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Published latest aggregated blog posts
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src/content/posts-aggregator/10.json

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src/content/posts-aggregator/11.json

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{
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"title": "Quarkus Newsletter #54 - March",
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"link": "https://quarkus.io/blog/quarkus-newsletter-54/",
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"title": "Quarkus 3.19.3 - Maintenance release",
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"link": "https://quarkus.io/blog/quarkus-3-19-3-released/",
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"author": [
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{
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"name": "James Cobb",
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"name": "Guillaume Smet",
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"avatar": null
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}
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],
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"date": "2025-03-12T00:00:00.000Z",
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"feed_title": "Quarkus",
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"content": "Make sure you read Mario Fusco’s two-part blog about Agentic AI with Quarkus, where he discusses common workflows and agentic AI patterns and architectures, with practical examples using Quarkus and LangChain4j. Learn about the power of intelligent applications by combining the robustness of Java, the efficiency of Quarkus, and the advanced capabilities of RAG in a great article by Daniel Oh. Emil Lefkof gives a real-world example of how LangChain4j and AI can be leveraged to automatically extract structured metadata from PDF documents. Leveraging the combination of LangChain4j and Google Gemini AI proves to be a powerful approach for automating document analysis workflows. \"Performance & Productivity: Rethinking Java Dependencies for the Cloud Era\" by Markus Eisele discusses how Quarkus extensions are curated, lightweight, and optimized for microservices and serverless. You will also see the latest Quarkus Insights episodes, top tweets/discussions and upcoming Quarkus attended events. Check out ! Want to get newsletters in your inbox? using the on page form."
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"content": "We released Quarkus 3.19.3, the second (we skipped 3.19.0) maintenance release for our 3.19 release train. We also released two candidate releases: * Quarkus 3.20.0.CR1 LTS - it is going to be our next LTS, it is based on 3.19 * Quarkus 3.21.0.CR1 - a regular minor release with new features UPDATE To update to Quarkus 3.19, we recommend updating to the latest version of the Quarkus CLI and run: quarkus update Note that quarkus update can update your applications from any version of Quarkus (including 2.x) to Quarkus 3.19. For more information about the adjustments you need to make to your applications, please refer to the . FULL CHANGELOG You can get the full changelog of on GitHub. COME JOIN US We value your feedback a lot so please report bugs, ask for improvements… Let’s build something great together! If you are a Quarkus user or just curious, don’t be shy and join our welcoming community: * provide feedback on ; * craft some code and ; * discuss with us on and on the ; * ask your questions on ."
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src/content/posts-aggregator/12.json

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{
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"title": "Running SQLite in Pure Java with Quarkus",
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"link": "https://quarkus.io/blog/sqlite4j-pure-java-sqlite/",
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"title": "Quarkus Newsletter #54 - March",
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"link": "https://quarkus.io/blog/quarkus-newsletter-54/",
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"author": [
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{
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"name": "Andrea Peruffo",
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"name": "James Cobb",
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"avatar": null
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}
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],
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"date": "2025-03-12T00:00:00.000Z",
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"feed_title": "Quarkus",
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"content": "What if you could run a C-based database in pure Java, with zero configuration, and even compile it to a native image effortlessly? With the new Quarkiverse extension , you can do exactly that. Traditionally, embedded databases in Java require reimplementing their C counterparts, often leading to differences in behavior, missing optimizations, and delayed bug fixes. However, provides a JDBC driver that leverages the original SQLite C implementation while running safely inside a sandbox. HANDS-ON EXAMPLE To see in action, you can start with any existing Quarkus application or one of the . If you prefer a ready-made example, check out , which integrates SQLite within a Quarkus application using Hibernate ORM. By simply changing the JDBC driver dependency, you can embed a fully functional SQLite database inside your application while retaining all the benefits of the native SQLite implementation. To get started, add the extension dependency to your pom.xml: <dependency> <groupId>io.quarkiverse.jdbc</groupId> <artifactId>quarkus-jdbc-sqlite4j</artifactId> </dependency> Then, configure your Quarkus application to use SQLite with standard JDBC settings: quarkus.datasource.db-kind=sqlite quarkus.datasource.jdbc.url=jdbc:sqlite:sample.db quarkus.datasource.jdbc.min-size=1 You can now use your datasource as you normally would with Hibernate and Panache. Note that we keep a minimum connection pool size > 0 to avoid redundant copies from disk to memory of the database. RUNNING IN A SECURE SANDBOX Under the hood, SQLite runs in a fully in-memory sandboxed environment, ensuring security and isolation. When a connection to a local file is opened, the following occurs: 1. The database file is copied from disk to an in-memory Virtual FileSystem. 2. A connection is established to the in-memory database. While this approach is highly secure, many users need to persist database changes. One recommended solution is to periodically back up the in-memory database to disk. This can be achieved through a scheduled job that: 1. Backs up the in-memory database to a new file. 2. Copies the backup to the host file system. 3. Atomically replaces the old database file with the new backup. This setup ensures a seamless experience while maintaining SQLite’s sandboxed security. You can adapt this approach to fit your specific needs. Here’s a sample implementation: @ApplicationScoped public class SQLiteBackup { @ConfigProperty(name = \"quarkus.datasource.jdbc.url\") String jdbcUrl; @Inject AgroalDataSource dataSource; // Execute a backup every 10 seconds @Scheduled(delay=10, delayUnit=TimeUnit.SECONDS, every=\"10s\") void scheduled() { backup(); } // Execute a backup during shutdown public void onShutdown(@Observes ShutdownEvent event) { backup(); } void backup() { String dbFile = jdbcUrl.substring(\"jdbc:sqlite:\".length()); var originalDbFilePath = Paths.get(dbFile); var backupDbFilePath = originalDbFilePath .toAbsolutePath() .getParent() .resolve(originalDbFilePath.getFileName() + \"_backup\"); try (var conn = dataSource.getConnection(); var stmt = conn.createStatement()) { // Execute the backup stmt.executeUpdate(\"backup to \" + backupDbFilePath); // Atomically replace the DB file with its backup Files.move(backupDbFilePath, originalDbFilePath, StandardCopyOption.ATOMIC_MOVE, StandardCopyOption.REPLACE_EXISTING); } catch (IOException | SQLException e) { throw new RuntimeException(\"Failed to back up the database\", e); } } } TECHNICAL DEEP DIVE compiles the official SQLite C to WebAssembly (Wasm), which is then translated into Java bytecode using the . This enables SQLite to run in a pure Java environment while maintaining its full functionality. SECURITY AND ISOLATION One of the key benefits of this approach is security. Running SQLite inside a Wasm sandbox ensures memory safety and isolates it from the host system, making it an excellent choice for applications that require embedded databases while avoiding the risks of native code execution. CONCLUSION With the new extension, you get the best of both worlds: the power and reliability of SQLite combined with the safety and portability of Java. This extension seamlessly integrates SQLite into Quarkus applications while maintaining a lightweight and secure architecture. Best of all, everything compiles effortlessly with native-image. Ready to try it out? Give a spin in your projects and experience the benefits of running SQLite in pure Java with Quarkus! PRIOR ART * * "
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"content": "Make sure you read Mario Fusco’s two-part blog about Agentic AI with Quarkus, where he discusses common workflows and agentic AI patterns and architectures, with practical examples using Quarkus and LangChain4j. Learn about the power of intelligent applications by combining the robustness of Java, the efficiency of Quarkus, and the advanced capabilities of RAG in a great article by Daniel Oh. Emil Lefkof gives a real-world example of how LangChain4j and AI can be leveraged to automatically extract structured metadata from PDF documents. Leveraging the combination of LangChain4j and Google Gemini AI proves to be a powerful approach for automating document analysis workflows. \"Performance & Productivity: Rethinking Java Dependencies for the Cloud Era\" by Markus Eisele discusses how Quarkus extensions are curated, lightweight, and optimized for microservices and serverless. You will also see the latest Quarkus Insights episodes, top tweets/discussions and upcoming Quarkus attended events. Check out ! Want to get newsletters in your inbox? using the on page form."
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src/content/posts-aggregator/13.json

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{
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"title": "RESTEasy 6.2.12.Final and 7.0.0.Beta1 Releases",
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"link": "https://resteasy.dev/2025/03/10/releases/",
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"title": "Running SQLite in Pure Java with Quarkus",
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"link": "https://quarkus.io/blog/sqlite4j-pure-java-sqlite/",
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"author": [
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{
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"name": null,
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"name": "Andrea Peruffo",
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"avatar": null
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}
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],
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"date": "2025-03-10T18:11:11.000Z",
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"feed_title": "RESTEasy",
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"content": ""
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"date": "2025-03-12T00:00:00.000Z",
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"feed_title": "Quarkus",
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"content": "What if you could run a C-based database in pure Java, with zero configuration, and even compile it to a native image effortlessly? With the new Quarkiverse extension , you can do exactly that. Traditionally, embedded databases in Java require reimplementing their C counterparts, often leading to differences in behavior, missing optimizations, and delayed bug fixes. However, provides a JDBC driver that leverages the original SQLite C implementation while running safely inside a sandbox. HANDS-ON EXAMPLE To see in action, you can start with any existing Quarkus application or one of the . If you prefer a ready-made example, check out , which integrates SQLite within a Quarkus application using Hibernate ORM. By simply changing the JDBC driver dependency, you can embed a fully functional SQLite database inside your application while retaining all the benefits of the native SQLite implementation. To get started, add the extension dependency to your pom.xml: <dependency> <groupId>io.quarkiverse.jdbc</groupId> <artifactId>quarkus-jdbc-sqlite4j</artifactId> </dependency> Then, configure your Quarkus application to use SQLite with standard JDBC settings: quarkus.datasource.db-kind=sqlite quarkus.datasource.jdbc.url=jdbc:sqlite:sample.db quarkus.datasource.jdbc.min-size=1 You can now use your datasource as you normally would with Hibernate and Panache. Note that we keep a minimum connection pool size > 0 to avoid redundant copies from disk to memory of the database. RUNNING IN A SECURE SANDBOX Under the hood, SQLite runs in a fully in-memory sandboxed environment, ensuring security and isolation. When a connection to a local file is opened, the following occurs: 1. The database file is copied from disk to an in-memory Virtual FileSystem. 2. A connection is established to the in-memory database. While this approach is highly secure, many users need to persist database changes. One recommended solution is to periodically back up the in-memory database to disk. This can be achieved through a scheduled job that: 1. Backs up the in-memory database to a new file. 2. Copies the backup to the host file system. 3. Atomically replaces the old database file with the new backup. This setup ensures a seamless experience while maintaining SQLite’s sandboxed security. You can adapt this approach to fit your specific needs. Here’s a sample implementation: @ApplicationScoped public class SQLiteBackup { @ConfigProperty(name = \"quarkus.datasource.jdbc.url\") String jdbcUrl; @Inject AgroalDataSource dataSource; // Execute a backup every 10 seconds @Scheduled(delay=10, delayUnit=TimeUnit.SECONDS, every=\"10s\") void scheduled() { backup(); } // Execute a backup during shutdown public void onShutdown(@Observes ShutdownEvent event) { backup(); } void backup() { String dbFile = jdbcUrl.substring(\"jdbc:sqlite:\".length()); var originalDbFilePath = Paths.get(dbFile); var backupDbFilePath = originalDbFilePath .toAbsolutePath() .getParent() .resolve(originalDbFilePath.getFileName() + \"_backup\"); try (var conn = dataSource.getConnection(); var stmt = conn.createStatement()) { // Execute the backup stmt.executeUpdate(\"backup to \" + backupDbFilePath); // Atomically replace the DB file with its backup Files.move(backupDbFilePath, originalDbFilePath, StandardCopyOption.ATOMIC_MOVE, StandardCopyOption.REPLACE_EXISTING); } catch (IOException | SQLException e) { throw new RuntimeException(\"Failed to back up the database\", e); } } } TECHNICAL DEEP DIVE compiles the official SQLite C to WebAssembly (Wasm), which is then translated into Java bytecode using the . This enables SQLite to run in a pure Java environment while maintaining its full functionality. SECURITY AND ISOLATION One of the key benefits of this approach is security. Running SQLite inside a Wasm sandbox ensures memory safety and isolates it from the host system, making it an excellent choice for applications that require embedded databases while avoiding the risks of native code execution. CONCLUSION With the new extension, you get the best of both worlds: the power and reliability of SQLite combined with the safety and portability of Java. This extension seamlessly integrates SQLite into Quarkus applications while maintaining a lightweight and secure architecture. Best of all, everything compiles effortlessly with native-image. Ready to try it out? Give a spin in your projects and experience the benefits of running SQLite in pure Java with Quarkus! PRIOR ART * * "
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src/content/posts-aggregator/14.json

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{
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"title": "Meet Keycloak at KubeCon EU, London in April 2025",
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"link": "https://www.keycloak.org/2025/03/keycloak-kubecon25-eu-announce",
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"title": "RESTEasy 6.2.12.Final and 7.0.0.Beta1 Releases",
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"link": "https://resteasy.dev/2025/03/10/releases/",
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"author": [
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{
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"name": "Ryan Emerson",
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"name": null,
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"avatar": null
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}
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],
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"date": "2025-03-08T00:00:00.000Z",
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"feed_title": "Keycloak Blog",
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"feed_avatar": "https://www.gravatar.com/avatar/87fe00619f08c241da8dfb23d907ffa2?s=50",
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"content": "We are thrilled to announce that Keycloak will be at KubeCon Europe, London April 1-4th 2025. Keycloak’s presence at previous KubeCons was a huge success, and we are always eager to meet Keycloak enthusiasts, users and newcomers alike. At this year’s event we will be hosting a Kiosk in the Project Pavilion, as well as presenting a talk about Evolving OpenID Connect and Observability. KEYCLOAK COMMUNITY MEET & GREET AT THE PROJECT PAVILION from Hitachi, and from Red Hat, and other contributors will be hosting a Keycloak kiosk at the . This is a great chance to meet people who use Keycloak, contribute to Keycloak, take our survey about new Keycloak features, and get some cool swag! Keycloak Kiosk opening hours: * Wednesday, April 2: 15:30 - 19:45 * Thursday, April 3: 14:00 - 17:00 * Friday, April 4: 12:30 - 14:00 PRESENTING EVOLVING OPENID CONNECT AND KEYCLOAK OBSERVABILITY and will be presenting a talk on Evolving OpenID Connect and Observability in Keycloak. * Friday, April 4, 14:30 - 15:00pm By Takashi Norimatsu, Hitachi & Ryan Emerson, Red Hat. RELATED TALKS Keycloak has a powerful community in Japan, and we have received several contributions in the past. One of Keycloak’s maintainers, Takashi Norimatsu, is based in Japan. There is also a quite popular Japanese book about by Yuichi Nakamura and Japanese community colleagues that will soon appear in its second edition. To learn more about community activities in Japan, join the following talk: * Thursday April 3, 2025 14:15 - 14:45 By Ota Kohei, Apple; Shu Muto, NEC Solution Innovators, Ltd.; Yuichi Nakamura, Hitachi, Ltd.; Sunyanan Choochotkaew, IBM Research; Noriaki Fukuyasu, The Linux Foundation SEE YOU SOON! We’re preparing for KubeCon EU 2025 and can’t wait to connect with our community. Mark your calendars and join us. See you in London!"
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"date": "2025-03-10T18:11:11.000Z",
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"feed_title": "RESTEasy",
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"content": ""
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src/content/posts-aggregator/15.json

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src/content/posts-aggregator/16.json

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