The Spring Cloud Data Flow team is pleased to announce the final 1.4.0 GA release. Follow the Getting Started guides for Local Server, Cloud Foundry, and Kubernetes. This release packs in quite a few improvements including: Dashboard improvements Ability to manage app versions (in Skipper mode) New stream deployment builder (in Skipper mode) Docker compose for development Security improvements Proxy server support for the Shell LDAP Role Mapping support Documentation improvements Dashboard Improvements A substantial focus of the 1.4.0 release has been the Dashboard UI and its integration with…

The Spring Cloud Data Flow team is pleased to announce the release of 1.4.0 RC1. Follow the Getting Started guides for Local Server, Cloud Foundry, and Kubernetes. Following are the release highlights: Stream Deployment UX In Skipper mode, we have added a brand new stream deployment builder form to simplify the selection of platform and the properties while deploying a stream. The options include override to the deployment platform and the deployer, application and global properties for the streaming pipeline. Deployment Properties Docker Compose for Development To simplify the getting started…

The Spring Cloud Data Flow team is excited to announce the release of 1.4.0 M1. Follow the Getting Started guides for Local Server, Cloud Foundry, and Kubernetes. A big focus of this first milestone release of the 1.4.x line has been the Dashboard UI. In an effort to keep our UI dependencies current at all times, we finally upgraded the UI to Angular 5.2 and Angular CLI 1.6. Furthermore, the UI now provides better integration with Spring Cloud Skipper. As such, you can now manage the versions of App Registrations and set a default version. Manage Versions The version information is now shown…

On behalf of the team, I am pleased to announce the general availability of Spring Cloud Data Flow 1.3 across a range of platforms Follow the Getting Started guides for Local Server, Cloud Foundry, and Kubernetes Release Highlights Stream updates and rollback A streaming data pipeline orchestrated as a series of microservice applications has always been the core value of Spring Cloud Data Flow’s design. In Data Flow 1.3 we have provided the ability to update sources, processors, and sinks independently without having to undeploy and redeploy the entire stream. The stream update and rollback…

On behalf of the team, I am pleased to announce the first milestone release of Spring Cloud Data Flow 1.3.0. Local Server: Getting Started Guide. Usability is one of the big focus for our team and in the 1.3 release-line, we are aiming to modernize the dashboard with an upgraded client-side technology stack, improved tooling, and documentation. The focus is to improve the readability, user-experience, and the overall performance. Angular 4 This first milestone release of Spring Cloud Data Flow contains the initial version of the new Angular 4 based Dashboard UI. The old AngularJS 1.x based UI…

On behalf of the Spring Cloud Data Flow team, I’m pleased to announce the release of Spring Cloud Data Flow and Spring Cloud Data Flow for Cloud Foundry 1.2.1.RELEASE. This release provides several improvements around OAuth2 authorization. Here are the relevant links to documentation and getting started guides. Local: Quick Start, Getting Started Guide Cloud Foundry: Getting Started Guide Spring Cloud Data Flow now provides role support for OAuth2, converging with the VIEW, CREATE, MANAGE roles that Data Flow supports when using the traditional security option. Considering the varying use-case…

The Spring XD team is pleased to announce that Spring XD 1.0.0 Milestone 4 is now available for download. Spring XD makes it easy to solve common big data problems such as data ingestion and export, real-time analytics, and batch workflow orchestration. This release includes several notable new features: Batch Processing UI Improved Type Conversion Composite Modules Improved DSL parsing and Tap functionality (Note: breaking syntax change) New sources: Reactor based syslog, tcp-client Expression based processors can invoke a pre-registered JSON Path function. Pre-defined Batch jobs for HDFS to…

This is the third part in a series of blog posts highlighting some of the new features available in Spring Integration 2.2 following the recent release of Release Candidate 1. The first part described the new set of MongoDB adapters. In part two we highlighted the new extended support for synchronizing non-transactional resources with transactions. In this third part today, we would like to introduce the new Java Persistence API (JPA) support that is provided starting with Spring Integration 2.2. The JPA module is persistence-provider-agnostic and has been tested using: The provided sample is…