Building a Cloud ETL Pipeline on Confluent Cloud
As enterprises move more and more of their applications to the cloud, they are also moving their on-prem ETL pipelines to the cloud, as well as building new ones. There
As enterprises move more and more of their applications to the cloud, they are also moving their on-prem ETL pipelines to the cloud, as well as building new ones. There
Event stream processing solves many business challenges, from big data ingestion and data integration, to real-time data processing and IoT. It gives you the ability to analyze big data streams
The Elasticsearch sink connector helps you integrate Apache Kafka® and Elasticsearch with minimum effort. You can take data you’ve stored in Kafka and stream it into Elasticsearch to then be
We are pleased to announce the release of ksqlDB 0.7.0. This release features highly available state, security enhancements for queries, a broadened range of language/data expressions, performance improvements, bug fixes,
We talked about how easy it is to send osquery logs to the Confluent Platform in part 1. Now, we’ll consume streams of osquery logs, detect anomalous behavior using machine
Apache Kafka® is often deployed alongside Elasticsearch to perform log exploration, metrics monitoring and alerting, data visualisation, and analytics. It is complementary to Elasticsearch but also overlaps in some ways,
Osquery (developed by Facebook) is an open source tool used to gather audit log events from an operating system (OS). What’s unique about osquery is that it uses basic SQL
When a company becomes overreliant on a centralized database, a world of bad things start to happen. Queries become slow, taxing an overburdened execution engine. Engineering decisions come to a
I am pleased to announce the release of Confluent Platform 5.4. Like any new release of Confluent Platform, it’s packed with features. To make them easier to digest, I want
Now that we’ve learned about the processing layer of Apache Kafka® by looking at streams and tables, as well as the architecture of distributed processing with the Kafka Streams API
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