Looking for Confluent Platform Schema Management docs? This page describes Schema Management on Confluent Cloud. If you are looking for Confluent Platform documentation, check out Schema Management on Confluent Platform.

Manage Schemas in Confluent Cloud

Schema Management is fully supported on Confluent Cloud with the per-environment, hosted Schema Registry, and is a key element of Stream Governance Overview.

View a schema

View the schema details for a specific topic.

Search for schemas

You can also find and view schemas by searching for them. Searches are global; that is, they span across environments and clusters.

  1. Start typing the name of a schema subject, data record, or data field name into the search bar at the top. You will get results as you type, including for other entities like topics.

    ../_images/cloud-02a-search-schema.png
  2. Hit enter to select an entity like a schema.

    ../_images/cloud-02b-search-schema.png

To learn more, see Searching Data and Schemas.

Find schemas from the Environment view

  1. Navigate to an environment.

  2. Click View and manage schemas to get a list of all schemas in the environment.

    ../_images/cloud-02c-view-manage-schemas.png
  3. Select the schema you want to view.

    ../_images/cloud-02d-view-schemas-list.png

Tree view and code view

Two different types of views are available for schemas:

  • tree view
  • editable code view

To switch between the views, click the buttons to the left of the schema level search box:

../_images/cloud-sr-schema-tree-toggle-icon-captions.png

By default, schemas are displayed in a tree view which allows you to understand the structure of the schema and navigate the hierarchy of elements and sub-elements.

../_images/cloud-sr-schema-tree-view.png

In the tree view you can:

  • Use the arrows to the left of an element to expand it and view sub-elements.
  • Apply and manage available tags as described in Tagging Data and Schemas.

In edit mode (the “code view”), you can create and edit schemas as described in the sections below.

../_images/cloud-sr-schema-code-view.png

Create a topic schema

Create key and value schemas. Value schemas are typically created more frequently than key schemas.

Best practices:

  • Provide default values for fields to facilitate backward-compatibility if pertinent to your schema.
  • Document at least the more obscure fields for human-readability of a schema.

Tip

You can also create schemas from the Confluent Cloud CLI, as described in the Create a Schema section in the Quick Start.

Create a topic value schema

  1. From the navigation menu, click Topics, then click a topic to select it (or create a new one).

  2. Click the Schema tab.

    ../_images/cloud-03-set-msg-value-schema.png
  3. Click Set a schema. The Schema editor appears.

    ../_images/cloud-04-schema-value-editor.png
  4. Select a schema type: JSON, Avro, or Protobuf. (The default is Avro.)

  5. The basic structure of a schema appears prepopulated in the editor as a starting point. Enter the schema in the editor:

    • name: Enter a name for the schema if you do not want to accept the default, which is determined by the subject name strategy. The default is schema_type_topic_name. Required.

    • type: Either record, enum, union, array, map, or fixed. (The type record is specified at the schema’s top level and can include multiple fields of different data types.) Required.

    • namespace: Fully-qualified name to prevent schema naming conflicts. String that qualifies the schema name. Optional but recommended.

    • fields: JSON array listing one or more fields for a record. Required.

      Each field can have the following attributes:

      • name: Name of the field. Required.
      • type: Data type for the field. Required.
      • doc: Field metadata. Optional but recommended.
      • default: Default value for a field. Optional but recommended.
      • order: Sorting order for a field. Valid values are ascending, descending, or ignore. Default: Ascending. Optional.
      • aliases: Alternative names for a field. Optional.

    For example, you could add the following simple schema.

    {
      "type": "record",
      "name": "value_my_new_widget",
      "fields": [
        {
          "name": "name",
          "type": "string"
        }
      ]
    }
    

    This will display in Confluent Cloud as shown below.

    ../_images/cloud-05-entered-schema.png

    In edit mode, you have options to:

    • Validate the schema for syntax and structure before you create it.
    • Add schema references with a guided wizard.
  6. Click Create.

    • If the entered schema is valid, you can successfully save it and a Schema updated message is briefly displayed in the banner area. The schema is saved and shown in tree view form.

      ../_images/cloud-06-schema-updated.png
    • If the entered schema is invalid, parse errors are highlighted in the editor (as in this example where a curly bracket was left off). If parse errors aren’t auto-highlighted, click the See error messages link on the warning banner to enable them.

      ../_images/cloud-schema-invalid-avro-warning-banner.png
      ../_images/cloud-07-schema-invalid-avro.png

If applicable, repeat the procedure as appropriate for the topic key schema.

Working with schema references

You can add a reference to another schema, using the wizard to help locate available schemas and versions.

../_images/cloud-05a-schema-references.png

The Reference name you provide must match the target schema, based on guidelines for the schema format you are using:

  • In JSON Schema, the name is the value on the $ref field of the referenced schema
  • In Avro, the name is the value on the type field of the referenced schema
  • In Protobuf, the name is the value on the Import statement referenced schema

First, locate the schema you want to reference, and get the reference name for it.

Add a schema reference to the current schema in the editor

  1. Click Add reference.
  2. Provide a Reference name per the rules described above.
  3. Select the schema fro the Subject list.
  4. Select the Version of the schema you want to use.
  5. Click Validate to check if the reference will pass.
  6. Click Save to save the reference.

For example, to reference to the schema for the employees topic (employees-value) from the widget schema, you can configure a reference to type, record as shown.

../_images/cloud-05b-schema-references.png

To learn more, see Schema References in the Confluent Platform documentation.

View, edit, or delete schema references for a topic

Existing schema references show up on editable versions of the schema where they are configured.

  1. Navigate to a topic; for example, the widget-value schema associated with the widget topic in the previous example.

  2. Click into the editor as if to edit the schema.

    If there are references to other Schemas configured in this schema, they will display in the Schema references list below the editor.

    You can also add more references to this schema, modify existing, or delete references from this view.

Create a topic key schema

  1. Click the Key option. You are prompted to set a message key schema.

    ../_images/cloud-08-set-msg-key-schema.png
  2. Click Set a schema.

  3. Enter the schema into the editor and click Save.

Tip

Kafka messages are key/value pairs. Message keys and message values can be serialized independently. For example, the value may be using an Avro record, while the key may be a primitive (string, integer, and so forth). Typically message keys, if used, are primitives, but they can be complex data types as well (for example, record or array). How you set the key is up to you and the requirements of your implementation. For detailed examples of key and value schemas, see the discussion under Schema Formats, Serializers, and Deserializers in the Schema Registry documentation.

Editing schemas

Edit an existing schema for a topic.

  1. From the navigation menu, click Topics, then click a topic to select it.

  2. Click the Schema tab.

  3. Select the Key or Value option for the schema.

  4. The tree view is shown by default.

    ../_images/cloud-schema-tree-view.png
  5. Click Evolve Schema.

    ../_images/cloud-schema-code-view.png
  6. Make the changes in the schema editor.

    For example, you could edit the previous schema by adding a new field called region.

    {
      "fields": [
        {
          "name": "name",
          "type": "string"
        },
        {
          "name": "region",
          "type": "string",
          "default": ""
        }
      ],
      "name": "value_widgets",
      "type": "record"
    }
    

    In edit mode, you have options to:

    Tip

    When the compatibility mode is set to Backward Compatibility, you must provide a default for the new field. This ensures that consumer applications can read both older messages written to the Version 1 schema (with only a name field) and new messages constructed per the Version 2 schema (with name and region fields). For messages that match the Version 1 schema and only have values for name, region is left empty. To learn more, see Passing Compatibility Checks in the Confluent Cloud Schema Registry Tutorial.

  7. Click Save.

    • If the schema update is valid and compatible with its prior versions (assuming a backward-compatible mode), the schema is updated and the version count is incremented. You can compare the different versions of a schema.

      ../_images/cloud-09-schema-version-updated.png
    • If the schema update is invalid or incompatible with an earlier schema version, parse errors are highlighted in the editor. If parse errors aren’t auto-highlighted, click the See error messages link on the warning banner to enable them.

      For example, if you add a new field but do not include a default value as described in the previous step, you will get an incompatibility error. You can fix this by adding a default value for “region”.

      ../_images/cloud-schema-invalid-avro-warning-banner.png
      ../_images/cloud-10-schema-incompatible.png

Comparing schema versions

Compare versions of a schema to view its evolutionary differences.

  1. From the navigation menu, click Topics, then click a topic to select it.

  2. Click the Schema tab.

  3. Select the Key or Value option for the schema. (The schema Value is displayed by default.)

    ../_images/cloud-11a-schema-version-newest.png
  4. Click Compare version.

    The current version number of the schema is indicated on the version menu.

    ../_images/cloud-11b-schema-version-history-choose.png
  5. Select the Turn on version diff check box.

  6. Select the versions to compare from each version menu. The differences are highlighted for comparison.

    ../_images/cloud-12-schema-compare.png

Changing subject level (per topic) compatibility mode of a schema

The default compatibility mode is Backward. The mode can be changed for the schema of any topic if necessary.

Caution

If you change the compatibility mode of an existing schema already in production use, be aware of any possible breaking changes to your applications.

This section describes how to change the compatibility mode at the subject level. You can also set compatibility globally for all schemas in an environment. However, the subject-level compatibility settings described below override those global settings.

  1. Select an environment.

  2. Select a cluster.

  3. From the navigation menu, click Topics, then click a topic to select it.

  4. Click the Schema tab for the topic.

  5. Select the Key or Value option for the schema.

  6. Click the ellipses (3 dots) on the upper right to get the menu, then select Compatibility settings.

    ../_images/cloud-13a-schema-compat-mode-menu.png

    The Compatibility settings are displayed.

    ../_images/cloud-13a-schema-compat-update.png
  7. Select a mode option:

    Descriptions indicate the compatibility behavior for each option. For more information, including the changes allowed for each option, see Schema Evolution and Compatibility.

  8. Click Save.

Searching for schemas and fields

Confluent Cloud offers global search across environments and clusters for various entity types now including schemas and related metadata. To learn more, see Searching Data and Schemas in Stream Catalog.

Tagging schemas and fields

Confluent Cloud provides the ability to tag schema versions and fields within schemas as a means of organizing and cataloging data based on both custom and commonly used tag names. To learn about tagging, see Tagging Data and Schemas in Data Discovery.

Deleting a schema from Confluent Cloud

  1. From the navigation menu, click Topics, then click a topic to select it.

  2. Click the Schema tab.

  3. Select the Key or Value option for the schema.

  4. Click the ellipses (3 dots) on the upper right to get the menu, then select Delete.

    ../_images/cloud-14-schema-delete-menu.png
  5. On the dialog, select whether to delete only a particular version of the schema or the entire subject (all versions).

    ../_images/cloud-14-schema-delete-dialog.png
  6. Select Delete to carry out the action.

To learn more about deleting schemas, see Schema Deletion Guidelines .

Using Broker-side Schema Validation

You can enable Schema Validation per topic to have the broker verify whether data produced to that topic is using a valid schema ID. Schema Validation is available only on Confluent Cloud dedicated clusters. To learn more about how to configure topics for schema validation and try out a tutorial, see the full guide at Using Broker-Side Schema Validation on Confluent Cloud.

Schema Linking

Confluent Cloud now provides Schema Linking to keep schemas in sync across Schema Registry clusters. To learn more about how it works and try out an example walkthrough, see the full guide at Schema Linking on Confluent Cloud (Preview).

Downloading a schema from Confluent Cloud

  1. From the navigation menu, click Topics, then click a topic to select it.

  2. Click the Schema tab.

  3. Select the Key or Value option for the schema.

  4. Click the ellipses (3 dots) on the upper right to get the menu, then select Download.

    ../_images/cloud-15-schema-download-menu.png

    A schema JSON file for the topic is downloaded into your Downloads directory.

    For example, if you download the version 1 schema for the employees topic from the Quick Start, you get a file called schema-employees-value-v1.avsc with the following contents.

    {
      "fields": [
        {
          "name": "Name",
          "type": "string"
        },
        {
          "name": "Age",
          "type": "int"
        }
      ],
      "name": "Employee",
      "namespace": "Example",
      "type": "record"
    }
    

Tip

The file extension indicates the schema format. For Avro schema the file extension is .avsc; for Protobuf schema, .proto; and for JSON Schema, .json.

Managing schemas for a Confluent Cloud environment

Schema Registry itself sits at the environment level and serves all clusters in an environment, therefore several tasks related to schemas are managed through the registry at this level.

To view and manage Schema Registry for a Confluent Cloud environment:

  1. Select an environment from the Home page. (An environment list is available from the top right menu.)

  2. Click the Schema Registry tab.

    Screenshot of Schema Registry settings

See Configure and Manage Schemas for an Environment in the Confluent Cloud Quick Start to learn how to:

Supported features and limits for Confluent Cloud Schema Registry

  • A single Schema Registry is available per Environment.
  • Access Control to Schema Registry is based on API key and secret.
  • Each Environment must have at least one Apache Kafka® cluster to enable Schema Registry.
  • Your VPC must be able to communicate with the Confluent Cloud Schema Registry public internet endpoint. For more information, see Use Confluent Cloud Schema Registry in a VPC peered environment.
  • Available on Amazon Web Services (AWS), Azure (Microsoft Azure), and GCP (Google Cloud Platform) for cloud provider geographies located in the US, Europe, and APAC. For each cloud provider, geographies are mapped under the hood to specific regions, as described in Enable Schema Registry for Confluent Cloud.
  • Maximum number of schemas allowed is 1,000.
  • Rate limits on number of API requests is 25 requests per second for each API key.
  • High availability (HA) is achieved by having multiple nodes within a cluster always in running state, with each node running in a different availability zone (AZ).