Refine
Document Type
Language
- English (4)
Has Fulltext
- yes (4)
Is part of the Bibliography
- no (4)
Keywords
Even for the more traditional insurance industry, the Microservices Architecture (MSA) style plays an increasingly important role in provisioning insurance services. However, insurance businesses must operate legacy applications, enterprise software, and service-based applications in parallel for a more extended transition period. The ultimate goal of our ongoing research is to design a microservice reference architecture in cooperation with our industry partners from the insurance domain that provides an approach for the integration of applications from different architecture paradigms. In Germany, individual insurance services are classified as part of the critical infrastructure. Therefore, German insurance companies must comply with the Federal Office for Information Security requirements, which the Federal Supervisory Authority enforces. Additionally, insurance companies must comply with relevant laws, regulations, and standards as part of the business’s compliance requirements. Note: Since Germany is seen as relatively ’tough’ with respect to privacy and security demands, fullfilling those demands might well be suitable (if not even ’over-achieving’) for insurances in other countries as well. The question raises thus, of how insurance services can be secured in an application landscape shaped by the MSA style to comply with the architectural and security requirements depicted above. This article highlights the specific regulations, laws, and standards the insurance industry must comply with. We present initial architectural patterns to address authentication and authorization in an MSA tailored to the requirements of our insurance industry partners.
To avoid the shortcomings of traditional monolithic applications, the Microservices Architecture (MSA) style plays an increasingly important role in providing business services. This is true even for the more conventional insurance industry with its highly heterogeneous application landscape and sophisticated cross-domain business processes. Therefore, the question arises of how workflows can be implemented to grant the required flexibility and agility and, on the other hand, to exploit the potential of the MSA style. In this article, we present two different approaches – orchestration and choreography. Using an application scenario from the insurance domain, both concepts are discussed. We introduce a pattern that outlines the mapping of a workflow to a choreography.
This article looks at a proposed list of generalized requirements for a unified modelling of event processing networks (EPNs) and its application to Amazon Kinesis Data Analytics. It enhances our previous work in this area, in which we recently analyzed Apache Storm and earlier also the EPiA model, the BEMN model, and the RuleCore model. Our proposed EPN requirements look at both: The logical model of EPNs and the concrete technical implementation of them. Therefore, our article provides requirements for EPN models based on attributes derived from event processing in general as well as existing models. Moreover, as its core contribution, our article applies those requirements by an in depth analysis of Amazon Kinesis Data Analytics as a concrete implementation foundation of an EPN model.
This article looks at a proposed list of generalized requirements for a unified modelling of event processing networks (EPNs) and its application to Microsoft Azure Stream Analytics. It enhances our previous work in this area, in which we recently analyzed Apache Storm, Amazon Kinesis Data Analytics and earlier also the EPiA model, the BEMN model, and the RuleCore model. Our proposed EPN requirements look at both: The logical model of EPNs and the concrete technical implementation of them. Therefore, our article provides requirements for EPN models based on attributes derived from event processing in general as well as existing models. Moreover, as its core contribution our article applies those requirements by an in depth analysis of Microsoft Azure Stream Analytics as a concrete implementation foundation of an EPN model.
