Oxford Dictionaries runs a global API competition, and Red Hat and the 3scale team are more than happy to support this initiative. Find more about the competition here.
Oxford Dictionaries powers a huge range of technologies, apps, and digital services. Their world-renowned dictionary data powers search engines, provides definitions in e-readers, and makes predictive text and language-learning software possible. On top of their rich language data, which is integrated with cutting-edge technology, they provide an outstanding API. Oxford Dictionaries uses that to work with partners across the globe to create some of the most flexible and reliable platforms and services in the world.
Here is what the folks from Oxford Dictionaries have to say about their competition:
At Oxford Dictionaries, we love language, and we want the world to communicate more easily. So, to celebrate language, communication, and the launch of our API, we’re holding the Oxford Dictionaries API competition. To enter, simply create an app that uses one or more of the languages in the Oxford Dictionaries API. It doesn’t matter if your app is an existing application that has recently integrated Oxford Dictionaries data or a brand new app; already published in an app store or never-before publicized. You can enter as an individual or as a team. We want to see what you can create!
The winner and four runners-up will be showcased on our site and receive PRO subscriptions to our API and a collector’s mug, and we will send all entrants a collector’s T-shirt. You can find out more about the competition and how to enter here.
Wanna know how to get a discount on your Summit pass? Wanna know where or what, the Summit party is gonna be? Then you should watch me embarrass myself in front of thousands of people in the Summit Party Promo video!
See that big guy doing nothing particularly embarrassing? Yeah? Well, that’s not me. I’m the plucky little guy in the backwards Sox hat who plays the butt of the joke in the last four seconds or so. Yup, that’s me, yours truly, ya boy, the self-deprecating weirdo.
So how did I get myself into this? Well, look out cause I’m fixin’ to tell ya, again…
Continue reading “I wasn’t born with these powers, I’ve just learned to live with them…”
Updated and enhanced integration services are now available on Red Hat OpenShift. A containerized, formatted version of Red Hat JBoss Fuse 6.3 is now available for simplified deployments on OpenShift instances.
Technology is shifting so rapidly — from cloud-based architectures, Internet of Things and a variety of devices for interaction, new data streams, and mobile apps, to name a few — that organizations have to be able to create and deploy applications and process data quickly. Traditional, monolithic systems and top-heavy ESB-style integration approaches tend to be too slow and rigid to enable this level rapid innovation.
That is where an agile integration framework like JBoss Fuse can be a foundational element in your IT and digital strategy. Agile integration has three core capabilities: distributed integration, containers, and an API-based architecture.
- JBoss Fuse uses the lightweight distributed integration patterns of the underlying Apache Camel project.
- As part of the JBoss middleware services on OpenShift, JBoss Fuse is available for rapid deployment within container and cloud environments. Red Hat OpenShift is based on Docker and Kubernetes. Container architectures allow developers to build and integrate traditional and microservices-based applications at scale quickly.
- JBoss Fuse can be used together with Red Hat 3scale API Management Platform as an engine to develop and deploy APIs, both internally to development groups and externally for customer and partner ecosystems.
Integration technologies help organizations build on their existing infrastructures even as they pivot to new cloud-based and service-based architectures.
Features (and Benefits) at a Glance
- Spring Boot support
- Custom-developed, containerized applications based on Apache Camel 2.18
- Integration with Hystrix and Zipkin microservices frameworks
- An optimized integration environment for microservices applications on Red Hat OpenShift
- Path to transition off existing Apache Karake-based applications to cloud architectures
- Consistent hybrid integration platform across their enterprise
We are excited to announce beta availability of Red Hat Single Sign-On 7.1 (RH-SSO). RH-SSO is a standards-based, out-of-the-box authentication, web single sign-on, and authorization service, which mediates between your enterprise user directory or third-party identity provider for identity information and your applications via standards-based tokens.
Beta documentation and code downloads are available in the Customer Portal. RPM packages are available for Linux systems through Red Hat Subscription Management.
Features and Highlights
Continue reading “Announcing: Red Hat Single Sign-On 7.1 Beta Is Available”
Red Hat JBoss Data Grid 7.0 is here.
This significant new release offers a variety of features which are designed for complex, distributed, and high-volume, velocity data requirements. JBoss Data Grid can support both on-premise and cloud-based infrastructures, and it can handle the near-instantaneous, complex demands of Internet of Things and big data environments.
What It Brings
JBoss Data Grid can be deployed in different architectures, depending on the needs of your environment. In addition to the traditional usage as distributed cache, in-memory data grids can function as the primary data store for applications or as a compute grid for distributed computing.
There are two use cases for using JBoss Data Grid as a data store:
- Data caching and transient storage. As an in-memory data store for frequently accessed application data or for transient data, such as shopping cart information or session data. This avoids hitting transactional backend systems are frequently, which reduces operating costs.
- Primary data store. Data Grid can function as a key-value store similar to a NoSQL database. This can be the primary data source for applications for rapid retrieval of in-memory data and to persist data for recovery and archiving. Applications can run data-intensive operations like queries, transaction management, and distributed workloads.
Modern architectures require flexible, distributed, and scalable memory and data storage. Using JBoss Data Grid as a distributed computing grid can help support the most demanding architectures:
- Scale-out compute grid and event-driven computing. Through storage node clusters, JBoss Data Grid can do a distributed architecture with application logic at each node for faster data processing and lower latency and traffic. This architecture also supports event-driven computing by executing application logic at the node as data are updated.
- Big data and the Internet of Things. JBoss Data Grid can support massive data streams — hundreds of thousands of updates per second. The Internet of Things can have data streams from thousands of connected devices, updating frequently. Clustering and scale, application logic and processing, and both in-memory and persistent storage in JBoss Data Grid enable those big data architectures by managing those massive data streams.
Real-Time Analytics and Performance for Digital Business
DIgital transformation means that organizations are pushing into a new intersection between their physical goods or services and online, on-demand applications. This digital environment is reliant on data — and unlike previous generations, this technology uses -near live data streams rather than historical data collections.
JBoss Data Grid is a leading high-performance, highly-scalable, in-memory data grid. In-memory data grids provide a means of scalable memory so that even rapidly changing application data can be processed. Better data processing and management enables organizations to make fast, accurate decisions using large data streams. JBoss Data Grid 7.0 offers a data foundation for real time analytics:
- Low latency data processing through memory and distributed parallel execution
- Data partitioning and distribution across cluster nodes for horizontal scalability
- High availability through data replication
- Shared data services for real-time and in-memory analytics and event processing
A Short List of Major Features
The release notes cover the full features and enhancements for JBoss Data Grid 7.0. There are a number of features for improved ease of use, real-time analytics, and language support:
- Distributed streams, which uses the Java 8 Stream API to take complex collections of data and run defined analytics operations.
- Resilient distributed dataset (RDD) and DStream integration with Apache Spark 1.6, allowing Data Grid to be a data source for Spark and to execute Spark and Spark Streaming operations on data in Data Grid.
- Hadoop InputFormat/OutputFormat integration, so that Hadoop tooling and oeprations can be used with data stored in Data Grid.
- New administrative consoles for cluster management to simplify common tasks for managing the cache, nodes, and remote tasks.
- Control operations for clusters including graceful shutdowns and startup and restores from persistent storage.
- A new Node.js Hot Rod client to support using Data Grid as a NoSQL database with Node.js applications.
- Running remote tasks (business logic) on a Data Grid server from the Java Hot Rod client.
- Support for a Cassandra cache store, which persists the entries of a distributed cache on a shared Apache Cassandra instance.
We are very excited to announce availability of Red Hat JBoss Data Grid (JDG) Version 7.0 Beta!
Based on the Infinispan project, JBoss Data Grid is a leading high-performance, highly-scalable, in-memory NoSQL store, which enables your enterprise to make fast, accurate decisions on large volumes of changing data and provides superior user experience for your customer-facing applications.
JDG 7.0 Beta introduces major new features in the areas of Real-time Data Analytics, ease of use and administration, and expanded polyglot support.
Real-Time Data Analytics
- Distributed Streams: In JDG 7.0, we introduce a distributed version of the Java 8 Stream API which enables you to perform rich analytics operations on data stored in JDG using the functional expressions available in the Stream API.
- Apache Spark and Hadoop Integration: JDG 7.0 features a new Resilient Distributed Dataset (RDD) and DStream integration with Apache Spark version 1.6. This enables you to use JDG as a highly scalable, high-performance data source for Apache Spark, executing Spark and Spark Streaming operations on data stored in JDG. We have also added a Hadoop InputFormat/OutputFormat integration, which enables use of tools from the Hadoop ecosystem on data stored in JDG.
Ease of Use and Administration
In JDG 7.0, we have released a new administration console which enables you to view a JDG cluster and perform clustered operations across its nodes. Operations include creating new caches and cache templates, adding or removing nodes, and deploying or executing remote tasks. We have also added the ability to shut down or restart a cluster in a controlled manner, with data restore from persistent storage.
Expanded Polyglot Support
Cassandra Cache Store
Additionally, JDG 7.0 introduces a new out-of-the-box Cassandra cache store, which enables you to persist the entries of a distributed cache on a shared Apache Cassandra instance.
Try It Today
Red Hat JBoss Middleware customers can download JDG 7.0 Beta from the Customer Portal
Beta documentation, including release notes, is available on the documentation page in the Portal.