Consumer lag spikes | Data format or schema incompatibility
Your Kafka consumer is lagging, logs are full of deserialization errors, and it's 2 AM. A producer team deployed a schema change without telling you, and now your consumer can't parse the data. This is one of the most common production incidents -- and it's completely preventable.
In this clip, watch as Marcus, the on-call engineer, uses Lenses to quickly diagnose a real P1 incident caused by upstream schema incompatibility. He compares message payloads side-by-side, detects the breaking schema change, and has the fix deployed in seconds.
- How to spot deserialization errors in your consumer logs
- How to use Lenses SQL Studio to compare messages at different offsets
- How to view schema diffs and identify breaking changes
- Real-time payload inspection with automatic PII masking
- How to coordinate schema changes across producer and consumer teams