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[Verda] Rename the datacrunch backend to verda (#3359)
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contributing/BACKENDS.md

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@@ -42,7 +42,7 @@ base class. See its docstrings for descriptions of the methods that your class s
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Refer to examples:
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- Offline providers:
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[datacrunch.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/datacrunch.py),
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[verda.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/verda.py),
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[aws.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/aws.py),
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[azure.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/azure.py),
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[lambdalabs.py](https://github.com/dstackai/gpuhunt/blob/main/src/gpuhunt/providers/lambdalabs.py).
@@ -64,7 +64,7 @@ Add your provider in the following places:
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For offline providers, you can add data quality tests under `src/integrity_tests/`.
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Data quality tests are run after collecting offline catalogs to ensure their integrity.
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Refer to examples: [test_datacrunch.py](https://github.com/dstackai/gpuhunt/blob/main/src/integrity_tests/test_datacrunch.py),
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Refer to examples: [test_verda.py](https://github.com/dstackai/gpuhunt/blob/main/src/integrity_tests/test_verda.py),
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[test_gcp.py](https://github.com/dstackai/gpuhunt/blob/main/src/integrity_tests/test_gcp.py).
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### 1.6. Submit a pull request
@@ -125,7 +125,7 @@ Then add these models to `AnyBackendConfig*` unions in [`src/dstack/_internal/co
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The script also generates `*BackendStoredConfig` that extends `*BackendConfig` to be able to store extra parameters in the DB. By the same logic, it generates `*Config` that extends `*BackendStoredConfig` with creds and uses it as the main `Backend` and `Compute` config instead of using `*BackendConfigWithCreds` directly.
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Refer to examples:
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[datacrunch](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/datacrunch/models.py),
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[verda](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/verda/models.py),
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[aws](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/aws/models.py),
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[gcp](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/gcp/models.py),
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[azure](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/models.py), etc.
@@ -136,7 +136,7 @@ Go to `compute.py` and implement `Compute` methods.
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Optionally, extend and implement `ComputeWith*` classes to support additional features such as fleets, volumes, gateways, placement groups, etc. For example, extend `ComputeWithCreateInstanceSupport` to support fleets.
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Refer to examples:
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[datacrunch](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/datacrunch/compute.py),
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[verda](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/verda/compute.py),
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[aws](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/aws/compute.py),
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[gcp](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/gcp/compute.py),
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[azure](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/azure/compute.py), etc.
@@ -146,7 +146,7 @@ Refer to examples:
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Go to `configurator.py` and implement custom `Configurator` logic. At minimum, you should implement creds validation.
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You may also need to validate other config parameters if there are any.
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Refer to examples: [datacrunch](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/datacrunch/configurator.py),
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Refer to examples: [verda](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/verda/configurator.py),
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[aws](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/aws/configurator.py),
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[gcp](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/gcp/configurator.py),
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[azure](https://github.com/dstackai/dstack/blob/master/src/dstack/_internal/core/backends/azure/configurator.py), etc.
@@ -195,7 +195,7 @@ For some VM-based backends, the `dstack` team also maintains
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[custom VM images](../scripts/packer/README.md) with the required dependencies
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and `dstack`-specific optimizations.
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Examples of VM-based backends include: `aws`, `azure`, `gcp`, `lambda`, `datacrunch`, `tensordock`, etc.
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Examples of VM-based backends include: `aws`, `azure`, `gcp`, `lambda`, `verda`, etc.
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#### 3.1.2. Container-based backend compute type
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contributing/GPUHUNT.md

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@@ -65,7 +65,7 @@ Some providers offer extreme flexibility in possible configurations, but not all
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- Filters out if: outdated family, not supported family
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- Queries configuration details to fill CPU, RAM, and GPU information
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### DataCrunch
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### Verda
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- Just queries all offers via API
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docs/assets/images/verda-logo.svg

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docs/docs/concepts/backends.md

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@@ -854,9 +854,11 @@ There are two ways to configure OCI: using client credentials or using the defau
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compartment_id: ocid1.compartment.oc1..aaaaaaaa
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```
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### DataCrunch
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<span id="datacrunch"></span>
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Log into your [DataCrunch](https://cloud.datacrunch.io/) account, click Keys in the sidebar, find `REST API Credentials` area and then click the `Generate Credentials` button.
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### Verda (formerly DataCrunch) { #verda }
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Log into your [Verda](https://console.verda.com/signin) account, click Keys in the sidebar, find `REST API Credentials` area and then click the `Generate Credentials` button.
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Then, go ahead and configure the backend:
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docs/docs/reference/server/config.yml.md

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@@ -258,18 +258,18 @@ to configure [backends](../../concepts/backends.md) and other [server-level sett
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type:
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required: true
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##### `projects[n].backends[type=datacrunch]` { #datacrunch data-toc-label="datacrunch" }
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##### `projects[n].backends[type=verda]` { #verda data-toc-label="verda" }
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#SCHEMA# dstack._internal.core.backends.datacrunch.models.DataCrunchBackendConfigWithCreds
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#SCHEMA# dstack._internal.core.backends.verda.models.VerdaBackendConfigWithCreds
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overrides:
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show_root_heading: false
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type:
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required: true
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item_id_prefix: datacrunch-
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item_id_prefix: verda-
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###### `projects[n].backends[type=datacrunch].creds` { #datacrunch-creds data-toc-label="creds" }
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###### `projects[n].backends[type=verda].creds` { #verda-creds data-toc-label="creds" }
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#SCHEMA# dstack._internal.core.backends.datacrunch.models.DataCrunchAPIKeyCreds
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#SCHEMA# dstack._internal.core.backends.verda.models.VerdaAPIKeyCreds
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overrides:
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show_root_heading: false
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type:

docs/partners.md

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@@ -95,9 +95,9 @@ hide:
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</span> -->
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<span class="feature-cell" target="_blank">
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<img width="52" style="margin: 10px -4px;" src="/assets/images/datacrunch-logo.svg">
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<img width="42" src="/assets/images/verda-logo.svg">
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<h3>
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DataCrunch
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Verda
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</h3>
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</span>
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</div>

pyproject.toml

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@@ -32,7 +32,7 @@ dependencies = [
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"python-multipart>=0.0.16",
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"filelock",
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"psutil",
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"gpuhunt==0.1.14",
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"gpuhunt==0.1.15",
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"argcomplete>=3.5.0",
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"ignore-python>=0.2.0",
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"orjson",
@@ -186,7 +186,11 @@ gcp = [
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"dstack[server]",
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]
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datacrunch = [
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"datacrunch",
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"verda; python_version >= '3.10'",
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"dstack[server]",
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]
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verda = [
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"verda; python_version >= '3.10'",
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"dstack[server]",
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]
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kubernetes = [
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"dstack[server]",
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]
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all = [
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"dstack[gateway,server,aws,azure,gcp,datacrunch,kubernetes,lambda,nebius,oci]",
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"dstack[gateway,server,aws,azure,gcp,verda,kubernetes,lambda,nebius,oci]",
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]

src/dstack/_internal/core/backends/base/offers.py

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@@ -39,6 +39,8 @@ def get_catalog_offers(
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catalog: Optional[gpuhunt.Catalog] = None,
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) -> List[InstanceOffer]:
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provider = backend.value
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if backend == BackendType.DATACRUNCH:
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provider = BackendType.VERDA.value # Backward compatibility
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if backend == BackendType.LAMBDA:
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provider = "lambdalabs"
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if backend == BackendType.AMDDEVCLOUD:

src/dstack/_internal/core/backends/configurators.py

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@@ -127,6 +127,15 @@
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except ImportError:
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pass
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try:
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from dstack._internal.core.backends.verda.configurator import (
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VerdaConfigurator,
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)
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_CONFIGURATOR_CLASSES.append(VerdaConfigurator)
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except ImportError:
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pass
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try:
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from dstack._internal.core.backends.vultr.configurator import VultrConfigurator
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# DataCrunch backend for backward compatibility

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