Using a terminal for Kafka observability won’t work. Does everyone really have to be a Kafka expert to see inside your event-driven architecture?
Knowing what data you have in Kafka and across your streaming applications is like trying to see in the dark; then there’s the problem of access for the rest of your team.
The bottom line? Engineers shouldn’t all have to be Kafka know-it-alls to troubleshoot Kafka streams.
of your Kafka streams
A shared understanding of streams through metadata
by discovering sensitive data in your streams
of your event-driven applications
for fewer incorrect dashboards & upset customers
“We knew that Kafka was critical for our business but we also knew it would be difficult to operate. Using Lenses helps us know where to look for the data we need so we can see what’s working across systems and apps.”
Laurent Pernot, Software Engineering Manager - Article
Investigate Kafka by exploring events using SQL via a Kafka UI or API. Lenses understands your data irrespective of serialization: Avro, Protobuf, JSON, CSV and more.
Explore Kafka topic metrics such as throughput & lag as well as metadata such as partitioning & configuration.
Real-time discovery & cataloging of metadata across your Kafka, PostgreSQL and elasticsearch infrastructure.
Allow engineers to add tags & descriptions to your Kafka and microservice data entities to better find and socialize data.
Have a holistic view & data lineage across data stores, microservices and event-driven applications through a UI or Topology.
Categorize metadata across your applications, connectors and data streams, and then configure pseudonymization and masking to obfuscate fields.
With over 27 million monthly active users & more than 2.5 thousand coders, learn how this mobile gaming company improved developer productivity through Kafka data observability.
Our Snapshot SQL helps you find those needles in a haystack of real-time data. We walk you through how it works.
React to live data