When moving to a hybrid cloud environment, integration between cloud and on-prem is a challenge. Here is how an iPaaS model helps and how to implement it.
A fair share of cloud migration challenges are spawned by weak integration between on-premise and cloud-based applications. These problems keep on resurfacing when the point-to-point network and hairball coding is used to integrate several applications. Developers develop code and throw it before the testing team for validation. And whenever there is a shakeup, developers need to repeat the entire process. This strategy is not ideal for companies with thousands of applications.
Once upon a time, applications were developed with little focus on integration with other applications. They were primarily stove-piped applications that offered one or two endpoints. These points don’t scale to accommodate SOA infrastructure. Lengthy code needs to be redeveloped to accommodate small changes. The following are some of the drawbacks of the hand-coded approach:
Historically, data was brought to the Central Processing Unit (CPU) for processing. This approach was changed as massive amounts of data soon overwhelmed the processor. The instant response was bringing multiple processors to data for processing and assessing. Each server consisted of small components to process individual elements of data sets. It was called parallel processing, where an infinite number of CPUs processed infinite numbers of data sets. In such an ecosystem, organizations face difficulties in scaling the ability of processors up to deal with a wide variety, volume, and velocity of data. As a result, teams encountered treacherously difficult challenges while:
To surmount these challenges, experts recommend organizations embrace a strategic integration approach that is based on industry best practices. Hybrid cloud adoption will see further increase and organizations undermining integration will fail to receive the benefits of cloud migration.
Initially, application leaders used ESB architecture to manage integration between applications and services. However, they realized that ESB doesn’t support scenarios where new and old applications run parallelly. It lacked scalability to accommodate new technology initiatives like Salesforce, Workday, Quickbooks, etc. Frequent IT intervention was needed at every layer to develop, test, and generate code.
Extract, Transform, and Load (ETL) was also used, but it suffered from many drawbacks, too. It only allowed getting data from a data repository. However, with the advent of Hadoop, this functionality has become outdated. Traditional row-and-column ETL doesn’t allow users to support storage of structured and unstructured data.
Modern applications use the Extended Markup Language (XML) format for storing data. On the other hand, physical machines use comma-separated values (CSV) for data storage. The ESB/ETL approaches are overwhelmed when too much data needs to be mapped from XML to CSV or CSV to XML. It is unwise to use these approaches for high speed and high volume projects.
Connecting applications through APIs is good, but it is not a silver bullet for more pervasive B2B integration needs. Specific APIs need to be developed for specific integration needs. And too much pressure is taken on when the same API muscle is used for multiple integrations. Organizations need to buy separate licenses for specific application integration scenarios.
Data has become a critical corporate asset and it is no longer a secondary asset. Jurassic integration approaches don’t help teams leverage data and engage customers. A greater degree of support from data integration tools is required to bring data from mobile, Internet of Things (IoT), and social channels.
Data security has become an even bigger concern as new and stringent compliances like the General Data Protection Regulation (GDPR) are looming. Conventional approaches don’t provide a safe passage through dense API cloud networks. A reliable pathway is needed that secures data at every endpoint.
Thorny challenges await application leaders when on-premise systems need to be integrated with cloud-based systems. And disruptions continue to resurrect in manual workflows. Let’s take a real-time scenario to understand this problem where manual steps will be used to connect SAP with Salesforce. This is a powerful combination of two trusted icons that can help organizations in becoming more productive.
Salesforce offers the Data Loader to integrate with other applications. To download the application, go to Salesforce Setup –> Data management -> Data Loader.
Lighting Connect is another approach to connect an SAP ERP Central Component (ECC) system with Salesforce, which will be discussed in this article. Here are the steps to integrate SAP with Salesforce with this tool.
Label:
Name:
Type:
URL:
https://sapes1.sapdevcenter.com/sap/opu/odata/sap/SALESORDERXX/
Connection Timeout:
High Data Volume:
Compress Requests:
Include in Salesforce Searches:
Custom Query Option:
Format:
Certificate:
Identity Type:
Authentication Protocol
Username:
Password:
Objects that end in __c are the custom objects that you created
The SAP Sales Order Execution Page Appears
Label
Name
Description
Account Name
Account Number
This method is cumbersome and it cannot be used over and again for integrating Salesforce data with other applications. This approach allows only access to SAP data and moving large chunks of data can be an uphill task.
Previously, it was only employees who were generating and accumulating organizational data into computer systems. Now users and machines are also generating the data across social channels, forums, online commerce, etc. Due to this change, organizations today have to deal with larger accumulated data generated by their customer facing platforms, monitoring systems, smart meters, etc. The next big challenge is unlocking this colossal amounts of data which holds massive hidden opportunities. Processing and refining such massive amounts of data is a next level challenge during cloud migration which can be addressed through iPaaS.
IT experts consider iPaaS is the best solution for defying the impact of disruption on security, data and analytics, communications, and endpoint technology. Smarter organizations are successfully overcoming their integration weaknesses and setting up future-ready IT architecture with this model. Next generation iPaaS model delivers compelling business benefits:
By simplifying application and data integration, iPaaS helps in modernizing IT architecture and setting up a cloud-first enterprise. The framework enables even business users to integrate with a gamut of external and internal business applications and processes safely and cost-effectively.
