streams

EventFlow: Event-driven microservices on OpenShift (Part 1)

EventFlow: Event-driven microservices on OpenShift (Part 1)

This post is the first in a series of three related posts that describes a lightweight cloud-native distributed microservices framework we have created called EventFlow. EventFlow can be used to develop streaming applications that can process CloudEvents, which are an effort to standardize upon a data format for exchanging information about events generated by cloud platforms.

The EventFlow platform was created to specifically target the Kubernetes/OpenShift platforms, and it models event-processing applications as a connected flow or stream of components. The development of these components can be facilitated through the use of a simple SDK library, or they can be created as Docker images that can be configured using environment variables to attach to Kafka topics and process event data directly.

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SCTP Stream Schedulers and User Message Interleaving

SCTP Stream Schedulers and User Message Interleaving

As some may have noticed already, a new request for comments (RFC) regarding the Stream Control Transmission Protocol (SCTP), RFC8260, has been published recently. This RFC defines two major changes for the SCTP protocol, originally defined in RFC4960:

1) Stream schedulers, which control which stream gets served next when sending a data chunk over the wire.
2) I-Data chunk, which extends DATA to overcome some of its limitations.

This blog post will go over the two changes, pointing out the benefits of using the stream schedulers, and especially when using them together with the new I-Data chunks.

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Infinispan’s Java 8 Streams Capabilities

Let’s be honest: it’s pretty exciting that Infinispan now supports Java 8 for many reasons, but perhaps one of the most anticipated reasons is because of the new stream classes. The main reason for this is the fact that it completely transforms the way we process data. Instead of having to iterate upon the data yourself, the underlying stream does this for you, and all you have to do is provide the operations to perform on it. This is perfect for distributed processing because the implementation handles the iteration entirely.

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