#Cloud

Hi Community,

Watch this video to learn how to manage your HealthShare HealthConnect Cloud deployments using the InterSystems CloudServices Portal. Inspect the details of your deployment, create users and productions in Health Connect Cloud, and access the System Management Portal for a given deployment:

⏯ Navigating the Health Connect Cloud Portal

https://www.youtube.com/embed/Lyx6TlSWCGQ
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Hi Developers!

Here is the score of technical bonuses for participants' applications in the InterSystems Developer Tools Contest 2023!

Hi Developers,

Enjoy watching the new video on InterSystems Developers YouTube:

⏯ InterSystems Cloud Services Overview

https://www.youtube.com/embed/wJXvfeQoZxQ
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Hey Community,

Enjoy watching the new video on InterSystems Developers YouTube:

⏯ Creating an HL7 v2 to FHIR Transformation Pipeline with HealthLake Target

https://www.youtube.com/embed/5ZOcooTo0fs
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Why SSH ?

If you do not have direct access to the server that runs your IRIS Docker container
you still may require access to the container outside "iris session" or "WebTerminal".
With an SSH terminal (PuTTY, KiTTY,.. ) you get access inside Docker, and then, depending
on your needs you run "iris session iris" or display/manipulate files directly.

Note:

What is Distributed Artificial Intelligence (DAI)?

Attempts to find a “bullet-proof” definition have not produced result: it seems like the term is slightly “ahead of time”. Still, we can analyze semantically the term itself – deriving that distributed artificial intelligence is the same AI (see our effort to suggest an “applied” definition) though partitioned across several computers that are not clustered together (neither data-wise, nor via applications, not by providing access to particular computers in principle). I.e., ideally, distributed artificial intelligence should be arranged in such a way that none of the computers participating in that “distribution” have direct access to data nor applications of another computer: the only alternative becomes transmission of data samples and executable scripts via “transparent” messaging. Any deviations from that ideal should lead to an advent of “partially distributed artificial intelligence” – an example being distributed data with a central application server. Or its inverse. One way or the other, we obtain as a result a set of “federated” models (i.e., either models trained each on their own data sources, or each trained by their own algorithms, or “both at once”).

Hi Developers,

The new video from Global Summit 2019 is available on InterSystems Developers YouTube:

⏯ InterSystems Cloud Manager

https://www.youtube.com/embed/Gh1zRwEUUGk
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Hi Community!

The new video from Global Summit 2019 is already on InterSystems Developers YouTube:

⏯ Managing the Transition from On-Premises to Cloud-Based SaaS

https://www.youtube.com/embed/SI_F3zaNBVM
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Some of you on the Developer Community have probably interacted with @Luca Ravazzolo if you are interested in cloud and container topics... If so, you'll enjoy Episode 2 of our new podcast — we chatted with Luca about Kubernetes and the InterSystems Kubernetes Operator. He does a great job of explaining the technology and its benefits here!

https://5e18edf067eb59-03854285.castos.com/player/147141
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Hi Community,

The new video from Global Summit 2019 is already on InterSystems Developers YouTube:

⏯ The Value of Developing with Containers

https://www.youtube.com/embed/4-Vsb-MdJMw
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Hi Community!

I'm pleased to share the announcement that InterSystems IRIS Data Platform is available on Amazon Web Services marketplace!

When you hear people talk about moving their applications to the cloud, are you unsure of what exactly they mean? Do you want a solution for migrating your local, physical servers to a flexible, efficient cloud infrastructure?

This summer the Database Platforms department here at InterSystems tried out a new approach to our internship program. We hired 10 bright students from some of the top colleges in the US and gave them the autonomy to create their own projects which would show off some of the new features of the InterSystems IRIS Data Platform. The team consisting of Ruchi Asthana, Nathaniel Brennan, and Zhe “Lily” Wang used this opportunity to develop a smart review analysis engine, which they named Lumière. As they explain:

Let assume you have a infinitely scaling algorithm implemented in your application, using replication, ECP, or any other means of horizontal scaling, and let assume you know how to run your system under any volume of requests, the trick is to deploy required number of computing nodes in the cluster. If we are talking about cluster of 2-4 nodes your administrator (or as they call it today "devops engineer") will install anything manually. Probably he will easily handle 5 nodes configuration in the cluster.