Retailers’ interactions with customers are happening all the time, across channels, with lots of devices and endpoints. Modern retailers face new pressure points due to changes in their operational landscape.
There are multiple strategic answers to this question: be it logistics, innovation, business model, service, or product ecosystem. Let's look at this more simplistically.
This reactive approach towards Digital Platforms and lack of vision play into the hands of Amazon, which benefits from a unique business model that allows it to stay ahead of the curve.
Retail brands are challenged to use cutting edge technologies like Cloud, AI/ML, microservices, Data Mesh, automation, and personalization solutions efficiently. They fall behind due to inefficient legacy platforms.
Retailers today face a lot of technical challenges in order to meet growing customer demands. These are just a few to state.
Depends on a consistent single state.
Depends on a single database.
Depend on failure and consistency being handled in the database.
Events convey facts. Facts remain true regardless of what else happens in the system.
Ensures that the events can be reliably propagated throughout the system.
Our data is the event, some may be at rest, others are in motion.
Rather systems are constantly converging, propagating, and messaging based.
Retailers have to keep up with ever-changing customer expectations, maintaining customer loyalty. Customers expect a seamless buying experience. To attract customer loyalty, retailers need an experience that stands out. So many technologies exist to drive marketing and sales, operations, and customer experience, but they don’ t seem to work together.
Retailers can create buyer experiences that can combat the fickle nature of the modern consumer only by:
Retailers need to modernize their customer experience and operational efficiency to meet the demand of modern retail. Listed below are a few benefits of adopting modern architectural approaches.
To fulﬁ l your customer’ s expectations about omnichannel, you must integrate every piece of information about products, pricing, promotions, shipments, stocks, and orders, and keep it up to date. Microservices are great for such an evolutionary approach. This document will describe in detail the key differentiator that makes reactive microservices a perfect choice for retailers, who want to modernize their eCommerce infrastructure.
Using an asynchronous, non-blocking, message-driven approach, highly resilient, and elastic systems can be formed, resulting in a consistently responsive user experience.
High-performance, providing instant feedback based on user and API interactions in all circumstances. So that means that Reactive systems need to be responsive under load at peak periods.
Able to scale up and down predictably and elastically, on-demand, across cores, nodes, and clusters.
Self-healing, recovering, and repairing themselves automatically for seamless business continuity.
Processing messages in parallel, asynchronously, without blocking, ensuring loose coupling, isolation, and location transparency.
Modeling complex, highly concurrent software systems without using locks, threads, race conditions. Ensuring that developers working on isolated, autonomous, event-driven systems where their changes aren’ t at risk of causing cascading failures that bring down an entire system require a modern tech stack and agile processes to be defined.
Primary Benefits of Reactive Systems
Reactive Systems allow teams to be just as scalable as the technology itself. LinkedIn scaled up its engineering teams from ~50 to ~500 individuals. They couldn’ t have done that if they’ d needed complex coordination and cooperation amongst teams developing their systems.
Customers coming from a more traditional software development approach are surprised by how fast deployment is when working with the Reactive Platform. Going from a release every one or two weeks to deploying dozens of times a day is not uncommon. Releases that used to take hours, days or longer now happen in minutes.
PayPal processes over one billion streaming events per day on just 8 VMs, whereas earlier, they needed over 100 VMs.
T-Mobile in the US moved from using 144 machines, each processing 13,000 messages/second, to just 12 machines, each processing 5 million messages/second.
Reactive Systems provide opportunities for dramatic cost savings on infrastructure.
At least 50% of infrastructure reduction is reported by all customers and most experienced significant improvement. This is due to the asynchronous, non-blocking, message-driven nature of the underlying Actor Model runtime of Akka.
Zalando scales 100x every day to support the system load brought about by their daily sales promotions. Then they scale back down when the sales are over and use only the infrastructure required to support the current load. Zalando’ s business model would be completely unaffordable with a more traditional development approach.
Reactive Systems can scale to a degree that, until now, simply wasn’ t possible.
Verizon chose to rebuild their customer-facing system with Play and Akka after experiencing regular outages during high-load events, like iPhone launches and Black Friday. They expected 43 million customers to upgrade to the new iPhone after the launch, and they mandated zero downtime. Their new system has experienced no downtime at all since its launch.
Walmart Canada also experienced outages at vital times until they bolstered critical parts of their system with Reactive technology. They experienced their first Black Friday without any downtime and needed ~50% less infrastructure.
Reactive Systems can self-heal and continue operating in the face of inevitable failures that occur in production environments.
Increasing Resilience and Elasticity naturally increases responsiveness. No matter what is happening, your system can respond in a meaningful way to users. This responsiveness means users continue to trust your application. Even if their experience degrades in some way, no failure affects the entire system
There are several reasons why Reactive Systems offer a reduction in TCO compared to traditional systems.
We live in a world where we need to respond very quickly to users. To meet the needs of a modern digital retail solution, the platform needs to be Cloud-native, API-first, Reactive, Events-first, Domain-driven Design, Distributed, and Microservices based.
A variety of competing technologies claim to offer a fast path to microservices. However, decomposing a traditional application into individual services does not guarantee that you will realize all of the desired benefits. Reactive Microservices run in a distributed environment where network, hardware, and software failures are everyday occurrences. A microservice system can succeed initially, only to fail under increased load or unexpected spikes.
For systems with demanding requirements, RETISIO recommends Reactive Principles as the best way to design a system that copes well with uncertainty.
Reactive Principles, as defined in the Reactive Manifesto, include the properties of being responsive, resilient, elastic, and message-driven.
When designed with Reactive Principles, microservices have the following characteristics:
Each microservice is completely decoupled. Its lifecycle, including failure, has no impact on other microservices in the system.
Each microservice acts and makes decisions independently and publishes its behavior through an API.
Each microservice does one thing and does it well.
A microservice produces, consumes, and reacts to events.
Mobility (and addressability):
A microservice can be moved at runtime and can be reached in the same way regardless of its location.
Event thinking is a cultural change that sets organizations ready for genuine digital business innovation
Event thinking is the approach to conceptualizing (thinking of) and implementing business solutions, where business activity is driven by event notifications and the first priority of business is to sense the business context and assess the appropriate response options in business real time.
With event thinking, the primary differentiating role of IT shifts from business data guardian to a business "nervous system"; the business shifts to the always-sensing and always-ready digital-business-native mode of operation.
CQRS stands for Command Query Responsibility Segregation. At its heart is the notion that you can use a different model to update information than the model you use to read information.
Powerful, native persistence strategies like Event Sourcing and CQRS supported by Apache Kafka, Apache Cassandra ensure data consistency across your clusters.
The fundamental idea of Event Sourcing is to ensure that every change to the state of an application is captured in an event object. These event objects are themselves stored in the sequence they were applied, for the same lifetime as the application state itself.
To see how event sourcing works, consider the Order entity in a typical Order Management Process. Traditionally, each order maps to a row in an ORDER table along with rows in another table like the ORDER_LINE_ITEM table. But when using event sourcing, the Order Service stores an Order by persisting its state-changing events: Created, Approved, Shipped, and Cancelled. Each event would contain sufficient data to reconstruct the Order’ s state.
A variety of competing technologies claim to offer a fast path to microservices. However, decomposing a traditional application into individual services does not guarantee that you will realize all of the desired benefits.
If you are breaking down a monolithic legacy application into a set of microservices, and if those microservices are communicating via REST (Representational State Transfer), then you still have, in effect, a monolithic application.
For systems with demanding requirements, ARC recommends Reactive Principles as the best way to design a FUTURE READY SYSTEM. Reactive Principles include the properties of being responsive, resilient, elastic, and message-driven. The trend towards using a microservices-based architecture for systems design is significant and it is happening for good business reasons. By having small, discrete components that can be developed, deployed, and scaled independently, microservices-based applications can take advantage of cloud economics. Developers can build and deploy services much more rapidly.
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