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This APIContext API latency heat map shows relative performance of a standard, reference GET request made to servers running on all the Google locations and via the Google global load balancer. Calls are made from AWS, Azure, IBM and Google clouds, and data is stored for all steps of the API call process and the key percentiles under consideration.

How we do it?

APIContext has set up a network of HTTPbin servers which make reference calls from all our public locations hosted on AWS, Amazon, Google and IBM. 

The calls themselves are either made in sequence from each data-center to each end point or via the Google Global Load balancer.

What this means to you?

With the basic chart you can see the impact of making a call from location X to cloud data center Y – either in terms of geography, usually the TCP connect time, or the location look up time.

Things to watch for

Not all cloud services work well with all the others. What works great on an all AWS setup can be poor if one of your partners works with Azure. It’s important to understand these combinations and how they can impact customers and users when trouble shooting why you are missing problems other users are complaining about.


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