One of the most important questions in architecting a data platform is where to store and archive data. In a blog series, we’ll cover the different storage strategies for Kafka and introduce you to Lenses’ S3 Connector for backup/restore. But in this first blog, we must introduce the different Cloud storage options available. Later blogs will focus on specific solutions, explain in more depth how this maps to Kafka and then how Lenses manage your Kafka topic backups.

Kafka adoption is growing fast. Very fast. At Lenses, we’re pushing out new features to increase developer productivity, reduce manual effort & improve the cost & hygiene of operating your Kafka platform. Only a few weeks since Lenses 5.1, yet here we are again with more goodies in our release 5.2.

Hello again. We strive to improve the productivity of developers building event-driven applications on the technology choices that best fit your organization. AWS continues to be a real powerhorse for our customers. Not just for running the workloads, but in supporting them with their native services: MSK Kafka, MSK Connect and now increasingly Glue Schema Registry. This is bringing a strong alternative to Confluent and their Kafka infrastructure offerings.

With version 5.1, Lenses is now offering enterprise support for our popular open-source Secret Provider to customers. In this blog, we’ll explain how secrets for Kafka Connect connectors can be safely protected using Secret Managers and walk you through configuring the Lenses S3 Sink Connector with the Lenses Secret Provider plugin and AWS Secret Manager.

With increased applications developed by different engineering teams on Kafka comes increased need for data governance. JSON is often used when streaming projects bootstrap but this quickly becomes a problem as your applications iterate, changing the data structures with add new fields, removing old and even changing data formats. It makes your applications brittle, chaos ensues as downstream consumers fall over due to miss data and SREs curse you.

Until recently, teams were building a small handful of Kafka streaming applications. They were usually associated with Big Data workloads (analytics, data science etc.), and data serialization would typically be in AVRO or JSON. Now a wider set of engineering teams are building entire software products with microservices decoupled through Kafka. Many teams have adopted Google Protobuf as their serialization, partly due to its use in gRPC.

Kafka is a ubiquitous component of a modern data platform. It has acted as the buffer, landing zone, and pipeline to integrate your data to drive analytics, or maybe surface after a few hops to a business service. More recently, though, it has become the backbone for new digital services with consumer-facing applications that process live off the stream. As such, Kafka is being adopted by dozens, (if not hundreds) of software and data engineering teams in your organization.

Apache Kafka has grown from an obscure open-source project to a mass-adopted streaming technology, supporting all kinds of organizations and use cases. Many began their Apache Kafka journey to feed a data warehouse for analytics. Then moved to building event-driven applications, breaking down entire monoliths. Now, we move to the next chapter. Joining Celonis means we’re pleased to open up the possibility of real-time process mining and business execution with Kafka.

Today, I’m thrilled to announce that Lenses.io is joining Celonis, the leader in execution management. Together we will raise the bar in how businesses are run by driving them with real-time data, making the power of streaming open, operable and actionable for organizations across the world. When Lenses.io began, we could never have imagined we’d reach this moment.

Here we are, our screens split and fingers poised to forage through two days of fresh Kafka content at Kafka Summit Americas. Tweet us your #KafkaSummit highlights if they’re missing here and we can add them to the round-up.