Why the next generation Enterprise Service Bus (ESB) needs to be Intelligent

The communication layer of yesterday has evolved and has now become intelligent. The industry of tomorrow needs to add transformation and intelligent logic between the data end-points for enabling their long list of IoT use cases that they want to address.

Before 2000, engineers who coded interfaces between ERP systems, factory sensors, and machines realized that they needed a standard, recyclable interface to abstract and automate their coding, one can argue that was the origin of Service Oriented Architecture (SOA), one of the architectures from which ESB evolved. From the ESB followed the need of an Event Driven Architecture (EDA) to leverage insights when they occur, these were initial steps toward the integration of large enterprise systems such as:

• Enterprise Resource planning (ERP)  
• Customer Relationship Management (CRM) 
• Enterprise Financial Services (EFS)

Research shows that ESB is the most promising strategy for integrating business applications across distributed and diverse frameworks and platforms today. ESB provides elastic interfaces among numerous applications, systems and services. Utilizing ESB as a middleware layer creates a superset of both SOA and EDA. As such, ESB provides support for transforming messages, live streaming data, smart routing, as well as protocol transformation. ESB done right is also an important component of emerging machine learning applications.

Traditional Service bus explained

The service bus core functionality is often described as an inbox where a message can be placed for later processing in an asynchronous way. That means that the application that publishes the message in the inbox doesn’t have to wait for the application that processes the message to complete the message processing, thus freeing up the publisher to continue its work.

In more complex scenarios, there could be one publisher and multiple subscribers to each message. The order the messages are received might be important to the order they are processed even when distributed across multiple subscribers (e.g., first in, first out).

The subscriber might occasionally poll the service bus for new messages, or it might leave a connection open and receive any messages as they are posted. The messages might be transactional in nature, or need to be scheduled to be processed at a later date. 

Industry 4.0 raises the bar

But the promise of Industry 4.0 sets new expectations for the traditional service bus architecture. Meaning that the service bus now needs more functionality than before. There is a need for an intelligent integration layer that not only moves messages between endpoints but can run real-time applications and workflows with full data analytics capabilities included. 

Moving from the message broker into a fully hybrid architecture with truly intelligent data workflows requires new thinking.

The service bus of tomorrow now needs to be adopted in all 3 major communication layers:

(Cloud based) Service Bus

Azure Service Bus is an example of a cloud-based service bus, built for messaging as a service. The cloud-based service bus is typically used for integrating microservices and cloud applications.

The cloud-based service bus typically doesn't offer any intelligence within the integrations, it is used for communication only. The intelligence is added at the data destination.

Enterprise Service Bus (ESB)

RabbitMQ and NServiceBus are other popular options for enterprise messaging services. Both can be run on-premise if needed. RabbitMQ is an open-source system that has many of the same features as Azure Service Bus, and NServiceBus is a commercial product that is tailored specifically for the Microsoft .Net ecosystem.

The traditional ESB is built to move messages between end-point systems, it is not built to handle intelligence which limits its usability to meet the requirements of tomorrow.

Manufacturing Service Bus (MSB)

This is a relatively new concept for describing the need for a communication and abstraction  layer on the factory floor. Used for integrating various machines, sensors, systems and services on the factory site.

The MSB can be compared to an Intelligent Edge Layer. Being a carrier for advanced analytics, machine learning, common data models and other necessary features for enabling machine data for the rest of the network.

The future service bus needs to be intelligent

The rise of the fourth revolution is putting pressure on the current industry, both technically and organizationally, resulting in new requirements on all data layers:

• Real-time event-driven communication - because machines need data in milliseconds. They can’t wait for network operations to adjust the production.
• Reactive is moving towards Predictive - creating a need for Machine Learning abilities within both the MSB and the ESB layers.
• All data is needed - the future demands that all data producers must be connected and analyzed.
• Do more with the same resources - Empower domain experts to leverage their knowledge using digital solutions. Meaning that OT and IT must work together, not in silos.
• Any-to-any data approach - the need of a common data model or a unified namespace to enable data comparison and usage of all asset data.

Complement and Replace

The industry is in critical need of finding an easy way to complement existing infrastructure to leverage the value that their data conceals. And at the same time in a need of finding new solutions for leveraging data to the fullest. Legacy and greenfield need to work together.

The industry needs to find a way to:

• Easily connect to all their sensors, machines, systems and services throughout the entire production site.
• Transform, normalize and filter data in an easy way to obtain functional data sets for further analysis and storage.
• Apply Machine Learning for predictive analysis at scale, in a cost efficient way
• Leverage computer vision for quality inspection, site monitoring, automatic readings etc
• Enable machine to machine communication
• Connect to new sensors and data sources like vision, video and sound sensors.
• Centralized development and analysis, with truly hybrid execution.
• Standardize and enforce a common data model over the whole network of connected assets.

The positive news is that existing service bus infrastructures can be complemented with an Intelligent Integration Layer that makes it possible to add one use case at the time.

Purpose built to address the future

The Crosser platform is purpose built to meet the industry needs of the future. Offering Cloud based innovation, management and orchestration of Industry 4.0 use cases:

• Hybrid-first. The only solution on the market that can run in the cloud, on-premise and at the industrial edge with the same software.
• Covers all three integration layers with the same platform
• Advanced streaming analytics
• Real-time integrations for machine-to-machine communication
• Pre-built connectors for industrial protocols and systems. Connect to over 800 applications.
• Built to handle the lifetime of your analytics and machine learning projects. Simplifying every step of the ML project.
• Large scale data mapper that can handle data model templates for a unified approach to all asset data.

Crosser is more than tech

Crosser’s low code approach to industry 4.0 use cases radically changes the way global enterprises engage their digitization projects. The low code approach accelerates all phases of the digital project. Increasing productivity, simplifying innovation and shortening time to value.

Among our customers we can see that the Low Code approach:

• Empowers existing domain experts to build advanced digital solutions without writing code
• Bridging OT and IT into one platform. Simplifying cooperation between departments.
• Graphical overview of all projects and use cases radically simplifies all phases of the project. Also simplifies handover between teams and departments.
• Centralized management and orchestration. Scale with ease using the cloud and on-premise management portal.
• Offers Enterprise Grade control and governance that reduces the workload on both IT and OT and gives a very low lifecycle management cost.