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more link fixes
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Signed-off-by: nikki everett <[email protected]>
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neverett committed Dec 20, 2024
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Expand Up @@ -22,11 +22,11 @@ The default I/O manager cannot be used if you are a Serverless user who:
- Are otherwise working with data subject to GDPR or other such regulations
:::

In Serverless, code that uses the default [I/O manager](/guides/build/connect-to-external-systems/io-managers) is automatically adjusted to save data in Dagster+ managed storage. This automatic change is useful because the Serverless filesystem is ephemeral, which means the default I/O manager wouldn't work as expected.
In Serverless, code that uses the default [I/O manager](/guides/operate/io-managers) is automatically adjusted to save data in Dagster+ managed storage. This automatic change is useful because the Serverless filesystem is ephemeral, which means the default I/O manager wouldn't work as expected.

However, this automatic change also means potentially sensitive data could be **stored** and not just processed or orchestrated by Dagster+.

To prevent this, you can use [another I/O manager](/guides/build/connect-to-external-systems/io-managers#built-in) that stores data in your infrastructure or [adapt your code to avoid using an I/O manager](/guides/build/connect-to-external-systems/io-managers#before-you-begin).
To prevent this, you can use [another I/O manager](/guides/operate/io-managers#built-in) that stores data in your infrastructure or [adapt your code to avoid using an I/O manager](/guides/operate/io-managers#before-you-begin).

:::note
You must have [boto3](https://pypi.org/project/boto3/) or `dagster-cloud[serverless]` installed as a project dependency otherwise the Dagster+ managed storage can fail and silently fall back to using the default I/O manager.
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Expand Up @@ -115,7 +115,7 @@ TODO: add picture previously at "/images/dagster-cloud/user-token-management/cod
| Start and stop [schedules](/guides/automate/schedules) ||||||
| Start and stop [schedules](/guides/automate/sensors) ||||||
| Wipe assets ||||||
| Launch and cancel [schedules](/guides/build/backfill) ||||||
| Launch and cancel [schedules](/guides/automate/schedules) ||||||
| Add dynamic partitions ||||||

### Deployments
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2 changes: 1 addition & 1 deletion docs/docs-beta/docs/dagster-plus/index.md
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Expand Up @@ -7,7 +7,7 @@ Dagster+ is a managed orchestration platform built on top of Dagster's open sour

Dagster+ is built to be the most performant, reliable, and cost effective way for data engineering teams to run Dagster in production. Dagster+ is also great for students, researchers, or individuals who want to explore Dagster with minimal overhead.

Dagster+ comes in two flavors: a fully [Serverless](/dagster-plus/deployment/deployment-types/serverless) offering and a [Hybrid](/dagster-plus/deployment/deployment-types/hybrid) offering. In both cases, Dagster+ does the hard work of managing your data orchestration control plane. Compared to a [Dagster open source deployment](/guides/), Dagster+ manages:
Dagster+ comes in two flavors: a fully [Serverless](/dagster-plus/deployment/deployment-types/serverless) offering and a [Hybrid](/dagster-plus/deployment/deployment-types/hybrid) offering. In both cases, Dagster+ does the hard work of managing your data orchestration control plane. Compared to a [Dagster open source deployment](/guides/index.md), Dagster+ manages:

- Dagster's web UI at https://dagster.plus
- Metadata stores for data cataloging and cost insights
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Expand Up @@ -10,11 +10,11 @@ Additionally, you may be serving stakeholders who aren't familiar with Python or

Using an asset factory reduces complexity and creates a pluggable entry point to define additional assets.

<details>
<summary>Prerequisites</summary>
:::note

This guide builds upon the concepts in the [asset factories](/guides/build/connect-to-external-systems/asset-factories) tutorial.
</details>
This guide builds on the concepts in the [asset factories](asset-factories) documentation.

:::

---

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Expand Up @@ -71,6 +71,6 @@ flowchart LR

## Next steps

- Learn to create [dependencies between assets](/guides/build/create-asset-pipelines/assets-concepts/asset-dependencies)
- Enrich Dagster's built-in data catalog with [asset metadata](/guides/build/create-asset-pipelines/metadata)
- Learn to use a [factory pattern](/guides/build/connect-to-external-systems/asset-factories) to create multiple, similar assets
- Learn to create [dependencies between assets](/guides/build/create-asset-pipelines/assets-concepts/asset-dependencies)
- Learn to use a [factory pattern](/guides/build/create-asset-pipelines/assets-concepts/asset-factories) to create multiple, similar assets
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Expand Up @@ -62,7 +62,7 @@ Using definition metadata to describe assets can make it easy to provide context

<CodeExample filePath="guides/data-modeling/metadata/definition-metadata.py" language="python" />

To learn more about the different types of metadata you can attach, see the [`MetadataValue`](/todo) API docs.
To learn more about the different types of metadata you can attach, see the [`MetadataValue`](/api/python-api/metadata#class dagster.MetadataValue) API docs.

Some metadata keys will be given special treatment in the Dagster UI. See the [Standard metadata types](#standard-metadata-types) section for more information.

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### Customizing code references \{#custom-references}

If you want to customize how code references are attached - such as when you are building [domain-specific languages with asset factories](/guides/build/connect-to-external-systems/asset-factories) - you can manually add the `dagster/code_references` metadata to asset definitions:
If you want to customize how code references are attached - such as when you are building [domain-specific languages with asset factories](/guides/build/connect-to-external-systems/assets-concepts/asset-factories) - you can manually add the `dagster/code_references` metadata to asset definitions:

<CodeExample filePath="guides/data-modeling/metadata/custom-local-references.py" language="python" />

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import DocCardList from '@theme/DocCardList';

<DocCardList />
<DocCardList />

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