On Demand Webinar:

TIBCO Cloud Integration Gives the Fastest Results & Lowest TCO Per AppVance Research

Modern application architectures, Agile and DevOps SDLC, and supporting channels like web, mobile, and IoT require you to reevaluate how you interconnect your systems and services.

Noted development expert Frank Cohen, founder of Appvance Inc., has recently released the 4th iteration of the company's PushToTest Integration Knowledge Kit. In this iteration, Frank and his team independently developed distributed applications using MuleSoft, Red Hat, Spring Boot, and the TIBCO Cloud Integration Develop component—which is based on the open source Project Flogo.

They built their applications to a specific use case using new architectural patterns such as cloud, microservices, serverless, and AWS Lambda. They documented and analyzed their productivity and experiences with each development environment, and found that TIBCO Cloud Integration gave the fastest results and lowest TCO.

You can download and utilize this free open-source Integration Knowledge Kit to perform your own evaluation. Your actual results will vary based on the requirements of the application that you develop.

Join Frank for this short webinar (with Q&A) as he walks through the Kit and shows you how to use it to compare the top technologies for integrating your systems leveraging a modern architecture.

This 30-minute on-demand webinar includes Q&A and covers:

  • Which integration approach is most efficient in terms of developer productivity?
  • Which approach allows you to make changes most quickly?
  • Key considerations for selecting an integration approach to support your microservices and serverless initiatives
  • Lessons learned on these platforms and how you can avoid pitfalls in going serverless with microservices

Get the kit, check out the webinar, and let us know your thoughts!

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AppVance Push to Test - Integration Knowledge Kit 2018 - Executive Briefing

Success with TIBCO:

27: Acquisitions

facilitated in 28 months

45 Percent

reduction in data errors

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