Generative AI is revolutionizing how we work and interact. Yet for generative AI applications relying on private, regulated, or commercially valuable data, feeding the model with the right information is crucial. Failure could result in adverse consequences such as poor performance, confidential information exposure, or regulatory requirement breaches. An integrated data platform is a powerful way to accelerate the development of generative AI applications by providing real-time data feeds, consolidating inputs from different sources, and defining clear information boundaries.

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When attacking any system, taking control of its central nervous system is the first step in infiltrating the core infrastructure and gaining control over its vital functions. Translating this to organization data, a clear target is Apache Kafka, the data hub increasingly adopted for mission-critical systems. This session explores the topic of attacking and defending Apache Kafka, shedding light on potential threats, attack vectors, and countermeasures. Initially, we’ll focus on understanding the potential attack surface of Apache Kafka.

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When sinking unix timestamps from Apache Kafka to OpenSearch/ElasticSearch using the dedicated connector, they are not recognized by default as timestamp in the target tech.

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You have an Apache Kafka topic that you want to consume via REST APIs (think curl or just a web browser), how to do it? The reply is Karapace an Open Source (Apache 2.0) tool providing Schema Registry and REST proxy functionality. Let’s check out how to quickly run it on Docker. Step 1: the Apache Kafka® Cluster You need an Apache Kafka cluster up & running, if you have one already you can skip to the next section.

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Useful Links Aiven Signup Code examples to run with Aiven for Apache Flink Flink JDBC SQL Connector Flink SQL CDC Connecto for PostgreSQL

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You can tabulate a JSON document (retrieve it as a row) in MySQL with the JSON_TABLE function.

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You can remove a field from JSON document in MySQL with the JSON_REMOVE function.

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You can insert a field in a JSON document in MySQL with the JSON_INSERT function.

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You can edit a JSON document in MySQL with:

• The JSON_SET function that will replace values for JSON paths that exists and add values for the ones that don’t exist.
• The JSON_REPLACE function that will replace values for JSON paths that exists and ignore the ones that don’t exist.

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You can merge two JSON documents in MySQL with:

• the JSON_MERGE_PRESERVE function to concatenate the document values
• the JSON_MERGE_PATCH function to keep the latest value for each key

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