Real-time stock data with Apache Flink and Apache Kafka
Aiven for Apache Flink® With Apache Kafka® and Apache Flink®, you can now have coding-free support for real-time data processing and streaming analytics! Find out how ->
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How to publish messages through Kafka to Grafana Loki
Back in November 2021, Grafana Labs released version 2.4 of Grafana Loki. One of the new features it included was a Promtail Kafka Consumer that can easily ingest messages out of Kafka and into Loki for storing, querying, and visualization. Kafka has always been an important technology for distributed streaming data architectures, so I wanted to share a working example of how to use it to help you get started.
Support Database Technology Migration with Apache Kafka and Apache Kafka Connect
Aiven for Apache Kafka® Migrating from one database technology (such as PostgreSQL®) to another (such as MySQL) using batch has a variety of problems. Find out how to use Apache Kafka® to perform streaming updates, and keep the target continually in sync with the source.
Preparing Apache Kafka for Scala 3
Have you ever thought you'd quite like to migrate Apache Kafka to Scala 3? Find out how Aiven's OSPO managed it!
Scaling Kafka at Honeycomb
When you send telemetry into Honeycomb, our infrastructure needs to buffer your data before processing it in our “retriever” columnar storage database. For the entirety of Honeycomb’s existence, we have used Apache Kafka to perform this buffering function in our observability pipeline.
Optimizing data streaming pipelines: a panel recap
Find out how to use Apache Flink and Apache Kafka to make your pipelines better in this Flink Forward Global 2021 panel recap.
Metrics for Apache Kafka with Datadog and Aiven | Ryan Martin (Aiven)
Using managed services is all very well, but how do you get the data you need from the different services into Datadog so you can see it all in one place? This session will walk through the configuration for bringing your Aiven-managed Apache Kafka service metrics into your Datadog explorer. You’ll see how to filter the metrics to focus on specific topics or consumer groups, and how to use the Aiven client to create a repeatable, scriptable setup. This session is recommended for anyone living in the as-a-Service world who cares about data and is interested in using metrics to optimize their Kafka clusters.
Adapting Legacy Systems to a Stream-Based Platform
In a perfect world, small pieces of software scale up and down with a high-performance message broker like a heart, pumping data in a controlled, efficient manner. However, at some point, in every single system, an application starts pumping out large data requests, in a sporadic, uncontrollable manner. Because here, we are talking about the real world, right? In this article, we will address the problem of adapting a legacy system to play with a stream-based platform.