Author: admin

#InternetofThings #AI https://goo.gl/SjJ1VS #Technology #IoT #ML

ICYMI: I’ve been thinking about the potential for measuring value exchange at the API management level a lot more lately, and while I’m working on a project to profile banks that are needing to comply with the PSD2 regulations in Europe, I’m thinking about the missed opportunities for the API providers I’m using to fuel my research to leverage the value I’m generating. I’m using a variety of data enrichment APIs for helping add to the contact data, corporate profiles, images, documents, patents, and other valuable data to what I’m doing as part of my wider research into the API space. While these APIs have valuable services that I am paying for, all of the APIs are just using one HTTP verb – GET.

On a regular basis I come across incorrect, or incomplete data, and as part of my work I dive in and correct the data, and continue to connect the dots. I often find better copies of logos, add in relevant business profile data, and I always provide very detailed information regarding a company’s API – which I find to be some of the most telling aspects of what a company does, or doesn’t do. I’m thankful for the services that the third-party APIs I utilize, but I think they are missing out on a pretty big opportunity for trusted partners like me to be able to POST or PUT the data I am gathering back to their systems. https://goo.gl/x4eLjK #DataIntegration #ML

We were exchanging emails with the APIMetrics team this week, discussing the challenges that come up when monitoring APIs. We are working through the different ways in which we can create real-time streams of data from monitors that APImetrics has set up, and one of the challenges you encounter when monitoring API infrastructure at scale is the ability to sift through large volumes of signals to understand what truly matters. When you are monitoring a large number of APIs, depending on the approach, the overall health of the API, and the clients that are consuming resources, you are likely to experience regular waves of HTTP status codes to sort through looking for the responses that actually matter and mean something. We are thinking about how cutting HTTP status code noise will make API monitoring streams more intelligent.

As we were discussing this, the topic of machine learning (ML) came up, and how we can use it to help make sense of the potentially huge amounts of HTTP status codes we’ll have to process. Allowing us to not respond to individual signals, but groups or patterns of signals, and make API monitoring a little more intelligent, and reduce the chances we’ll miss some important monitoring updates. Using machine learning to do the heavy lifting of looking through large amounts of data, and rely on humans to do the responding when relevant patterns are uncovered. If you rely on humans to look at every signal returned they are inevitably going to burn out, miss patterns, and become blind to much of what is returned. By leaning on ML to look through the volume of data, we can lighten the load for the human, and help them be a little more efficient in what they deliver. https://goo.gl/cXToqw #DataIntegration #ML

ICYDK: APIs are hard to talk about across large groups of people while ensuring everyone is on the same page. APIs don’t have much of a visual side to them, providing a tangible reference for everyone to use by default. This is where OpenAPI comes in, helping us “see” an API, and establish a human- and machine-readable document that we can produce and pass around, and use as a reference to what an API does. OpenAPI makes me feel like I have a handle on what an API does, in a way that I can actually have a conversation around it with other people–without it, things are much fuzzier.

Many folks associate OpenAPI with documentation, code generation, or some other tooling or service that uses the specification – putting their emphasis on the tangible thing, over the definition. While working on projects, I spend a lot of time educating folks about what OpenAPI is, what it is not, and how it can facilitate communication across teams and API stakeholders. While this work can be time-consuming, and a little frustrating sometimes, it is worth it. A little education and OpenAPI adoption can go a long way to moving projects along, because (almost) everyone involved is able to be actively involved in moving API operations forward. https://goo.gl/c5znu1 #DataIntegration #ML