Project Katana lets you compose a modern Web application from a wide range of different Web technologies and then host that application wherever you wish. Howard Dierking presents a sample application to get you started.
This article shows you how to combine the two languages to serve the same .NET application. You get the best of both worlds: Python and .NET work together to provide reusable code functionality without your having to rewrite the code base for a single environment.
FitNesse is an open-source framework for supporting user-acceptance testing. The aim is to make the construction of the individual tests as easy and intuitive as possible. It works with Java, .NET and database applications. It is very useful, but needs a simple 'tips from the trenches' guide to its use. Here is the start of that guide.
.NET libraries that have served you well for years can prove equally useful in today’s new environments—provided you’re willing to expend the migration effort needed. Using the Sterling NoSQL OODB, This article looks at forward migration patterns and best practices that minimize potential difficulties and maximize opportunities for reuse across platforms.
The capability granularity and constraint granularity of a service contract can greatly impact performance of the service architecture. A service consumer communicating over a network connection can experience significant latency between request and response when exchanging large messages over poor network connections. Network latency is often beyond your control, especially when you consume third party services over a public network. Nevertheless you can architect your services to minimize the performance impact of remote service interactions.
Tuning service runtime performance will improve the utilization of individual services as well as the performance of service compositions that aggregate these services. Even though it is important to optimize every service architecture, agnostic services in particular, need to be carefully tuned to maximize their potential for reuse and recomposition.
Because the logic within a service is comprised of the collective logic of service capabilities, we need to begin by focusing on performance optimization on the service capability level.
In this article we will explore several approaches for reducing the duration of service capability processing. The upcoming techniques specifically focus on avoiding redundant processing, minimizing idle time, minimizing concurrent access to shared resources, and optimizing the data transfer between service capabilities and service consumers.