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For the most part, Java developer's favorite thing to do with Microsoft was to ignore it. Closed source, high price tags and proprietary interfaces only strengthened arguments for Java developers to keep Microsoft out of their projects. Many Java gurus may have stopped paying attention to Microsoft all together. If you did, you may have missed some of their latest efforts and progress. Check it out—it might even be enough to reconsider Microsoft's reputation entirely.
In this blog series, we have used the SpringTrader application as an example of an existing legacy Java app to modernize. In Parts 1, 2, and 3, we got the app up and running on Pivotal Cloud Foundry and began refactoring the architecture. This post extends the effort. At the end, you will clearly see how we have improved scalability, resiliency, and maintainability. Code examples and downloads are included.
In this post, Pivotal Labs Engineering Manager, David Julia, provides an example of a problematic RESTful JSON API and an approach for refactoring it. When API designs are implicit, they don’t reveal and enable the intended API usage, and they become very difficult to implement. In today’s world of cloud connectivity and developer community, poorly designed API can greatly slow down or stop software service adoption in its tracks, not to mention the public feedback for poor APIs. David’s approach, and the related code, clearly explain some of the key considerations.
Bjorn Harvold is the CTO of Traveliko.com, an online hotel booking website. For over the past decade, he has worked with the Spring Framework on a full-time basis, and in recent years has utilized Cloud Foundry due to its tight integration with Java and Spring technologies. In this post, he discusses Bearchoke Tempest, a collection of frontend tools and demos for Spring and Cloud Foundry developers which include REST with security & versioning, a stock ticker over WebSocket, Facebook & MailChimp integration, and more. Pivotal spoke with Harvold about his history in the open source community, why he released Bearchoke Tempest, and why Spring and Cloud Foundry are making his life easier these days.
In the first two installments of this series, we began refactoring the monolithic SpringTrader application by migrating it to Pivotal Cloud Foundry and integrating a new remote microservice. In this post, we will cover how to add resilience to the application via the use of Eureka and Hystrix from the Netflix OSS project.
Over the last couple of months, the Cloud Foundry Java Experience team has improved a number of features for applications running in production. We've added support for Luna HSMs, an improved memory calculator, support for the Dynatrace and Introscope APM providers, and made many other minor improvements. Now a number of additional developer-focused improvements can be found in the latest Cloud Foundry Java Buildpack release.
During sessions and presentations, Pivotal will demonstrate its implementations of Cloud Native Java technologies at the JavaOne convention, taking place October 25-29 at Hilton Union Square in San Francisco. As an increasing number of enterprises migrate to a Cloud Native architecture, they seek guidance on how to best deploy and optimize Java apps on cloud platforms. Leading developers from Pivotal will be offering insight, best practices, and use cases during their presentations.
In the first installment of this series, we used the SpringTrader application as an example of an existing legacy Java app, and we outlined an approach to do two things—migrate the app to Pivotal Cloud Foundry and prepare it to run in a microservices architecture. In this post, we dive into the refactoring and modernization of one key service, enabling it to deal with real-time market data.
Migrating legacy, monolith apps on to Cloud Native architectures is a challenge. In this post, we delve into the details of taking an existing Java app, refactoring it, and deploying it on Pivotal Cloud Foundry. This is the first part in a series, and uses an actual legacy application, SpringTrader, as an example.
In this article, Pivotal Cloud Foundry platform engineer and consultant, Guido Westenberg, gives us a deep look towards an integration between Cloud Foundry and various configuration servers. The automation he explains also requires no application code changes, removing a lot of config issues from the plate of both development and operations teams. A source code example and YouTube demo is provided as well.