Operations | Monitoring | ITSM | DevOps | Cloud

For many growing businesses, data infrastructure grows and evolves organically. This often results in teams running one technology for log analytics, like a self-managed ELK cluster, and a completely separate technology for application search. While functional, these disparate tech stacks begin to eat into the bottom line. Businesses grapple with fragmented skill sets, inconsistent security models, multiple vendors, and a constant operational tax.

In today’s interconnected world, data sovereignty has evolved from a legal concept into a strategic imperative. For some European businesses and institutions, it’s no longer just about regulatory compliance – it’s about trust, resilience, and long-term digital independence.

We’re rolling out table-formatted topics for Apache Kafka, enabling open-source users to ingest, process, and emit data natively as Apache Iceberg tables. We’ve developed a new class of topics in Apache Kafka that stream data into lakehouse formats such as Apache Iceberg. The developer experience, similar to Diskless, is flexible, and the topics are opt-in via cluster configuration.

Finding yourself migrating and weighing the options when it comes to moving your entire Apache Kafka setup to a new cloud? This blog will point you to a solution to efficiently migrate your workloads to an Aiven for Apache Kafka cluster circumventing the headache that usually comes with cloud migration.

Diskless topics reward high-throughput workloads with large batches but can struggle with low-throughput patterns. Note: This analysis is based on testing with Diskless Kafka 4.0.0-rc15. Diskless topics are available for you to start experimenting with via the Inkless fork but the feature is still in development, and performance characteristics may change significantly as the technology matures. If you're: This post is for you!

Kafka and Iceberg is a costly marriage of inconvenience. If you write code for a living you’ve probably heard of Apache Iceberg - but you might not realise the detour your Kafka events must take to get there. Typically a Kafka message written to an Iceberg table must take a journey via a connector, rack up transfer fees, and idle in a sidecar before it appears as an Iceberg table—hardly the friction‑free flow open table formats promise.