Key challenges with iPaaS and how to resolve them

Key challenges with iPaaS and how to resolve them
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by Sanjeev Kapoor 21 Jul 2022

Nowadays, many enterprises use cloud computing infrastructures and cloud services to support their operations. In several cases, they take advantage of multiple and heterogeneous services to support their operations in the scope of multi-cloud environments. This results in “siloed” business operations that are fragmented and characterized by poor automation and intelligence. For example, if you’re using business applications across multiple clouds, you’re at risk of encountering data discrepancies and errors. This can lead to unnecessary expenses for your organization.  Therefore, organizations are seeking for effective ways to integrate different cloud services.

The Integration Platform as a Service (iPaaS) paradigm allows enterprises to integrate different cloud applications and develop workflows. Modern iPaaS solutions standardize how applications are integrated into an organization, making it easier to automate business processes and share data across applications. This is especially helpful for large enterprises with complex processes, since iPaaS streamlines business process management. iPaaS technology implements a single interface for simplifying cloud integration and bridging gaps across systems. This makes the use of business applications more seamless for the employees of an enterprise, making the software secure and reliable.

In the scope of the iPaaS paradigm services are accessed using open APIs offered by different cloud applications. This facilitates developers to produce integrated cloud applications regardless of the underlying heterogeneity of cloud infrastructures and services.

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The Challenges of iPaaS Deployment

When implementing and deploying iPaaS cloud services enterprises are confronted with many different challenges.

The first challenge is the heterogeneity of data models and APIs. Even when using standards-based protocols, it is not always easy to ensure that data can be shared and used across applications. For example, the Open Data Protocol (OData) standard allows applications to access data from multiple sources via a single interface, but it can’t guarantee that all data are consistent. A further complication is that each application might have different requirements for accessing this data, which makes it difficult to create a single interface that meets all needs. To alleviate this challenge there is usually a need for designing and deploying some business interoperability solution. However, unifying the business semantics of different cloud applications is a challenge because there are many different types of applications with different business requirements. For example, some applications have an XML interface, while others use JSON. Likewise, some applications have SOAP-based APIs for security reasons, while others support OAuth2 for authentication. In addition, not all applications support all features. For example, some databases have no support for geospatial queries or complex data types.

Another challenge is addressing different cloud environments and cloud models as part of an integrated approach. For example, some companies may use public clouds (e.g., Amazon Web Services (AWS) and Microsoft Azure), while others prefer private or hybrid clouds. Each of these options has its own advantages and disadvantages when it comes to speed, scalability, reliability, and cost. Hence, when it comes to creating an integrated environment some of these requirements might be compromised. This makes it very difficult to create a unified view of these disparate environments so that they appear as one consistent environment when viewed through an iPaaS platform.

One more challenge relates to offering smart security mechanisms across cloud applications. This means protecting both the application itself and its users by ensuring that only authorized requests can access data and services in the integrated iPaaS environment. However, different cloud applications and services support diverse and sometimes conflicting security profiles. It is usually challenging to compromise the diversity of the various security profiles in ways that ensure strong cybersecurity for the integrated iPaaS infrastructure.

Most importantly, when implementing an iPaaS solution, enterprises must align business issues with technical challenges. Integration is motivated by the need to improve efficiency and business results. Therefore, the technical solutions should aim at solving business problems rather than keeping up with technology trends.


Best Practices for Successful iPaaS

Here are some best practices that can help enterprises start their iPaaS journey on the right foot:

  • Start with the Business Goal in Mind: The first step in overcoming iPaaS challenges is to start with the business goal first and seek the technical solution later. This is because it’s easy to get lost in all the features that are available on iPaaS platforms, but it’s important to make sure that your integration requirements are aligned with your business goals. Hence, when you have a clear picture of what needs to be done, you can begin looking for compatibility across vendors and services. For example, if you realize that you need to integrate with Salesforce, Adobe Marketing Cloud and Google Adwords, you need to seek for a technical solution that makes these three tools compatible with each other.
  • Define common data models and APIs: When building new systems or integrating existing ones, it’s important to define a common data model that all parties can use when communicating with each other. This will allow each system to understand what data it needs from another system in order to offer a proper set of data integration capabilities. It also makes it easier for users who want to integrate multiple systems together because they only need to learn one set of data models instead of having to learn them all separately.
  • Data model mapping: Once a set of common data models are defined, make sure that you map the data models of individual systems to the common models. This is one of the most common issues with data integration Companies often have different ways of representing information so it’s difficult for software developers to map each other’s data models accurately. It also means users must spend time learning how to use a new system instead of focusing on business needs.
  • Implementing the right connectors: Any iPaaS solution must use connectors between cloud applications and their data sources on one side, and between different cloud applications on the other side. These connectors can be implemented as standalone components or libraries that can be used by developers to connect their application with other cloud applications and with external services like other cloud databases or social networks.
  • Pay adequate emphasis on security integration: With the rise in cyberattacks and data breaches, many companies are becoming more protective about their data than ever before. This means that any integration solution will have to be highly secure and compliant with industry standards such as GDPR (General Data Protection Regulation) or HIPAA (Health Insurance Portability and Accountability Act). In this direction, it is important to design integrated security policies that can be applied across different cloud platforms and tools.


iPaaS is a relatively new concept, but it has already begun to transform the way that developers work. In the coming years the iPaaS market will continue to grow as more developers look for the flexibility of an integrated platform that allows them to work with multiple cloud platforms without having to learn new languages or tools each time. That’s the reason why enterprises must take a closer look on iPaaS platforms and related service offerings.

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