With the proliferation of service meshes composed of Microservices, Application Programming Interfaces (API’s) and the API Management (APIM) solutions to develop, deploy, manage and govern both API’s and Microservices, the need for Site Reliability Engineering (SRE) best practices and approaches to converge with APIM produced machine data (data/application logging) has never been greater. Without the ability to intelligently collect, infer, inform and extract insights to improve the performance of the enterprise ecosystem of applications and services that make up your service mesh, the sprawl of API’s and microservices will inexorably overwhelm your ability to manage, much
One of the most exciting things about API’s is the ability to invoke them to parse and evaluate a message (i.e. an Order Status object), and, based on the contents of the message, distribute to up to N number of systems to complete the transaction(s). While traditional Message Queuing (MQ) solutions are the obvious Go-To (to ensure reliability, and support for asynchronous messaging), this blog post explores leveraging JMS to handle reliable, synchronous & asynchronous message delivery to an N number of downstream systems. How would you architect the solution?
The first pass is pretty simple: