Why Kubernetes and Kafka Are the Combo for DataOps Success

Why Kubernetes and Kafka Are the Combo for DataOps Success

This enhances your team's efficiency and increases scalability to process more data. ... Coupled together, Apache Kafka with Kubernetes can massively increase the agility and efficiency of building real-time data applications.

What is DataOps? Why is a real-time data platform essential to the use cases driving it? How can you build data pipelines with open source complexity?

In this episode of The New Stack Makers podcast — recorded live for KubeCon+CloudNativeCon North America, we talk to Andrew Stevenson, chief technical officer and co-founder of Lenses.io, about how Apache Kafka and Kubernetes can together dramatically increase the agility, efficiency and security of building real-time data applications.

“Data is a constant, and it’s moving around, no matter what technology we’re using,” Stevenson said.

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So how do organizations make the most of that bigger-than-big data? Well, the majority of them have adopted open source tools Kafka stream processing platform or Kubernetes container orchestration system — or most likely both. But the complexity of these huge systems can be overwhelming to the point of ineffective. And with open source tooling, as Stevenson says, can come uncertainty.

Sponsor Note

sponsor logoKubeCon + CloudNativeCon conferences gather adopters and technologists to further the education and advancement of cloud native computing. The vendor-neutral events feature domain experts and key maintainers behind popular projects like Kubernetes, Prometheus, Envoy, CoreDNS, containerd and more.

He explained, “It’s a real struggle making sure the open source technology has the governance around it. It’s not that data is something new to people in organizations — they have data. But it’s the security aspect around it. And if you couple that with, quite often, the lack of visibility on open source technology — that is where it starts to fail.”

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