Moving to Kafka stream processing from batch is a learning curve that feels like running into a brick wall. Why not use skills you already have, such as SQL?
Are rekeying, exactly-once semantics and exception handling giving you a headache? If Kafka streaming applications can be frustrating to build, they are more challenging to scale, troubleshoot and carry to production.
Building & deploying Kafka stream processing applications doesn’t have to be so difficult.
And the less time you need to spend learning the fundamentals of Kafka, the more time you can spend solving your core business challenges.
Build & deploy streaming applications without the need to learn Kafka streams
Self-service deployment framework of streaming apps on Kubernetes
Applications defined and managed as configuration & deployed on your infrastructure
“Lenses not only helps developers to understand which data is there and how the data is represented, but provides a feedback mechanism on the schema itself. It’s a big part of our low-code app development process.”
Anders Eriksson, Data Engineer - Avanza
Filter, aggregate, transform and reshape data with streaming SQL, deploying over your existing Kubernetes or Connect infrastructure.
Deploy, manage & monitor your Kafka connect connectors all from a UI and with error handling and alerting.
Document and tag applications across different product teams, frameworks and deployment pipelines.
The real-time application topology provides a data-centric, google-maps style view of the dependencies between different apps and flows.
Use a secure UI or API to produce events into a Kafka to test your event-driven application. Works across all serializations.
Manage and evolve schemas held in your 3rd party schema registry such as Confluent or Cloudera, protected by RBAC.
Deploy data transformation workloads defined as SQL to convert data such as JSON, XML or CSV to AVRO or other formats
This highly regulated financial services provider used Lenses to help teams deploy on Kafka without constraints, speeding up time-to-market of streaming apps by 10x and sending 600k targeted communications to end-customers.