From a cruising altitude, all Enterprise Service Bus (ESB) services look the same, promising scalability and agility to grow your IT environment. However, every ESB use case is a different entity and companies embracing it should expect setbacks, just like using a bus for transportation. You face traffic jams, breakdowns, excess fuel consumption, frequent repairs, and other technical problems. Here are 6 old bus problems that overflow while enabling integration between disparate data residing across cloud and on-premise environments.
An ESB performs several tasks, but among many things it should deliver data at the right place to the right user. Business operations face disruptions if the bus is not accessible to users and heavily code based.
A right solution makes data interchange easy by allowing users to connect with service layer and bringing data from any network without delay. It delivers easy access for exchanging mass amounts of data. It is built up from the ground to support business critical technology changes without lengthy test cycles. You need to rethink your ESB strategy if its interface is not accessible or doesn’t allow you to add or remove obsolete services.
This is what happens in a conventional ESB integration model. A developer develops code for building integrations without knowing what other team members are doing. The testing team raises bugs and again sends them to the development team. The same process is repeated by multiple teams until they end up creating spaghetti services. Even developers face difficulties in understanding which point was connected to which service. This complex integration hairball strains connectivity and slows down data movement.
An ESB framework should continuously support long-running transactions arriving from multiple data sources in cloud or on-premise. Teams face perennial disruptions if incomplete workloads are moved to target database. An ESB framework in place must deliver performance to transport heavy duty workload between source and target systems with integrity.
There was a time when only employees were generating data in an organization. In the current scenario, smart machines, analytics, gadgets and sensors are also generating data. Jurassic-age ESB approaches are not sufficient to support this new data arriving from bare-metal servers, cloud resources, and other intelligent machines. A forward-thinking ESB model allows users to extract and decipher hybrid data generated by continuously flowing events and streams. This helps in removing friction between new & old technologies and improving business outcomes.
Nobody uses a crane to pick up a needle. Moving workloads with a conventional ESB model can be that frustrating. Businesses find themselves stuck in a rut when they need to convert data formats during business exchange. A modern day ESB framework should pack robust functionalities to manage all external connections and data interfaces for your organization. It should deliver dynamic services to convert partner data from any-to-any format and respond faster to his needs. It needs to make service delivery easy by enabling simple data mapping functions to specify format conversion and translation rules.
ESB malfunctions in a typical web environment where a logical combination of applications is defined by manual coding. It might be a good solution where a small number of applications are running locally. However, it will be better to use an ESB engine supported by a Service Oriented Architecture when you have multiple business applications and repositories & partners, both in cloud and on-premise. It accelerates business agility by infusing out-of-the-box reusability across IT layers and services. Users can automate orchestrations, map applications, and define business rules in simple, non-technical ways.
Integrating technologies with conventional ESB models can be an extensive process. Read this resource to know about these hazards in detail and see how we can help you.