I'm pleased to announce the release of Spring LDAP 2.0.2.RELEASE. The highlights of this release include:

• LDAP-300 - Fix potential NullPointerException when using Spring LDAP in a uber jar
• LDAP-299 - Deprecation of spring-ldap-ldif-batch module in favor of using classes within Spring Batch

For additional information on the release, refer to the changelog.

Reference | Javadoc

I'm pleased to announce the release of Spring Security 3.2.4. This release includes a number of bug fixes. To view a list of changes see the changelog.

Reference | Javadoc | Guides

Dear Spring community,

It's my pleasure to announce that Spring Framework 4.0.5 and 3.2.9 have been released. Both of those are designed as a final feature release in the respective line - we will only consider further releases from the 4.0.x and 3.2.x branches in case of serious bugs now.

http://projects.spring.io/spring-framework/

Spring Framework 3.2.9 comes with a repackaged ASM 5.0.2 and is therefore capable of basic Java 8 bytecode processing. However, specific Java 8 feature support - JSR-310 date-time, repeatable annotations, etc - is exclusive to the Spring Framework 4.x line.

SPR…

Hot on the heels of the Spring 3.2.9 and 4.0.5 releases, I am pleased to announce the availability of the GA release of the Spring Data release train named Dijkstra.

We're happy to welcome 5 new modules to the release train: Elasticsearch, Cassandra, Couchbase, Gemfire and Redis. Two of them even celebrate their first GA version ever. So I'd like to send special congratulations and thanks to the project leads Mohsin Husen for Spring Data Elasticsearch and David Webb as well as Matthew Adams for Spring Data Cassandra.

Here's the full list of participating modules:

• Spring Data Commons 1.8 GA - Artifacts - JavaDocs - Documentation - Changelog
• Spring Data JPA 1.6 GA - Artifacts - JavaDocs - Documentation - Changelog
• Spring Data MongoDB 1.5 GA - Artifacts - JavaDocs - Documentation - Changelog
• Spring Data Neo4j 3.1 GA - Artifacts - JavaDocs - Documentation - Changelog
• Spring Data Solr 1.2 GA - Artifacts - JavaDocs - Documentation - Changelog
• Spring Data Couchbase 1.1 GA - Artifacts - JavaDocs - Documentation - Changelog
• Spring Data Cassandra 1.0 GA - Artifacts - JavaDocs - Documentation - Changelog
• Spring Data Elasticsearch 1.0 GA - Artifacts - JavaDocs - Documentation - …

Recorded at SpringOne2GX 2013 in Santa Clara, CA

Speaker: Zhiyong Li

SAS® Institute has a large portfolio of Java EE applications. SAS had previously provided support to deploy and run all of these applications in WebLogic, WebSphere and JBoss. Beginning with SAS 9.4, which was released in July 2013, SAS updated its infrastructure and middle tier platform to deliver and run on Pivotal tc Server. In this talk, we will discuss the motivation, technology selection, architecture, system administration, automated installation and configuration, etc., that SAS used to improve value for its customers. Specifically, we will discuss the following areas in detail:

• Technology selection: To make tc Server viable, we include the messaging, caching and the transaction management system.
• Architecture: To leverage tc Server scalability and reliability in SAS products, we support clustering by using the Pivotal Web Server and the mod_proxy. Application migration: We provide guidance to our Java developers and configuration developers on how to migrate their applications to the tc Server environment.
• Security: We support SSL, single sign-on and other enterprise security protocols such as Integrated Windows Authentication, CA Site Minder, IBM Web Seal, SAML, etc.
• System administration: We provide a single entry point to manage all SAS application stacks including all web applications by leveraging the Hyperic product.
• Automated installation / configuration: We provide the automated process to install and configure Hyperic and all Pivotal Application Fabric products (tc Server, vFWS and GemFire) and SAS web applications.
• Delivery and support: SAS delivers embedded tc Server as the SAS Web Application Server for use with all our offerings with a midtier on all our supported host platforms. This enables SAS to provide complete supported application architecture with more complete visibility and control of the critical software.
• Cloud deployment: This approach also provides advantages for our customers leveraging virtualization and cloud deployment strategies.

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Recorded at SpringOne2GX 2013 in Stana Clara, CA

Speakers: Emad Benjamin and Guillermo Tantachuco

The session will cover various GC tuning techniques, in particular focus on tuning large scale JVM deployments. Come to this session to learn about GC tuning recipe that can give you the best configuration for latency sensitive applications. While predominantly most enterprise class Java workloads can fit into a scaled-out set of JVM instances of less than 4GB JVM heap, there are workloads in the in memory database space that require fairly large JVMs. In this session we take a deep dive into the issues and the optimal tuning configurations for tuning large JVMs in the range of 4GB to 128GB. In this session the GC tuning recipe shared is a refinement from 15 years of GC engagements and an adaptation in recent years for tuning some of the largest JVMs in the industry using plain HotSpot and CMS GC policy. You should be able to walk away with the ability to commence a decent GC tuning exercise on your own. The session does summarize the techniques and the necessary JVM options needed to accomplish this task. Naturally when tuning large scale JVM platforms, the underlying hardware tuning cannot be ignored, hence the session will take detour from the traditional GC tuning talks out there and dive into how you optimally size a platform for enhanced memory consumption. Lastly, the session will also cover vfabric reference architecture where a comprehensive performance study was done. Learn more about

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Speaker: Pieter Humphrey

Creating a stream of live twitter data for an analytics dashboard using Spring XD, a JavaScript D3 component / Spring XD's REST API.

Source code:https://github.com/spring-projects/spring-xd-samples/tree/master/analytics-dashboard

Learn more about Spring XD: http://projects.spring.io/spring-xd

Learn more about Spring for Apache Hadoop: http://projects.spring.io/spring-hadoop

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Speaker: Gary Russell

The Spring Integration team has been hard at work on the latest release of the popular integration framework. Before version 4.0, it was impractical to define a complete Spring Integration flow without using XML. With this major release, the existing basic annotation support has received an overhaul and those who prefer to use java @Configuration classes can now define their applications without needing to use any XML (of course, XML is still supported as well). In this session we will cover these major changes to the framework, explaining how and when to use them. It will be mainly demonstration and code walk through, and we will build a useful Spring Boot / Integration application from scratch.

Learn more about Spring Integration at http://projects.spring.io/spring-integration

Learn more about Spring Boot at http://projects.spring.io/spring-boot

Learn more about Spring Framework at http://projects.spring.io/spring-framework

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The first milestone release for Spring Boot 1.1.0 is available now in the Spring milestone repository.

Highlights include:

• Additional templating support.
• Improved metrics and health endpoints.
• Additional data integrations (including improved MongoDB support and support for GemFire).
• A host of minor improvements and additions.
• Updated dependencies for many third-party libraries.

See the release notes for a complete list of new and noteworthy features.

We'd appreciate any feedback from existing Spring Boot 1.0 users. If you are upgrading, be sure to follow the instructions from the release notes…