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Real-Time Supply Chain With Apache Kafka in the Food and Retail Industry

The supply chain in the food and retail industry is complex, error-prone, and slow. This article explores real-world deployments across the end-to-end supply chain powered by data streaming with Apache Kafka to improve business processes with real-time services. The examples include manufacturing, logistics, stores, delivery, restaurants, and other parts of the food and retail business. Case studies include Walmart, Albertsons, Instacart, Domino's Pizza, Migros, and more.

The Supply Chain in the Food and Retail Industry

The food industry is a complex, global network of diverse businesses that supplies most of the food consumed by the world's population. It is far beyond the following simplified visualization :-)

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Portfolio Architecture Examples: Retail Collection

This article is a continuation of a series of posts about our project named Portfolio Architectures. The previous post, Portfolio Architecture Examples: Healthcare Collection, begins with a project overview, introduction, and examples of tooling and workshops available for the project.  You may want to refer back to that post to gain insight into the background of Portfolio Architectures before reading further.  

Retail Collection

The collection featured today is centered around architectures in the retail industry. There are currently seven architectures in this collection. We'll provide a short overview of each, leaving the in-depth exploration as an exercise for the reader.

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Industry Cloud Is The Future Of Cloud Transformation and Realization

Today, the cloud underpins most new technological disruptions and has proven itself during times of uncertainty with its resiliency, scalability, flexibility, and speed.

According to Gartner, Cloud adoption has expanded rapidly — more than 20% CAGR from 2020 to 2025 in total spending. But guess what — total cloud spend still makes up ‘only’ about 10% of global enterprise IT spend. So where is the barrier? What’s holding the Public Cloud penetration and pervasive usage inside enterprises?

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Retail data framework – Common architectural elements

article imageIn our previous article from this series we introduced a use case around the data framework for retail stores.

The process was laid out how we've approached the use case and how portfolio solutions are the base for researching a generic architectural blueprint.

The only thing left to cover was the order in which you'll be led through the blueprint details.

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Retail Data Framework — An Architectural Introduction

article imageThis article launches a new series exploring a retail architecture blueprint. It's focusing on presenting access to ways of mapping successful implementations for specific use cases.

It's an interesting challenge creating architectural content based on common customer adoption patterns. That's very different from most of the traditional marketing activities usually associated with generating content for the sole purpose of positioning products for solutions. When you're basing the content on actual execution in solution delivery, you're cutting out the chuff.

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Augmented Reality Demo With Apache Kafka and Machine Learning

Augmented Reality (AR) and Virtual Reality (VR) get traction across industries far beyond gaming. Retail, manufacturing, transportation, healthcare, and other verticals leverage it more and more. This blog post explores a retail demo that integrates a cutting-edge augmented reality mobile shopping experience with the backend systems via the event streaming platform Apache Kafka.

Augmented Reality (AR) and Virtual Reality (VR)

Augmented reality (AR) is an interactive experience of a real-world environment where the objects in the real world are enhanced by computer-generated perceptual information. AR is a system that fulfills three basic features: a combination of real and virtual worlds, real-time interaction, and accurate 3D registration of virtual and real objects.

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Omnichannel Retail and Customer 360 With Apache Kafka

Event Streaming with Apache Kafka disrupts the retail industry. Walmart's real-time inventory system and Target's omnichannel distribution and logistics are two great examples. This blog post explores a key use case for postmodern retail companies: Real-time omnichannel retail and customer 360 with data in motion.

Disruption of the Retail Industry with Apache Kafka

Various deployments across the globe leverage event streaming with Apache Kafka for very different use cases. Consequently, Kafka is the right choice, whether you need to optimize the supply chain, disrupt the market with innovative business models, or build a context-specific customer experience.

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Business optimisation architecture – Common architectural elements

In my previous article from this series I introduced a use case around business optimisation for retail stores. 
The process was laid out how I've approached the use case and how portfolio solutions are the base for researching a generic architectural blueprint.
The only thing left to cover was the order in which you'll be led through the blueprint details.

This article starts the real journey at the very top, with a generic architecture from which we'll discuss the common architectural elements one by one.

Blueprints review

As mentioned before, the architectural details covered here are base on real solutions using open source technologies. The example scenario presented here is a generic common blueprint that was uncovered researching those solutions. It's my intent to provide a blueprint that provides guidance and not deep technical details.

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Beginner’s Guide to Building an Online Retail Web Shop Workshop (Guided Rules)

With the release of Red Hat Decision Manager 7.3, I've started updating my free online workshop, a beginners guide to building an online retail web shop.

The previous article covered creating a domain-specific language or DSL for your online retail web shop.. This update is the for the fifth lab in this workshop, with more to follow. Learn how to create guided rules with Red Hat Decision Manager.