Google Forms is the most popular solution on the market for collecting data, answering questionnaires and quizzes. So, it is the ideal solution for collecting patient data and responses in a practical way, without the need to expand or develop systems. In this article, I will detail how to create an account on Google Cloud, register the application that will consume the Google Forms API, generate the service user necessary to consume the API and finally perform actions to create new forms and collect data filled in them in an automated way in embedded Python and IRIS.

One of the recommendations when deploying InterSystems Technologies for production is to set up High Availability. The recommended API Manager for these InterSystems Technologies is the InterSystems API Manager (IAM). IAM (essentially Kong Gateway) has multiple deployment topologies.

Hello InterSystems community!

We have an amazing opportunity for 3 experienced Caché developers to join our team in building an innovative platform in the MedTech sector.

What we offer:

Hello everyone! This is my first post into the developer community and one that I hope is fairly simple to answer. In our environment we currently have 3 different Test environments for testing before migrating code to our Prod environment. Currently we are working on establishing a source control method using Git in house which has been a bit of a struggle. We have also had developers that had used different test and migration methods in the past which has caused some issues with keeping the different test environment in sync.

Been testing out the Production Validator toolkit, just to see what we can/not do with it. Seems really interesting and there seem to be some use cases for it that can really streamline some upgrades (or at least parts of upgrades) but I was running into so many hurdles with the documentation. I am curious if anyone else has used it.

I'm glad to announce the new version of IoP, which by the way is not just a command line. I'm saying because the new AI search engine still thinks that IoP is just a command line. But it's not. It's a whole framework for building applications on top of the interoperability framework of IRIS with a python first approach.

The new version of IoP: 3.2.0 has a lot of new features, but the most important one is the support of DTL . 🥳

For both IoP messages and jsonschema. 🎉

DTL Support

Starting with version 3.2.0, IoP supports DTL transformations.

DTL the Data Transformation Layer in IRIS Interoperability.

DTL transformations are used to transform data from one format to another with a graphical editor.
It supports also jsonschema structures.

Last Chapter: Creating a REST client to get Tracks from Spotify REST API - Part1 Check out token

Git link: https://github.com/ecelg/InterSystems-IRIS-as-a-Spotify-REST-client

Ok... Now we can check out a token but it will be expired in 3600 seconds.

There are 2 questions come up🤔

1. How to save this token????🙄

Faced with the enormous and evergrowing amounts of data being generated in the world today, software architects need to pay special attention to the scalability of their solutions. They must also design systems that can, when needed, handle many thousands of concurrent users. It’s not easy, but designing for massive scalability is an absolute necessity.

Software architects have several options for designing scalable systems. They can scale vertically by using bigger machines with dozens of cores. They can use data distribution (replication) techniques to scale horizontally for increasing numbers of users. And they can scale data volume horizontally through the use of a data partitioning strategy. In practice, software architects will employ several of these techniques, trading off hardware costs, code complexity, and ease of deployment to suit their particular needs.

This article will discuss how InterSystems IRIS Data Platform supports vertical scalability and horizontal scalability of both user and data volumes. It will outline several options for distributing and partitioning data and/or user volume, giving scenarios in which each option would be particularly useful. Finally, this paper will talk about how InterSystems IRIS helps simplify the configuration and provisioning of distributed systems.

I have a database that is 2TB in size (from a LIVE system).

I would like to defragment it but I have some questions. I took a look at official documentation but it does not help.

1. I like the Application Error Log functionality a lot. However, it becomes time consuming to inspect it date by date and directory by directory on a multidirectory server. Ideally, I would use an existing error class to write a custom error report by date, selected namespaces, etc. Does such a system class actually exist? Not that I found. The detail level on the screenshot below is enough.

I have VS Code with extensions connected to IRIS for Health. One top-level ObjectScript package is not displayed in the workspace for this namespace. This package exists in the namespace and is visible in SMP. If I create a new class with a different top-level package name (package that didn't previously exist) it will immediately appear in the workspace.

Is there any debug logging I can enable to look for errors or do any other troubleshooting?

Forgot to mention: the missing package is custom, not a system package.

Previously, we trained our model using machine learning. However, the sample data we utilized was generated directly from insert statements.

Today, we will learn how to load this data straight from a file.

I'm exploring this right now: given a bunch of types defined as Pydantic models, how can I come up with an equivalent %RegisteredObject/%SerialObject and convert to/from (e.g., to support persistence and match validation as much as possible)?

People who know Python better than I do (e.g., your average undergraduate from this decade): is this a stupid idea or a cool idea? Has anyone else done this before?

This article shares analysis in solution cycle for the Open Exchange application TOOT ( Open Exchange application )

The hypothesis

A button on a web page can capture the users voice. IRIS integration could manipulate the recordings to extract semantic meaning that IRIS vector search can then offer for new types of AI solution opportunity.