The cloud is now the most popular method for expanding or modernizing apps. There are however instances where the move isn't easy and can be difficult, for instance, when it comes to migrating applications that require information from a mainframe. Moving the data and applications at certain points could be out of the sync. When the migration is in progress, the mechanisms must be in place to enable interoperability between legacy workloads and to access data outside into the mainframe. For this scenario, there is Data Format Description Language (DFDL) which is an open-standard modeling language that comes from the Open Grid Forum (OGF) can be utilized to access data from an IBM mainframe e.g., IBM Integration Bus.

DFDL utilizes a model or schema that permits binary or textual data to be interpreted out of its natural format, and then presented as data set from the mainframe (i.e. an it is a logical representation of data's contents, regardless of physical form). In addition, are you seeking to learn about more about Google Cloud in-depth knowledge and hands-on expertise, including designing, development, and managing an efficient, secure cloud-based system for your business's requirements. It also will give you the foundation to take an exam called the Google Certified Professional Cloud Architect exam Check out Google Cloud Certification.

DFDL Processing in conjunction with IBM App Connect

When we think about solutions to process and parse data that are described in DFDL One of the choices previously was IBM App Connect which permits the development of customized solutions through IBM DFDL.

We are pleased to announce Google Open-Source DFDL Processor with Google Cloud

At Google we strive to create for all people all over the world. In this regard Google Cloud's Google Cloud team has developed and made open-source the solution called DFDL Processor, which can be easily accessible & customized for businesses to utilize.

We recognize that mainframes may be costly to manage and maintain and maintain, integrated Cloud Firestore and Bigtable as the databases for storing data for the DFDL definitions. Firestore is able to provide 100K reads and 25K writes 100K deletes, and 1TB of storage every month for about 186 dollars per month. On the other side, Bigtable provides a fast and scalable database solution that is capable of storage of petabytes, or even terabytes of data at a cheaper cost. The move away from mainframes and the adoption of cloud-based solutions for database will save businesses thousands of dollars each month.

We have replaced App Connect using our open-source DFDL processor Cloud Pub/Sub service and the open-source Apache Daffodil Library. Pub/Sub links the mainframe to the processor, and also connects the processor to downstream applications. It also includes the Daffodil Library helps compile schemas and output information sets to support the DFDL definition as well as the message. The total cost of using the Pub/Sub service as well as Daffodil Library Daffodil Library comes out to around $117 per month. This implies that an organization could reduce costs by a minimum of $380 per month with this method.

How does it work

The information described in DFDL typically requires to be made available in widely used formats , such as JSON to be accessed by downstream programs that may have already been moved to an environment that is cloud-native. 

Conclusion

In this article we've reviewed various pipelines for processing the data specified in DFDL along with cost comparatives between these pipelines. We also have shown how to utilize Cloud Pub/Sub, Firestore, and Bigtable to build services capable of listening for events in binary format, removing the relevant DFDL description from an managed database and processing it to produce an JSON file that can be used by downstream applications with well-established libraries and technologies. If you want In-depth knowledge can be acquired with better preparation from the GCP Certification Cost India.