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Apache Kafka observability to avoid flying blind

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?

Data Observability

How many tools does it take to change a lightbulb in Kafka?

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.

What is Kafka observability? Why bother?

Faster Kafka troubleshooting

Faster Kafka troubleshooting

of your Kafka streams

Team collaboration

Team collaboration

A shared understanding of streams through metadata

Meet compliance

Meet compliance

by discovering sensitive data in your streams

Accelerated delivery

Accelerated delivery

of your event-driven applications

Cleaner Data

Cleaner data

for fewer incorrect dashboards & upset customers

Article

“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

Laurent Pernot, Software Engineering Manager - Article

Best practices for Kafka data observability

Engineers struggle with the Kafka commands they need to learn.

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.

Kafka Commands
No visibility

We have no visibility into our Kafka topic health.

Explore Kafka topic metrics such as throughput & lag as well as metadata such as partitioning & configuration.

How can we document what data we have?

Real-time discovery & cataloging of metadata across your Kafka, PostgreSQL and elasticsearch infrastructure.

Document data
Collaborate to Kafka streams

How can we better collaborate & add context to Kafka streams?

Allow engineers to add tags & descriptions to your Kafka and microservice data entities to better find and socialize data.

How can we track data lineage of our data pipelines?

Have a holistic view & data lineage across data stores, microservices and event-driven applications through a UI or Topology.

Track data lineage
Redact sensitive data

How can we redact sensitive data to stay compliant?

Categorize metadata across your applications, connectors and data streams, and then configure pseudonymization and masking to obfuscate fields.

What are the components of Kafka observability?

Data Exploration

Data
Exploration

Flows Monitoring

Flows
monitoring

Data catalog

Data
catalog

Data masking

Data
masking

Metadata tagging

Metadata
tagging

Connector Management

Connection management

Case Study

Playtika

Gaining 300 Data Engineering Hours Per Day with Lenses

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.

How to

Navigate data with SQL

Our Snapshot SQL helps you find those needles in a haystack of real-time data. We walk you through how it works.

Explore data

Debug microservices

React to live data

Data Capture Monolith Blog

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Change Data Capture and Kafka to break up your monolith

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Data Catalog Blog

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Data dump to data catalog for

Apache Kafka

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Distributed Tracing

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Distributed tracing with Kafka message headers

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Get your DataOps workspace for Apache Kafka

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