iPAAS' are essentially ESBs remarketed for the cloud for organatisations without the in-house expertise to coordinate building their own integration hub with a combination of tools like Kafka and API management gateways.
Organizations lacking the
* Architectural leadership
* Coordination capabilities
* Engineering resources
* strong comms between teams
tend to go for these solutions to paper over their existing problems. Particularly those around engineering capabilities.
These solutions work great for a while until the edge cases around data arrival and consumption usages resurface.
It's important to note that these solutions shine when it comes to the API discoverability across teams and light data format translations but as soon as that has happened get your data out quick!
Don't be tempted by their in-house solutions that try to solve caching, scaling and the ETL languages provided because they will tend to be half-baked and not as battle tested and will lock you in. The commitment for a large org using these systems is a 5-10 horizon.
By all means check them out and be ready for alot upfront design work to find the sweet spot and alot of engineering effort and frustration (alot).
* Coordination capabilities
* Engineering resources
* strong comms between teams
tend to go for these solutions to paper over their existing problems. Particularly those around engineering capabilities.
These solutions work great for a while until the edge cases around data arrival and consumption usages resurface.
It's important to note that these solutions shine when it comes to the API discoverability across teams and light data format translations but as soon as that has happened get your data out quick!
Don't be tempted by their in-house solutions that try to solve caching, scaling and the ETL languages provided because they will tend to be half-baked and not as battle tested and will lock you in. The commitment for a large org using these systems is a 5-10 horizon.
By all means check them out and be ready for alot upfront design work to find the sweet spot and alot of engineering effort and frustration (alot).