Resolving the Confluent.Kafka Consumer Schema Registry Artifact Lookup Error

Описание: Discover why you might encounter the `No artifact with ID '33' was found.; error code: 404` error in Confluent.Kafka and how to resolve it effectively using schema registry techniques.
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Resolving the Confluent.Kafka Consumer Schema Registry Artifact Lookup Error

If you've been working with Confluent.Kafka and Schema Registry, you might have encountered a frustrating issue when trying to consume messages from your Kafka topic, specifically the error message: "No artifact with ID '33' was found.; error code: 404." You may have already called schemaRegistry.GetLatestSchemaAsync, which returns a valid schema ID of 39. So why is the consumer fetching a different artifact ID? Let’s dive into this issue and explore the solution step by step.

Understanding the Problem

When using Confluent.Kafka along with the Schema Registry, each version of a schema is associated with a unique ID. Therefore, when you consume messages, the consumer tries to resolve the schema ID embedded within the messages. If the schema version with that particular ID cannot be found in the registry, you'll encounter the aforementioned 404 error.

Common Causes of the Issue

Deleted Schema Versions: If a schema version was deleted, any messages produced with that schema will reference a schema ID that no longer exists.

Schema Caching: It is possible that a caching mechanism is serving outdated information, resulting in a mismatch between the schema you fetched and what the consumer is trying to access.

Offset Management: If your consumer is attempting to consume older messages that used a schema version that has since been removed, this could lead to the error.

Steps to Diagnose and Resolve the Error

1. Check Schema Versions

You can diagnose the issue by checking the available schema versions for a specific subject using the Schema Registry API.

Use the endpoint:

[[See Video to Reveal this Text or Code Snippet]]

Verify if the ID 33 exists in the returned schema versions. If it does not, continue to the next step.

2. Determine if Schema Versions Were Deleted

If the ID 33 does not exist, it's likely that this version was deleted. You need to consider the following:

If a schema was deleted, any messages produced using that schema will no longer have a valid reference to the schema ID.

You may need to skip offsets in Kafka that correspond to old versions if you want to consume messages reliably.

3. Update Consumer Logic

Since the consumer deserializer automatically attempts to resolve the schema ID present within the Kafka messages, the consumer code must ensure that you handle such scenarios gracefully. Here are a couple of strategies:

Avoid Hardcoding IDs: The deserializer cannot bypass the ID lookup; therefore, hard-coding schema IDs is not a viable solution.

Ensure Validity of Schema: Always ensure that your consumed message relates to a valid schema version before processing. Consider adding error handling that checks for schema validity and skips certain messages accordingly.

4. Possible Caching Issues

If caching might be causing this issue, make sure to configure your CachedSchemaRegistryClient correctly. If necessary, clear or refresh your cache to ensure that the latest schema metadata is fetched when your consumer starts.

Conclusion

Encountering a 404 error for a schema ID in Confluent.Kafka can be quite confusing, especially when you receive a valid ID from the Schema Registry. It's essential to understand how Kafka consumers handle schema IDs and to have a strategy in place for managing schema versions properly. By following the steps outlined above—checking schema versions, ensuring valid schemas, and managing offsets—you can effectively resolve issues related to Schema Registry artifact lookups.

With this knowledge, you can confidently work with Confluent.Kafka and avoid the common pitfalls associated with schema