The requirement is to exploit an on-prem soap service from a cloud hosted micro service through Apigee layer. Why we have chosen Apigee is to simply apply the policies for XML to JSON and vice versa conversion. But Security is a big concern here. How currently the on-prem works is based on IP white-listing, but that's not possible in this case as we should whitelist the Apigee CIDR which again will be another security issue as other applications on the range can access the service.Another possible option we looked at is to route the traffic from Apigee to an HA proxy (This server comes under the service specific subnet) and then to on-prem service, so we only need to white list the ranges where HA proxy resides. We cannot change the on-prem service to accept any ApiKey, so that's also not an option. Is there any better solution do you think can be done to achieve this?
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Machine Learning or ML is currently is much hype and everyone is making some cool stuffs or want to make some awesome and world changing applications through it.
There are many applications out there that can help you to do son, without even writing any code, but that's not machine learning, it is something which combines both mathematics and computer science to develop a system or application that can learn through the mistakes it make.
Machine learning involves some complex mathematical functions that can be coded into computer program and can be installed on devices and many complex tasks can be performed.
There are many applications which make use of machine learning algorithm and predicts what will be the output, one such application is weather forecasting which uses complex mathematical functions to generate results for the same.
Machine learning can do the following:
- Finding, extricating and outlining pertinent data
- Making predictions dependent on the analyzed information
- Figuring probabilities for explicit outcomes
- Adjusting to specific improvements self-sufficiently
- Upgrading forms dependent on perceived examples
and much more.
ML is a sub-territory of Artificial intelligence, whereby the term alludes to the capacity of IT frameworks to autonomously discover answers for issues by perceiving designs in databases or it can also be defined as Machine Learning empowers IT frameworks to perceive designs based on existing calculations and informational collections and to create sufficient arrangement ideas. Along these lines, in Machine Learning, counterfeit information is created based on experience.
So as to empower the software to freely create answers, the above activities of individuals are essential. For instance, the necessary calculations and information must be taken care of into the frameworks ahead of time and the separate examination rules for the acknowledgment of examples in the information stock must be characterized.