Code in chat or by filling in the create form manually.
Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are now generally available
Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are now generally available (GA), powered by Apache Spark 4.2.0. For release notes, see Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning .
More from ModalEvery Modal release →
Modal 1.5.2
- We've added new interfaces for programmatic management of workspace settings: Use the modal.Workspace.settings.list() method or modal workspace settings list CLI to see current workspace-level settings. Use the modal.Workspace.settings.set() method or modal workspace settings set CLI to configure new values.
Modal 1.5.4
With this release, it's now possible to opt into a more performant Sandbox backend, which affords substantially higher creation rates and concurrency. Set MODAL_SANDBOX_V2=1 as an environment variable and your Sandboxes will use this new system without any code changes. This will become the default behavior in version 1.6.0 of the Python SDK.
Modal 1.5.1
This release includes several major new features, including the debut of a new serverless compute primitive for low-latency HTTP applications (@app.server()) and a new CLI for deploying production-ready LLM inference endpoints with minimal configuration (modal endpoint).
Modal 1.5.5
- We've added a modal.Sandbox.logs API, allowing you to fetch() logs from a specific date/time range or to tail() the most recent logs. Note that only logs from the entrypoint process of a Sandbox are currently stored, and streaming logs via this interface is not currently supported.
Modal 1.5.0
This is a major release that includes several new features (named Images, version-pinned Function lookups, Sandbox domain allowlists), a new modal skills CLI, and a small number of breaking changes. We're introducing a "named Image" concept, akin to a Modal-native Image registry.
Modal 1.4.3
- This release introduces a new "regional routing" concept for Function inputs, which is now in Public Beta. By setting routing_region="..." in the @app.function() or @app.cls() decorators, you can configure the Function to route its inputs through servers in us-west, eu-west, or ap-south instead of us-east.
Modal 1.6.0
Sandboxes now use our next-generation backend, affording substantially higher creation rates and concurrency limits for CPU Sandboxes. No code changes are required, but there are some semantic differences to be aware of: The modal.Sandbox.create() method now blocks until the Sandbox is scheduled instead of returning immediately.
Modal 1.6.1
- We've added CLI commands for observability over Modal Endpoints: modal endpoint info displays basic metadata. modal endpoint stats reports aggregate performance metrics. modal endpoint logs fetches or streams logs.