Agent
Change log for Lenses Agent 6.2.
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Change log for Lenses Agent 6.2.
Two new optional config keys let you tune the topic-type-detection sampling consumer per deployment:
lenses.interval.topic.sampling.poll-timeout-ms — per-attempt Kafka poll timeout for the sampling consumer (default 2000).
lenses.interval.topic.sampling.poll-attempts — maximum poll attempts before giving up (default 3).
Both defaults match the previously hard-coded values, so existing deployments are unaffected unless you opt in.
The Provisioning API is now documented in the OpenAPI specification.
TopicStatsWorker log noise during normal operation has been demoted from INFO to DEBUG, so production logs stay readable.
Better diagnostic logging for topic identification when investigating JSON payload edge cases.
When a SQL query joined or selected from a topic whose value was a JSON object missing some fields, the engine could fail to resolve a union struct type. The engine now matches by subset of fields instead, so partial JSON objects no longer fail the query.
If a topic's value or key referenced a schema that the agent could not yet resolve from the Schema Registry (for example during startup or when the registry was briefly unreachable), reads against that topic could fail. Marshaller construction is now deferred, so the rest of the topic remains readable while the registry catches up.
The Schemas listing in the Agent UI no longer renders "NaN" in place of a name when a schema lacks a numeric identifier.
The topic configurations screen now lays out correctly on smaller screen sizes and viewports.
The Throughput card now shows bytes/s and records/s per topic for both Source and Target, rather than showing only totals. A search bar appears automatically when there are more than 5 topics.
The Health card header now displays P50, P90, and Max lag across all source partitions at a glance. Source partitions with lag above the P90 threshold are highlighted in the partition table, and each lag cell shows the partition's share of total lag on hover.
Clicking a topic name or offset value in any K2K metrics table now opens a studio tab directly instead of reloading the page. The same applies to K2K app links in the Topics drawer and the error tooltip buttons on the app listing.
This update for Lenses SQL Processors, dealing with JSON Kafka topics involving unions and nested records, addresses previous query failures. Optional fields missing from JSON are now treated as null, exact schema matches are prioritized, and specific error messages indicate the path and expected type of any missing required fields.
Reading Kafka data through a SQL snapshot is based solely on the record context, not the schema known to Lenses. This approach resolves issues where data, written using the schema registry with subject naming strategies like RecordNameStrategy, or TopicRecordNameStrategy, doesn't encounter failures.
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