Debugging Kafka Messages: Inspection & Analysis
Find specific messages, decode serialized payloads, and diagnose data quality issues using KLogic's powerful message inspection and analysis tools.
KLogic Message Inspector
A real-time window into your Kafka topic data with powerful filtering and decoding
Live Message Feed
Stream messages from any topic partition in real time, or browse historical messages by specifying an offset range or time window.
Advanced Filtering
Filter messages by key, value content, headers, partition, or custom JMESPath expressions to find exactly what you need.
Schema Decoding
Automatically decode Avro, Protobuf, JSON Schema, and raw JSON messages for human-readable inspection.
Avro & Protobuf Decoding
Inspect serialized binary messages as human-readable structured data
Avro Decoding
KLogic integrates directly with Confluent Schema Registry to decode Avro messages. The schema ID embedded in the message wire format is used to fetch the correct schema.
Automatic Schema Lookup
Schema IDs in the Confluent wire format are resolved automatically from your Schema Registry.
Schema Evolution Support
Messages encoded with older schema versions are decoded correctly, showing which version was used.
Key & Value Separate
Both message key and value can have independent Avro schemas decoded simultaneously.
Protobuf Decoding
Upload your .proto descriptor files or connect to a Schema Registry with Protobuf support to decode binary messages.
Proto Descriptor Upload
Upload compiled .desc files to KLogic for message decoding without Schema Registry.
Nested Message Types
Complex nested Protobuf message hierarchies are expanded and displayed in a tree view.
oneof & Enum Support
Protobuf oneof fields and enum values are rendered with their symbolic names, not raw integers.
Decoded Message Example
Raw Binary (Base64)
Decoded Avro (Schema v3)
Finding Specific Messages
Techniques for locating messages across high-volume topics
Key-Based Lookup
If you know the message key, KLogic can calculate the partition using the standard Kafka partitioner and retrieve messages directly from that partition.
Time-Based Search
Specify a time range to search messages produced during a specific window. KLogic uses Kafka's offsetsForTimes API for efficient seeking.
Offset-Based Navigation
Jump directly to a known offset within a specific partition. Useful for replaying or investigating messages from error logs that include offsets.
Header-Based Filtering
Many applications embed trace IDs, correlation IDs, or event types in message headers. Filter by any header key-value pair to trace a request through your system.
X-Trace-IDPractical Debugging Workflow
A systematic approach to diagnosing message-level issues
Identify the Affected Topic & Time Window
Start with the topic where the issue was observed and narrow the time range to when errors were reported. Check consumer group lag spikes as a clue.
Configure the Correct Deserializer
Select Avro, Protobuf, JSON, or String deserializer in KLogic's message inspector. If using Schema Registry, ensure it is connected and accessible.
Apply Filters to Narrow Results
Use key search, value content filtering, or header matching to isolate the specific messages causing problems. Start broad, then narrow incrementally.
Inspect Message Structure
Examine decoded message fields for null values, unexpected types, missing required fields, or data outside expected ranges.
Correlate Across Topics
Use trace IDs from message headers to follow a request through multiple topics in your event-driven pipeline using KLogic's Flow Map view.
Debug Kafka Messages with Confidence
KLogic's message inspector gives you the visibility you need to diagnose data quality issues, trace events, and understand your Kafka data flows.
Free 14-day trial • Avro & Protobuf support • Schema Registry integration