Releasesby IbisManage Neki router parameters with Terraform
UpdateyesterdayUnverifiedAdded Oct 15, 2026
The PlanetScale Terraform provider v1.13.0 adds parameter management to planetscale_neki_router . You can configure router settings in Terraform and read them through the router data source.
Topics: Data integration, Postgres, Developer tools
More PlanetScale releases
Every PlanetScale releaseCLI shows which Postgres and Neki parameters need an update
The PlanetScale CLI v0.346.0 shows when a parameter requires an update before you can configure it. Parameter listings now include a Requires update column for Postgres branches, and for Neki configuration profiles, admins, and sidecars.
PlanetScale is now available on Azure
We've added Microsoft Azure as a cloud provider. You can now create PlanetScale Postgres and Neki databases in Azure regions, alongside the AWS and Google Cloud regions we already support. Vitess databases are not currently available on Azure. To get started, choose Azure as the cloud provider when creating a new database, then pick a region.
Vitess aggressive cutover for a single deploy request
You can now opt a single deploy request into aggressive cutover from the CLI and API. pscale deploy-request create --aggressive-cutover pscale deploy-request update --aggressive-cutover pscale deploy-request update --aggressive-cutover=false You can change this any time before you deploy the schema change.
MCP server: Branch metrics
The PlanetScale MCP server can now check your database's metrics. planetscale_get_branch_metrics pulls CPU, memory, disk, replication lag, and connections into your AI assistant, so you can see those numbers without leaving your editor. It works for Vitess, Postgres, and Neki.
Retry a partially failed deploy request
Vitess deploy request's now have the ability to recover from partial failures. If part of a migration has failed, the deploy request page will now provide the option to retry the failing tables instead of starting the entire deploy over. Retry will restart the migration for only the failed tables.
Limit MCP query access for an organization
Organization administrators can now limit the database query access members grant to MCP clients. In organization settings, MCP query access can be set to no query access, read-only queries, or read and write queries. This applies the next time someone authorizes an MCP client.
Postgres dedicated read replicas
PlanetScale Postgres now supports independently configurable dedicated read replicas. Create one or more dedicated read replicas in the primary region or another region from the same cloud provider. Configure the cluster size, replica count, storage, and supported Postgres parameters independently from the primary cluster.
New reparent metrics for Prometheus
We've added two Prometheus metrics that show when a shard's primary changed, and why: planetscale_vitess_planned_reparents_total counts planned reparents, such as the ones that happen during maintenance or when you request one.
Also shipped on Oct 14, 2026
PlanetScale in October 2026Workspace-level package repositories for Databricks Apps are generally available
Workspace admins can now configure default Python and npm package repositories for Databricks Apps. Apps inherit the workspace configuration while still allowing app-level overrides. See Configure default package repositories .
The Apache Hive catalog endpoint in the Lakehouse runtime catalog is now generally available (GA)
The Apache Hive catalog endpoint in the Lakehouse runtime catalog is now generally available (GA). This integration lets you use the metastore as a serverless, central metadata layer, enabling seamless data sharing and unified querying across Apache Spark, Apache Hive, and BigQuery.
Metadata migration from Dataproc Metastore to Lakehouse is now generally available (GA)
Metadata migration from Dataproc Metastore to Lakehouse is now generally available (GA). You can perform a one-time backfill migration or dry run to migrate metadata from a Dataproc Metastore service to an Apache Iceberg REST catalog endpoint or a Hive catalog endpoint using the Google Cloud console, the gcloud CLI, or the REST API.
Conversational analytics now lets you create a conversation with all of the data sources in multiple...
Conversational analytics now lets you create a conversation with all of the data sources in multiple projects, or create a conversation with a dataset . These features are generally available (GA).
You can publish a BigQuery Conversational Analytics agent in Gemini Enterprise
You can publish a BigQuery Conversational Analytics agent in Gemini Enterprise . This feature is now generally available (GA).
The AI.AGG function now supports the output_schema argument, which lets you specify the schema of the...
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