---
title: "Release tracks in dbt platform"
source: dbt Core Documentation
source_url: https://github.com/dbt-labs/docs.getdbt.com
licence: Apache-2.0
domain: data-and-analysis
subdomain: dbt-docs
date_added: 2026-04-25
---

Since May 2024, new capabilities in the dbt framework are delivered continuously to <Constant name="dbt" />. Your projects and environments are upgraded automatically on a cadence that you choose, depending on your <Constant name="dbt" /> plan.

Previously, customers would pin to a minor version of <Constant name="core" />, and receive only patch updates during that specific version's active support period. Release tracks ensure that your project stays up-to-date with the modern capabilities of <Constant name="dbt" /> and recent versions of <Constant name="core" />.

This will require you to make one final update to your current jobs and environments. When that's done, you'll never have to think about managing, coordinating, or upgrading dbt versions again.

By moving your environments and jobs to release tracks you can get all the functionality in <Constant name="dbt" /> as soon as it's ready. On the **Latest** release track, this includes access to features _before_ they're available in final releases of <Constant name="core" /> OSS.

## Which release tracks are available?

| Release track | Description | Plan availability | API value |
| ------------- | ----------- | ----------------- | --------- |
| **Latest Fusion**  | The latest build of the new engine for dbt, available to select accounts. | All plans <Lifecycle status="private_preview" /> | `latest-fusion` |
| **Latest** | Provides a continuous release of the latest functionality in the <Constant name="dbt_platform" /> .Includes early access to new features of the dbt framework before they're available in <Constant name="core" />. | All plans | `latest` |
| **Compatible** | Provides a monthly release aligned with the most recent open source versions of dbt Core and adapters, plus functionality exclusively available in the dbt platform.See [Compatible track changelog](/docs/dbt-versions/compatible-track-changelog) for more information. |  Starter, Enterprise, Enterprise+ | `compatible` |
| **Extended** | The previous month's **Compatible** release. | Enterprise, Enterprise+ | `extended` |
| **Fallback** | The previous month's **Extended** release. | Enterprise+ | `fallback` |

To configure an environment in the [dbt Admin API](/docs/dbt-cloud-apis/admin-cloud-api) or [Terraform](https://registry.terraform.io/providers/dbt-labs/dbtcloud/latest) to use a release track, set `dbt_version` to the release track name:
- `latest-fusion` <Lifecycle status="private_preview" />
- `latest`
- `compatible`
- `extended`

## Which release track should I choose?

Choose the **Latest** release track to continuously receive new features, fixes, performance improvements — latest & greatest dbt. This is the default for all customers on <Constant name="dbt" />.

Choose the **Compatible** and **Extended** release tracks if you need a less-frequent release cadence, the ability to test new dbt releases before they go live in production, and/or ongoing compatibility with the latest open source releases of <Constant name="core" />.

### Using the Fallback release track

The **Fallback** release track provides an emergency rollback option for account admins if you suspect a regression in the "Extended" track. 

1. Enable it by going to **Account settings** 
2. Click the **Fallback** release track button in the <Constant name="dbt_platform" /> interface, rather than through environment settings. 
3. Fill in the details in the **Revert to Fallback** pop up to confirm and share any info with dbt Support.

Switching to **Fallback** alerts the dbt Support team, who may reach out to help resolve the issue. This track is meant only as a temporary safety option to unblock you and not for ongoing use. You should return to "Extended" or "Compatible" once the issue is resolved.
<DocCarousel slidesPerView={1}>

<Lightbox src="/img/docs/dbt-versions/rollback.png" width="80%" title="Fallback release track button in dbt platform"/>

<Lightbox src="/img/docs/dbt-versions/rollback-popup.png" width="80%" title="Fallback release track popup in dbt platform"/>

</DocCarousel>


### Common architectures

**Default** - Majority of customers on all plans
- Prioritize immediate access to fixes and features
- Leave all environments on the **Latest** release track (default configuration)

**Hybrid** - Starter, Enterprise, Enterprise+
- Prioritize ongoing compatibility between <Constant name="dbt" /> and <Constant name="core" /> for development & deployment using both products in the same dbt projects
- Configure all environments to use the **Compatible** release track
- Understand that new features will not be available until they are first released in <Constant name="core" /> OSS (several months after the **Latest** release track)

**Cautious** - Enterprise, Enterprise+, Business Critical
- Prioritize "bake in" time for new features & fixes
- Configure development & test environments to use the **Compatible** release track
- Configure pre-production & production environments to use the **Extended** release track
- Understand that new features will not be available until _a month after_ they are first released in <Constant name="core" /> OSS and the Compatible track. Developers (on **Compatible**) will get access to new features before they can leverage those capabilities in production (on **Extended**), and must be mindful of the additional delay.

**Virtual Private dbt or Single Tenant**
- Changes to all release tracks roll out as part of <Constant name="dbt" /> instance upgrades once per week

## Upgrading from older versions

### How to upgrade {#upgrade-tips}

If you regularly develop your dbt project in <Constant name="dbt" />, and you're still running on a legacy version of <Constant name="core" />, dbt Labs recommends that you try upgrading your project in a development environment. [Override your dbt version in development](/docs/dbt-versions/upgrade-dbt-version-in-cloud#override-dbt-version). Then, launch the <Constant name="studio_ide" /> or <Constant name="platform_cli" /> and do your development work as usual. Everything should work as you expect.

If you do see something unexpected or surprising, revert back to the previous version and record the differences you observed. [Contact <Constant name="dbt" /> support](/docs/dbt-support#dbt-cloud-support) with your findings for a more detailed investigation.

Next, we recommend that you try upgrading your project’s [deployment environment](/docs/dbt-versions/upgrade-dbt-version-in-cloud#environments). If your project has a [staging deployment environment](/docs/deploy/deploy-environments#staging-environment), upgrade and try working with it for a few days before you proceed with upgrading the production environment. 

If your organization has multiple dbt projects, we recommend starting your upgrade with projects that are smaller, newer, or more familiar for your team. That way, if you do encounter any issues, it'll be easier and faster to troubleshoot those before proceeding to upgrade larger or more complex projects.

### Considerations

To learn more about how dbt Labs deploys stable dbt upgrades in a safe manner to <Constant name="dbt" />, we recommend that you read our blog post: [How we're making sure you can confidently switch to the \"Latest\" release track in <Constant name="dbt" />](/blog/latest-dbt-stability).

If you're running dbt version 1.6 or older, please know that your version of <Constant name="core" /> has reached [end-of-life (EOL)](/docs/dbt-versions#eol-version-support) and is no longer supported. We strongly recommend that you update to a newer version as soon as reasonably possible.

dbt Labs has extended the critical support period of <Constant name="core" /> v1.7 for <Constant name="dbt" /> Enterprise-tier customers to March 2025. At that point, we will be encouraging all customers to select a Release Track for ongoing updates in <Constant name="dbt" />.

<Expandable alt_header="I'm using an older version of dbt in the dbt platform. What should I do? What happens if I do nothing?" >

If you're running dbt version v1.6 or older, please know that your version of dbt Core has reached [end-of-life (EOL)](/docs/dbt-versions#eol-version-support) and is no longer supported. We strongly recommend that you update to a newer version as soon as reasonably possible.

dbt Labs has extended the "Critical Support" period of dbt Core v1.7 for dbt Enterprise-tier customers while we work through the migration with those customers to Release Tracks. In the meantime, this means that v1.7 will continue to be accessible in dbt for Enterprise customers, jobs and environments on v1.7 for those customers will not be automatically migrated to "Latest," and dbt Labs will continue to fix critical bugs and security issues.

Starting in October 2024, dbt accounts on the Developer and Starter (formerly Teams) plans have been migrated to release tracks from older dbt Core versions. If your account was migrated to the **Latest** release track and you notice new failures in scheduled jobs, please [contact dbt support](/docs/dbt-support#dbt-cloud-support) to report the problem or request an extension.

</Expandable>

<Expandable alt_header="What are other known issues when upgrading from older dbt Core versions?" >

If you are upgrading from a very old unsupported version of dbt Core, you may run into one of these edge cases after the upgrade to a newer version:
- [v1.1] Customers on BigQuery should be aware that <Constant name="dbt" /> sets a default [per-model timeout](/docs/local/connect-data-platform/bigquery-setup#job_execution_timeout_seconds) of 5 minutes. You may override this config in your connection details. Older versions of dbt (including v1.0) did not appropriately respect this timeout configuration.
- [v1.3] Customers with non-dbt `.py` files defined within their project directories, such as `models/`. Since v1.3, dbt expects these files be valid [Python models](/docs/build/python-models). The customer needs to move these files out of their `models/` directory, or ignore them via `.dbtignore`
- [v1.5] Customers who have `--m` in their job definitions, instead of `-m` or `--models`. This autocompletion (`--m[odels]` for `--models`) has never been officially documented or supported. It was an implicit behavior of argparse (CLI library used in dbt-core v1.0-1.4) that is not supported by `click` (the CLI library used in dbt-core since v1.5+).
- [v1.5] Empty invalid `tests` config start raising a validation error](/docs/dbt-versions/core-upgrade/Older%20versions/upgrading-to-v1.5). Replace empty `tests` config with `tests: []` or remove it altogether.
- [v1.6] Performance optimization to `load_result` means you cannot call it on the same query result multiple times. Instead, save it to a local variable once, and reuse that variable (context: [dbt-core#7371](https://github.com/dbt-labs/dbt-core/pull/7371)

You should [contact dbt support](/docs/dbt-support#dbt-cloud-support) to request an extension, during which you will need to make those updates.

</Expandable>

<Expandable alt_header="I see that my account was migrated to Latest. What should I do?" >

For the vast majority of customers, there is no further action needed.

If you see new failures in your scheduled jobs now that they are running on a newer version of dbt, you may need to update your project code to account for one of the edge cases described on this page. You should [contact dbt support](/docs/dbt-support#dbt-cloud-support) to request an extension, during which you will need to make those updates.

</Expandable>

<Expandable alt_header="What about breaking changes to packages (maintained by dbt Labs or by others)?" >

When we talk about _latest version_, we’re referring to the underlying runtime for dbt, not the versions of packages you’re installing. Our continuous release for dbt includes testing against several popular dbt packages. This ensures that updates we make to dbt-core, adapters, or anywhere else are compatible with the code in those packages.

If a new version of a dbt package includes a breaking change (for example, a change to one of the macros in `dbt_utils`), you don’t have to immediately use the new version. In your `packages` configuration (in `dependencies.yml` or  `packages.yml`), you can still specify which versions or version ranges of packages you want dbt to install. If you're not already doing so, we strongly recommend [checking `package-lock.yml` into version control](/reference/commands/deps#predictable-package-installs) for predictable package installs in deployment environments and a clear change history whenever you install upgrades.

If you upgrade to the **Latest** release track, and immediately see something that breaks, please [contact support](/docs/dbt-support#dbt-cloud-support) and, in the meantime, downgrade back to v1.7.

If you’re already on the **Latest** release track, and you observe a breaking change (like something worked yesterday, but today it isn't working, or works in a surprising/different way), please [contact support](/docs/dbt-support#dbt-cloud-support) immediately. Depending on your contracted support agreement, the dbt Labs team will respond within our SLA time and we would seek to roll back the change and/or roll out a fix (just as we would for any other part of dbt). This is the same whether or not the root cause of the breaking change is in the project code or in the code of a package.

If the package you’ve installed relies on _undocumented_ functionality of dbt, it doesn't have the same guarantees as functionality that we’ve documented and tested. However, we will still do our best to avoid breaking them.

</Expandable>

<Expandable alt_header="I see that dbt Core version 1.8 was released in April 2024. Will a version 1.8 become available in the dbt platform?" >

No. Going forward, customers will access new functionality and ongoing support in dbt by receiving automatic updates. We believe this is the best way for us to offer a reliable, stable, and secure runtime for dbt, and for you as dbt users to be able to consistently take advantage of new features.

In 2023 (and earlier), customers were expected to manage their own upgrades by selecting dbt Core versions, up to and including dbt Core v1.7, which was released in October 2023. (Way back in 2021, <Constant name="dbt" /> customers would pick specific _patch releases_ of dbt Core, such as upgrading from `v0.21.0` to `v0.21.1`. We’ve come a long way since then!)

In 2024, we've changed the way that new dbt functionality is made available for <Constant name="dbt" /> customers. Behavior or breaking changes are gated behind opt-in flags. Users don't need to spend valuable time managing their own upgrades. Currently, it is possible to receive continuous (daily) updates. We are adding other release cadence options for managed customers of <Constant name="dbt" /> by the end of the year.

Opting into a release cadence with automated upgrades is required for accessing any new functionality that we've released in 2024, and going forward.

We continue to release new minor versions of dbt Core (OSS). We most recently released dbt Core v1.9 on December 9, 2024. These releases always include a subset of the functionality that's already available to the dbt platform customers, and always after the functionality has been available in the dbt platform.

</Expandable>

If you have comments or concerns, we’re happy to help. If you’re an existing <Constant name="dbt" /> customer, you may reach out to your account team or [contact support](/docs/dbt-support#dbt-cloud-support).
