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Messaging is essential to modern life and how you get things done. So, without messaging, how would the world look? This question may appear far-fetched, but it’s a significant concern for computing. How do you talk to software? What is the mechanism through which software programs communicate with each other? How does software speak to you?

This article introduces REST and event-driven architectures and explains why organizations should move to an EDA to maximize customer satisfaction.

In this article, we’ll explore why and how using a managed Apache Pulsar service saves you time and energy by reducing toil. We’ll explore some partners that offer a Pulsar as a service solution and highlight their strengths and challenges to help you select a managed service to use.

In this article, we’ll explore what event streaming is, how it works, and discuss the growing importance of event streaming. Then, we’ll highlight how we can simplify the task of learning event streaming with the help of Apache Pulsar.

Let’s explore some advantages and challenges of moving from JMS to Pulsar.

In this article, we'll evaluate the features, architectures, performance, and use cases of Apache Pulsar versus Kafka, to help you decide which is the better solution for you.

In this article, we’ll examine how Pulsar Schemas work and contrast them with schemaless systems to determine the best approach. We’ll also demonstrate how to use Java clients with Pulsar.

Almost any application that requires real-time or near-real-time data processing benefits from having a message queue or streaming data processing component in its architecture. Online food ordering apps, e-commerce sites, media streaming services, and online gaming are straightforward examples. But weather apps, smart cars, health status apps with smartwatch technology, or anything Internet of …

I would also like to focus this reading on what is Pulsar and how it works under its own merits rather than comparing it against apache Kafka. I am taking this approach as there is plenty literature doing this already and because from a messaging system architecture both of these paradigms, up to a point, are different.

This guide will walk you step by step to deploy a Pulsar instance with one cluster but prepared already to extend the deployment further, including more Pulsar clusters at a later stage.

This article explores how to enable observability for your Pulsar environment using Prometheus and Grafana, starting from a demo standalone Pulsar cluster. You then learn how to import sample Grafana dashboards for Pulsar from GitHub. Finally, once everything is up and running, we zoom in on several of the standard and crucial metrics for building your observability dashboards on Pulsar.

This guide is for getting started using the Pulsar binaries. Lets do this!

Getting started with Pulsar using containers on your desktop

This guide is for getting started using the Pulsar on Kubernetes

A collection of guides to help you get started with Pulsar