We upgraded one of our projects to the latest version of Quarkus and encountered a deployment failure in our staging environment with an unusual error message.
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Using Sonar helps improve the code quality. Sonar identifies code smells, bugs, and vulnerabilities, it provides an overview of the code coverage and complexity and finds duplications. There are more advantages if one integrates it in the pipeline and decides to customise its rule, but it is possible to gain a lot just by running it locally.
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In a project, I have documents identified by UUIDs. For the lack of a better strategy, I decided to partition them based on the value of the UUID identifier. For example, my first partition could be 00000000-0000-0000-0000-000000000000 - 0fffff-ffff-ffff-ffff-ffffffffffff, the second one 10000000-0000-0000-0000-000000000000 and 1fffff-ffff-ffff-ffff-ffffffffffff, and so on.
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For a project, I need to store large amounts of documents and retrieve chunks based on their relevance. My current solution is a small embedded Chroma, and I wanted something more scalable. Enters: Elasticsearch.
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