Hey, Tim here. I was the one talking about this on the podcast. As I mentioned in the podcast, the monitoring of APIs was a method that we quickly found out didn't really scale or help. It suffered from a few issues, mainly the vendors were updating their api's but not their docs. The way that we tackled it in the end was to let things fail. We have actually taken this approach with many things i.e. fail, but have a method which cleans up after the new changes have been deployed.
The way we handle it now is that our integration will start throwing serialisation errors. This will then have our platform send a probe to get a RAW response from the system and then we let the admin see side by side, the old data and the new data. This allows the developers to schedule a new deployment to make these fixes. The good thing is that when the new deployment is made, the orchestration around it will handle fixing the data that it couldn't resolve while the serialisation was failing.
We do get other benefits out of this, including the ability to better handle integrations where you have absolutely no idea what to expect from the API e.g. old Oracle, IBM products that don't have discovery endpoints like Dynamics, Salesforce etc does.
Our recommendation after managing so many integrations is "let things fail". Embrace a data integration pattern that allows things to fail.
The way we handle it now is that our integration will start throwing serialisation errors. This will then have our platform send a probe to get a RAW response from the system and then we let the admin see side by side, the old data and the new data. This allows the developers to schedule a new deployment to make these fixes. The good thing is that when the new deployment is made, the orchestration around it will handle fixing the data that it couldn't resolve while the serialisation was failing.
We do get other benefits out of this, including the ability to better handle integrations where you have absolutely no idea what to expect from the API e.g. old Oracle, IBM products that don't have discovery endpoints like Dynamics, Salesforce etc does.
Our recommendation after managing so many integrations is "let things fail". Embrace a data integration pattern that allows things to fail.