Schema Linking on Confluent Cloud¶

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Schema Registry now supports Schema Linking. The following video and documentation explain the concepts, configurations, and tools you need to get started using Schema Linking in your Confluent deployments. The quick start guides you step-by-step with hands-on examples of how to create and use exporters to implement schema linking on your clusters.

Tip

The video below focuses on Schema Linking on Confluent Cloud, but the feature is also available on Confluent Enterprise, with Confluent Platform specific setup, commands, and workflow, as described in the Confluent Platform Schema Linking Quick Start. Schema Linking on Confluent Cloud and on Confluent Platform share the core concepts and mechanisms of schema contexts, exporters, configuration options, exporter lifecycle, and REST APIs.

What is Schema Linking?¶

Schema Linking keeps schemas in sync across two Schema Registry clusters. Schema Linking can be used in conjunction with Cluster Linking to keep both schemas and topic data in sync across two Schema Registry and Kafka clusters.

Schema Registry introduces two new concepts to support Schema Linking:

Schema contexts - A schema context represents an independent scope in Schema Registry, and can be used to create any number of separate “sub-registries” within one Schema Registry cluster. Each schema context is an independent grouping of schema IDs and subject names, allowing the same schema ID in different contexts to represent completely different schemas. Any schema ID or subject name without an explicit context lives in the default context, denoted by a single dot .. An explicit context starts with a dot and can contain any parts separated by additional dots, such as .mycontext.subcontext. Context names operate similar to absolute Unix paths, but with dots instead of forward slashes (the default schema is like the root Unix path). However, there is no relationship between two contexts that share a prefix.
Schema exporters - A schema exporter is a component that resides in Schema Registry for exporting schemas from one Schema Registry cluster to another. The lifecycle of a schema exporter is managed through APIs, which are used to create, pause, resume, and destroy a schema exporter. A schema exporter is like a “mini-connector” that can perform change data capture for schemas.

The Quick Start below shows you how to get started using schema exporters and contexts for Schema Linking.

For in-depth descriptions of these concepts, see Schema Contexts and Schema Exporters

Quick Start¶

If you’d like to jump in and try out Schema Linking now, follow the steps below. At the end of the Quick Start, you’ll find deep dives on contexts, exporters, command options, and APIs, which may make more sense after you’ve experimented with some hands-on examples.

Get the latest version of the Confluent CLI¶

Got Confluent CLI? Make sure it’s up-to-date.

If you are still running the legacy Confluent Cloud CLI, run ccloud update --major to get prompts for available updates and upgrade directly to confluent v2.0.

If you already have the new unified CLI, run confluent update. The unified CLI enables you to use confluent instead of ccloud in commands. Once you’ve upgraded, check out this handy unified CLI confluent commands reference available here.
To learn more about the new unified CLI and migration paths, see Install Confluent CLI, Migrate to Confluent CLI v2, and Run multiple CLIs in parallel.

These are the Schema Linking features that should be available in the latest version of the CLI:

New Features
-------------
  - Support for passing Schema Registry API key and secret in produce/consume commands
  - New Schema linking commands under ``confluent schema-registry exporter``

To get CLI help on the exporter directly in the terminal, type confluent schema-registry exporter

Set up two Schema Registry clusters in source and destination environments¶

Log on to Confluent Cloud, and create two new environments: one named “SOURCE” and the other named “DESTINATION”.

Navigate to Environments (top right menu), click Add cloud environment, and follow the steps.
Add a Kafka cluster to each environment so that you can enable Schema Registry in each environment (for example “my-cluster-on-source” in the SOURCE environment, and “my-cluster-on-destination” in the DESTINATION environment.) These can be any cluster type.

You can do this through the Confluent CLI or the Confluent Cloud Console.
- On the Cloud Console, click Add cluster in an environment and follow the steps to name and create the cluster.
- On the CLI, type confluent environment list, then confluent environment use <environment-id> to navigate to each environment, and then create the clusters in the appropriate environments.
  
  For example, in the SOURCE environment:
```
confluent kafka cluster create my-cluster-on-source --type basic --cloud gcp --region us-east1
```
  And in the DESTINATION environment:
```
confluent kafka cluster create my-cluster-on-destination --type basic --cloud gcp --region us-west1
```
Set up a Schema Registry in each environment and take note of its API endpoint.
- In each environment, navigate to the Schema Registry tab on the Cloud Console, click Set up my own, and follow the prompts. The Schema Registry tab should display when the registry is created.
- On the Schema Registry tabs for both source and destination, copy and save the API endpoints for each.
Create an API key and secret for interacting with the Schema Registry clusters on both source and destination clusters.

Navigate to the Schema Registry tab, click the edit icon under API credentials, and follow the prompts. Be sure to save your key and secret pairs for both source and destination. You will not be able to retrieve the secrets later.
Review source and destination access information.

By now you should have a triplet of Schema Registry access details for both source and destination clusters, which you will use in the following steps:
- Schema Registry URL (the API endpoint)
- API key
- API secret
Tip

URLs (endpoints) for source and destination specify the physical Schema Registry clusters. The URLs can be the same if the schema registries are on the same physical cluster. They are different logical clusters, and will be identified by the different API key/secret pairs. The URLs will be different if the registries are on different physical clusters.

Create schemas on the source¶

Create at least two or three schemas in the source environment; at least one of which has a qualified subject name.

To create each schema from the Cloud Console, follow these steps:

From the Schema Registry tab in the SOURCE environment, Click Schemas on the right panel for an environment, then Add schema.
Fill in the subject name.
- To create a schema with an unqualified subject name, simply provide a name such as coffee or donuts.
- To create a schema with a qualified subject name in a specified context, use the syntax: :.<context-name>:<subject-name>. For example: :.snowcones:sales or :.burgers:locations
Take the default schema in each case.

For this Quick Start, you are not working with the schemas themselves, but rather learning how to work with subject names and contexts. Therefore, you can just take the default schema to save time, unless you want to use a specific schema for your own purposes.
Click Create.

Create credentials for the exporter¶

Your schema exporter will be reading schemas in the source environment and exporting linked copies to the destination, so it needs credentials to access the destination.

Create ~/config.txt which you will use to create exporters, and fill in the URL and credentials the exporter needs to access the DESTINATION cluster:

schema.registry.url=<destination sr url>
basic.auth.credentials.source=USER_INFO
basic.auth.user.info=<destination api key>:<destination api secret>

Important

For Schema Linking, always use API keys tied to service accounts, not users. For now, you must use the CLI to create API keys tied to service accounts, as the Confluent Cloud Console does not currently support service accounts for Schema Linking. To learn more, see Create a resource-specific API key and Best Practices for Using API Keys in Confluent Cloud.
These are the credentials the exporter will use to access the destination. You will still need to provide source and destination credentials to run commands in these environments, as noted at particular points in the steps below.

Create the exporter on the source¶

For these Quick Start examples, you’ll want to create the exporters on the source, so make sure your current environment is SOURCE.

You can use confluent environment list and confluent environment use <environment-id> to navigate.
Create a new exporter using the confluent schema-registry exporter create command.

For this demo, you want the exporter to copy all schemas, including those in specific contexts (other than the default), so include the --subjects flag with the context wildcard to denote subjects under all contexts: --subjects ":*:":
```
confluent schema-registry exporter create <exporter-name> --subjects ":*:" --config-file ~/config.txt
```
For example, this command creates an exporter called “my-first-exporter” that will export all schemas, including those in specific contexts as well as those in the default context:
```
confluent schema-registry exporter create my-first-exporter --subjects ":*:" --config-file ~/config.txt
```
Enter your source API key and secret when prompted for them.

You should get output verifying that the exporter was created: Created schema exporter "my-first-exporter".

More options for exporters¶

The exporter you just created is relatively basic, in that it just exports everything. As you’ll see in the next section, this is an efficient way to get an understanding of how you might organize, export, and navigate schemas with qualified and unqualified subject names.

Keep in mind that you can create exporters that specify to export only specific subjects and contexts using this syntax:

confluent schema-registry exporter create <exporterName> --subjects <subjectName1>,<subjectName2> \
--context-type CUSTOM --context-name <contextName> \
--config-file ~/config.txt

Replace anything within <> with a name you like.
subjects are listed as a comma-separated string list, such as “pizzas,sales,customers”.
subjects, context-type, and context-name are all optional. context-name is specified if context-type is CUSTOM.
subjects defaults to *, and context-type defaults to AUTO.

Alternatively, if you take all the defaults and do not specify --subjects when you create an exporter, you will get an exporter that only exports schemas in the default context:

confluent schema-registry exporter create my-first-exporter --config-file ~/config.txt

With this type of exporter, schemas on the source that have qualified subject names will not be exported to the destination.

Another optional parameter you can use with confluent schema-registry exporter create and confluent schema-registry exporter update is --subject-format. This specifies a format for the subject name in the destination cluster, and may contain ${subject} as a placeholder which will be replaced with the default subject name. For example, dc_${subject} for the subject orders will map to the destination subject name dc_orders.

You can create and run multiple exporters at once, so feel free to circle back at the end of the Quick Start to create and test more exporters with different parameters.

See Configuration Options for full details on schema exporter parameters.

Verify the exporter is running and view information about it¶

Still in the SOURCE environment, run the following commands.

List available exporters.
```
confluent schema-registry exporter list
```
Your exporter will show in the list.

Describe the exporter.

confluent schema-registry exporter describe <exporterName>

Your output should resemble:

confluent schema-registry exporter describe my-first-exporter
+--------------------------------+--------------------------------------------------------------------------+
| Name                           | my-first-exporter                                                        |
| Subjects                       | *                                                                        |
| Context Type                   | AUTO                                                                     |
| Context                        |                                                                        . |
| Remote Schema Registry Configs | basic.auth.credentials.source="USER_INFO"                                |
|                                | basic.auth.user.info="[hidden]"                                          |
|                                | schema.registry.url="https://psrc-0xx5p.us-central1.gcp.confluent.cloud" |
+--------------------------------+--------------------------------------------------------------------------+

Get configurations for the exporter.

confluent schema-registry exporter get-config <exporterName>

Get the status of exporter.

confluent schema-registry exporter get-status <exporterName>

Finally, as a check, get a list of schemas on the source.

Use the prefix wildcard to list all schemas:
```
confluent schema-registry subject list --prefix ":*:"
```
With the wildcard, this is effectively the same as the command: confluent schema-registry subject list The command will return the list of subjects you’ve created on the source, for example:
```
        Subject
+---------------------+
  :.burgers:locations
  :.snowcones:sales
  coffee
  customers
  donuts
```

Check that the schemas were exported¶

Now that you have verified that the exporter is running, and you know which schemas you created on the source, check to see that your schemas were exported to the destination.

Switch to the DESTINATION.

Use confluent environment list and confluent environment use <environment-id> to navigate.
Run the following command to view all schemas, providing your API key and secret for the DESTINATION when prompted.
```
confluent schema-registry subject list --prefix ":*:"
```
Notice how the context is passed as the subject prefix when querying. The example above uses the context wildcard :*: to match all contexts. It is, in effect, the same as the generic command confluent schema-registry subject list, but a more explicit subject prefix could be used to pass a specific context.

Your output list of schemas on the DESTINATION should match those on the SOURCE.
```
          Subject
+--------------------------------+
  :.lsrc-3qy52.burgers:locations
  :.lsrc-3qy52.snowcones:sales
  :.lsrc-3qy52:coffee
  :.lsrc-3qy52:customers
  :.lsrc-3qy52:donuts
```

List only schemas in particular contexts.

One you have a list of all subjects on the destination with the prefixes (as in the above example), you can pass only the context name to see a narrowed list of subjects in a particular context.

For example, to list schemas in the burgers context:

confluent schema-registry subject list --prefix ":.lsrc-3qy52.burgers:"

The output will be:

             Subject
+--------------------------------+
  :.lsrc-3qy52.burgers:locations

To list schemas in the snowcones context:

confluent schema-registry subject list --prefix ":.lsrc-3qy52.snowcones:"

The output will be:

             Subject
+------------------------------+
  :.lsrc-3qy52.snowcones:sales

Tip

If you used the optional parameter --subject-format when you created the exporter on the source, check to see that the exported subjects on the destination map to the subject rename format you specified.

You use the same curl commands to call the APIs. Here is an example:

curl -u <destination api key>:<destination api secret> '<destination sr url>/subjects?subjectPrefix=:.context1:foo'

Pause the exporter and make changes¶

Pause the exporter.

Switch back to the SOURCE, and run the following command to pause the exporter.

confluent schema-registry exporter pause <exporterName>

You should get output verifying that the command was successful. For example: Paused schema exporter "my-first-exporter".

Check the status, just to be sure.

confluent schema-registry exporter get-status <exporterName>

Your output should resemble:

confluent schema-registry exporter get-status my-first-exporter
+--------------------+-------------------+
| Name               | my-first-exporter |
| Exporter State     | PAUSED            |
| Exporter Offset    |          10011386 |
| Exporter Timestamp |     1631107710822 |
| Error Trace        |                   |
+--------------------+-------------------+

Reset schema exporter offset, then get the status.

confluent schema-registry exporter reset <exporterName>

confluent schema-registry exporter get-status <exporterName>

The status will show that the offset is reset. For examples:

confluent schema-registry exporter get-status my-first-exporter
+--------------------+-------------------+
| Name               | my-first-exporter |
| Exporter State     | PAUSED            |
| Exporter Offset    |                -1 |
| Exporter Timestamp |                 0 |
| Error Trace        |                   |
+--------------------+-------------------+

Update exporter configurations or information.

You can choose to update any of subjects, context-type, context-name, or config-file. For example:
```
confluent schema-registry exporter update <exporterName> --context-name <newContextName>
```

Resume schema exporter.

confluent schema-registry exporter resume <exporterName>

Delete the exporter¶

When you are ready to wrap up your testing, pause and then delete the exporter(s) as follows.

Pause the exporter.

confluent schema-registry exporter pause <exporterName>

Delete the exporter.

confluent schema-registry exporter delete <exporterName>

This concludes the Quick Start. The next sections are a deep dive into Schema Linking concepts and tools you just tried out.

Schema Contexts¶

What is a schema context?¶

A schema context, or simply context, is essentially a grouping of subject names and schema IDs. A single Schema Registry cluster can host any number of contexts. Each context can be thought of as a separate “sub-registry”. A context can also be copied to another Schema Registry cluster, using a schema exporter.

How contexts work¶

Following are a few key aspects of contexts and how they help to organize schemas.

Schemas and schema IDs are scoped by context¶

Subject names and schema IDs are scoped by context so that two contexts in the same Schema Registry cluster can each have a schema with the same ID, such as 123, or a subject with the same name, such as mytopic-value, without any problem.

To put this another way, subject names and schema IDs are unique per context. You can have schema ID 123 in context .mycontext and schema ID 123 in context .yourcontext and these can be different from one another.

Default context¶

Any schema ID or subject name without an explicit context lives in the default context, which is represented as a single dot .. An explicit context starts with a dot and can contain any parts separated by additional dots, such as .mycontext.subcontext. You can think of context names as similar to absolute Unix paths, but with dots instead of forward slashes (in this analogy, the default schema context is like the root Unix path). However, there is no relationship between two contexts that share a prefix.

Qualified subjects¶

A subject name can be qualified with a context, in which case it is called a qualified subject. When a context qualifies a subject, the context must be surrounded by colons. An example is :.mycontext:mysubject. A subject name that is unqualified is assumed to be in the default context, so that mysubject is the same as :.:mysubject (the dot representing the default context).

There are two ways to pass a context to the REST APIs.

Using a qualified subject
Using a base context path

Using a qualified subject¶

A qualified subject can be passed anywhere that a subject name is expected. Most REST APIs take a subject name, such as POST /subjects/{subject}/versions.

There are a few REST APIs that don’t take a subject name as part of the URL path:

/schemas/ids/{id}
/schemas/ids/{id}/subjects
/schemas/ids/{id}/versions

The three APIs above can now take a query parameter named “subject” (written as ?subject), so you can pass a qualified subject name, such as /schemas/ids/{id}?subject=:.mycontext:mysubject, and the given context is then used to look up the schema ID.

Using a base context path¶

As mentioned, all APIs that specify an unqualified subject operate in the default context. Besides passing a qualified subject wherever a subject name is expected, a second way to pass the context is by using a base context path. A base context path takes the form /contexts/{context} and can be prepended to any existing Schema Registry path. Therefore, to look up a schema ID in a specific context, you could also use the URL /contexts/.mycontext/schemas/ids/{id}.

A base context path can also be used to operate with the default context. In this case, the base context path takes the form “/contexts/:.:/”; for example, /contexts/:.:/schemas/ids/{id}. A single dot cannot be used because it is omitted by some URL parsers.

Multi-Context APIs¶

All the examples so far operate in a single context. There are three APIs that return results for multiple contexts.

/contexts
/schemas?subjectPrefix=:*:
/subjects?subjectPrefix=:*:

The first API above, /contexts, returns a list of all contexts. The other two APIs, /schemas and /subjects, normally only operate in the default context. They can be used to query all contexts by passing a subjectPrefix with the value :*:, called the context wildcard. The context wildcard matches all contexts.

Specifying a context name for clients¶

When using a client to talk to Schema Registry, you may want the client to use a particular context. An example of this scenario is when migrating a client from communicating with one Schema Registry to another. You can achieve this by using a base context path, as defined above. To do this, simply change the Schema Registry URL used by the client from https://<host1> to https://<host2>/contexts/.mycontext.

Note that by using a base context path in the Schema Registry URL, the client will use the same schema context for every Schema Registry request. However, an advanced scenario might involve a client using different contexts for different topics. To achieve this, you can specify a context name strategy to the serializer or deserializer:

context.name.strategy=com.acme.MyContextNameStrategy

The context name strategy is a class that must implement the following interface:

/**
 * A {@link ContextNameStrategy} is used by a serializer or deserializer to determine
 * the context name used with the schema registry.
 */
public interface ContextNameStrategy extends Configurable {

  /**
   * For a given topic, returns the context name to use.
   *
   * @param topic The Kafka topic name.
   * @return The context name to use
   */
  String contextName(String topic);
}

Again, the use of a context name strategy should not be common. Specifying the base context path in the Schema Registry URL should serve most needs.

Schema Exporters¶

What is a Schema Exporter?¶

Previously, Confluent Replicator was the primary means of migrating schemas from one Schema Registry cluster to another, as long as the source Schema Registry cluster was on-premise. To support schema migration using this method, the destination Schema Registry is placed in IMPORT mode, either globally or for a specific subject.

The new schema exporter functionality replaces and extends the schema migration functionality of Replicator. Schema exporters reside within a Schema Registry cluster, and can be used to replicate schemas between two Schema Registry clusters in Confluent Cloud.

Schema Linking¶

You use schema exporters to accomplish Schema Linking, using contexts and/or qualified subject names to sync schemas across registries. Schema contexts provide the conceptual basis and namespace framework, while the exporter does the heavy-lift work of the linking.

Schemas export from the source default context to a new context on the destination¶

By default, a schema exporter exports schemas from the default context in the source Schema Registry to a new context in the destination Schema Registry. The destination context (or a subject within the destination context) is placed in IMPORT mode. This allows the destination Schema Registry to use its default context as usual, without affecting any clients of its default context.

The new context created by default in the destination Schema Registry will have the form .lsrc-xxxxxx, taken from the logical name of the source.

Schema Registry clusters can export schemas to each other¶

Two Schema Registry clusters can each have a schema exporter that exports schemas from the default context to the other Schema Registry. In this setup, each side can read from or write to the default context, and each side can read from (but not write to) the exported context. This allows you to match the setup of Cluster Linking, where you might have a source topic and a read-only mirror topic on each side.

An exporter can copy schemas across contexts in the same Schema Registry¶

In addition, a schema exporter can copy schemas from one context to another within the same Schema Registry cluster. For example, you might create a “.staging” context, and then later copy the schemas from the “.staging” context to the default context when production-ready. When copying schemas to and from the same Schema Registry cluster, use the special URL local:///.

Customizing schema exports¶

There are various ways to customize which contexts are exported from the source Schema Registry, and which contexts are used in the destination Schema Registry. The full list of configuration properties is shown below.

How many exporters are allowed per Schema Registry?¶

The limit on the number of exporters allowed at any one time per Schema Registry is 10.

Configuration Options¶

A schema exporter has these main configuration properties:

name

A unique name for the exporter.

subjects

This can take several forms:

A list of subject names and/or contexts, for example: [ "subject1", "subject2", ".mycontext1", ".mycontext2" ]
A singleton list containing a subject name prefix that ends in a wildcard, such as ["mytopic*"]
A singleton list containing a lone wildcard, ["*"], that indicates all subjects in the default context. This is the default.
A singleton list containing the context wildcard, [":*:"], that indicates all contexts.

subject-format

This is an optional parameter you can use to specify a format for the subject name in the destination cluster. You can specify ${subject} as a placeholder, which will be replaced with the default subject name. For example, dc_${subject} for the subject orders will map to the destination subject name dc_orders.

context-type

One of:

AUTO - Prepends the source context with an automatically generated context, which is .lsrc-xxxxxx for Confluent Cloud. This is the default.
CUSTOM - Prepends the source context with a custom context name, specified in context below.
NONE - Copies the source context as-is, without prepending anything. This is useful to make an exact copy of the source Schema Registry in the destination.

context-name

A context name to be used with the CUSTOM contextType above.

config

A set of configurations for creating a client to talk to the destination Schema Registry, which can be passed in a config file (for example, --config-file ~/<my-config>.txt). Typically, this includes:

schema.registry.url - The URL of the destination Schema Registry. This can also be local:/// to allow for more efficient copying if the source and destination are the same.
basic.auth.credentials.source - Typically “USER_INFO”
basic.auth.user.info - Typically of the form <api-key>:<api-secret>

System Topics and Security Configurations¶

The following configurations for system topics are available:

exporter.config.topic - Stores configurations for the exporters. The default name for this topic is _exporter_configs, and its default/required configuration is: numPartitions=1, replicationFactor=3, and cleanup.policy=compact.
exporter.state.topic - Stores the status of the exporters. The default name for this topic is _exporter_states, and its default/required configuration is: numPartitions=1, replicationFactor=3, and cleanup.policy=compact.

If you are using role-based access control (RBAC), exporter.config.topic and exporter.state.topic require ResourceOwner on these topics, as does the _schemas internal topic. See also, Use Role-Based Access Control (RBAC) in Confluent Cloud and Configuring Role-Based Access Control for Schema Registry on Confluent Platform.

If you are configuring Schema Registry on Confluent Platform using the Schema Registry Security Plugin, you must activate both the exporter and the Schema Registry security plugin by specifying both extension classes in the $CONFLUENT_HOME/etc/schema-registry/schema-registry.properties files:

resource.extension.class=io.confluent.kafka.schemaregistry.security.SchemaRegistrySecurityResourceExtension,io.confluent.schema.exporter.SchemaExporterResourceExtension

The configuration for the exporter resource extension class in the schema-registry.properties is described in Set up source and destination environments in Schema Linking on Confluent Platform.

Lifecycle and States¶

Schema Registry stores schemas in a Kafka topic. A schema exporter uses the topic offset to determine its progress.

When a schema exporter is created, it begins in the STARTING state. While in this state, it finds and exports all applicable schemas already written to the topic. After exporting previously registered schemas, the exporter then enters the RUNNING state, during which it will be notified of any new schemas, which it can export if applicable. As schemas are exported, the exporter will save its progress by recording the latest topic offset.

If you want to make changes to the schema exporter, you must first “pause” it, which causes it to enter the PAUSED state. The exporter can then be resumed after the proper changes are made. Upon resumption, the exporter will find and export any applicable schemas since the last offset that it recorded.

While an exporter is paused, it can also be “reset”, which will cause it to clear its saved offset and re-export all applicable schemas when it resumes. To accomplish this, the exporter starts off again in STARTING state after a reset, and follows the same lifecycle.

The states of a schema exporter at various stages in its lifecycle are summarized below.

State	Description
STARTING	The exporter finds and exports all applicable previously registered schemas for the topic. This is the starting state, or the state after a reset.
RUNNING	The exporter is notified of new schemas, exports them if applicable, and tracks progress by recording last topic offset.
PAUSED	An exporter can be paused; for example, to make configuration changes. When it resumes, the exporter finds and exports schemas since the last recorded offset.

REST APIs¶

Schema Registry supports the following REST APIs, as fully detailed in Exporters in the Schema Registry API documentation:

Task	API
Gets a list of exporters for a tenant	GET /exporters
Creates a new exporter	POST /exporters
Gets info about an exporter	GET /exporters/{name}
Gets the config for an exporter	GET /exporters/{name}/config
Gets the status of an exporter	GET /exporters/{name}/status
Updates the information for an exporter	PUT /exporters/{name}/config
Pauses an exporter	PUT /exporters/{name}/pause
Resumes an exporter	PUT /exporters/{name}/resume
Resets an exporter, clears offsets	PUT /exporters/{name}/reset
Deletes an exporter	DELETE /exporters/{name}

Deployment Strategies and Cluster Linking¶

Schema Linking can replicate schemas between Schema Registry clusters as follows:

A cluster link sends data from a “source cluster” to a “destination cluster”. The supported cluster types are shown in the table below.

Source Schema Registry Cluster Options	Destination Schema Registry Cluster Options
Confluent Cloud with internet networking	Confluent Cloud with internet networking
Confluent Cloud with internet networking	Confluent Platform 7.0+ with an IP address accessible over the public internet
Confluent Platform 7.0+	Confluent Platform 7.0+
Confluent Platform 7.0+ with an IP address accessible over the public internet	Confluent Cloud with internet networking

Schema Linking can also be used in both directions between two clusters, allowing each side to continue to receive both reads and writes for schemas.

With regard to Confluent Cloud and Confluent Platform solutions, you would use Schema Linking with Cluster Linking to mirror from one instance to the other. Any use of Confluent Platform in these setups require Confluent Platform 7.0.+ or later.

To learn more about Cluster Linking and mirror topics, see Cluster Linking for Confluent Platform and Geo-replication with Cluster Linking on Confluent Cloud.

Access Control (RBAC) for Schema Linking¶

Note

A staged rollout of RBAC for Schema Linking is in progress in early December 2022. This feature may not be immediately available to all customers.

Role-Based Access Control (RBAC) enables administrators to set up and manage user access to Schema Linking. This allows for multiple users to collaborate on with different access levels to various resources.

The following table shows how RBAC roles map to Schema Linking resources. For details on how to manage RBAC for these resources, see Manage RBAC using Confluent Cloud Console and Manage RBAC using the Confluent CLI.

Role	Scope	All Schema Linking resources
OrganizationAdmin	Organization	✔
EnvironmentAdmin	Environment	✔
CloudClusterAdmin	Cluster
Operator	Organization, Environment, Cluster
MetricsViewer	Organization, Environment, Cluster
ResourceOwner	Schema Subject	✔ Only if (`subject = `) on source Schema Registry and (:.schema_context:`) on destination Schema Registry
DeveloperManage	Schema Subject
DeveloperRead	Schema Subject
DeveloperWrite	Schema Subject
DataDiscovery	Environment
DataSteward	Environment	✔

Table Legend:

✔ = Yes
Blank space = No