Best Practices recommendations on how to develop, test, deploy and manage solutions on InterSystems Data Platforms better.
Hi Community!
We are introducing a new feature on DC site - Best Practices of InterSystems Data Platforms.
It is the tag, which highlights articles on DC considered as Best Practices on how to develop, test, deploy and manage solutions on InterSystems Data Platforms.
Following 2 local Webinars we had focused on VS Code ["Intro" and "Beyond Basics"; in Hebrew], I prepared for the participants some related links of relevant resources which we sent as a follow-up. Sharing them here as well for the benefit of the Community.
You are all of course welcome to add more useful resources.
In InterSystems IRIS 2024.3 and subsequent IRIS versions, the AutoML component is now delivered as a separate Python package that is installed after installation. Unfortunately, some recent versions of Python packages that AutoML relies on have introduced incompatibilities, and can cause failures when training models (TRAIN MODEL statement). If you see an error mentioning "TypeError" and the keyword argument "fit_params" or "sklearn_tags", read on for a quick fix.
This part of the OMOP Journey, we reflect before attempting to challenge Scylla on how fortunate we are that InterSystems OMOP transform is built on the Bulk FHIR Export as the source payload. This opens up hands off interoperability with the InterSystems OMOP transform across several FHIR® vendors, this time with the Google Cloud Healthcare API.
This part of the OMOP Journey, we reflect before attempting to challenge Scylla on how fortunate we are that InterSystems OMOP transform is built on the Bulk FHIR Export as the source payload. This opens up hands off interoperability with the InterSystems OMOP transform across several FHIR® vendors, including Amazon Web Services HealthLake.
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In recent versions of IRIS, a powerful new data loading command has been introduced to SQL: LOAD DATA. This feature has been highly optimized to import data into IRIS extremely fast, allowing hundreds of gigabytes of data to be inserted in seconds instead of hours or days.
This is a very exciting improvement. However, a big problem in the data loading experience still exists. Namely, the time and hassle it takes to:
If you want to find out what exact version your Docker image is (and since the latest image tagging scheme you cannot just rely on the image tag; and assuming you don't want to actually run it just in order to find out) you can run this docker command:
Thirteen years ago, I attained dual undergraduate degrees in electrical engineering and math, then promptly started full-time at InterSystems using neither. One of my most memorable and stomach-churning academic experiences was in Stats II. On an exam, I was solving a moderately difficult confidence interval problem. I was running out of time, so (being an engineer) I wrote out the definite integral on the exam paper, punched it into my graphing calculator, wrote an arrow with “calculator” over it, then wrote the result. My professor, affectionately known as “Dean, Dean, the Failing Machine,”
InterSystems IRIS has quite a few different kinds properties. Let’s put them in order so that they make better sense.
First of all, I would divide them into categories:
Some of these kinds of properties are quite straightforward. For example, atomic properties:
Here's a sample code to display JSON or dynamic object.
It shows how to iterate over object, get property values and their paths.
With the release of InterSystems IRIS Cloud SQL, we're getting more frequent questions about how to establish secure connections over JDBC and other driver technologies. While we have nice summary and detailed documentation on the driver technologies themselves, our documentation does not go as far to describe individual client tools, such as our personal favourite DBeaver. In this article, we'll describe the steps to create a secure connection from DBeaver to your Cloud SQL deployment.
Hi community,
The aim of this article is to explain how to create messaging between IRIS and Microsoft Teams.
In my company, we wanted to monitor error messages, and we used the Ens.Alert class to redirect those error messages through a Business Operation that sent an email.
The problem was that we sent those error messages to a support account where there were many emails. We wanted something specific for a specific team.
If you are a customer of the new InterSystems IRIS® Cloud SQL and InterSystems IRIS® Cloud IntegratedML® cloud offerings and want access to the metrics of your deployments and send them to your own Observability platform, here is a quick and dirty way to get it done by sending the metrics to Google Cloud Platform Monitoring (formerly StackDriver).
Artificial Intelligence (AI) is getting a lot of attention lately because it can change many areas of our lives. Better computer power and more data have helped AI do amazing things, like improving medical tests and making self-driving cars. AI can also help businesses make better decisions and work more efficiently, which is why it's becoming more popular and widely used. How can one integrate the OpenAI API calls into an existing IRIS Interoperability application?
The InterSystems IRIS is a great data platform and it is met the current features required by the market. In this article, you see the top 10:
Note: this list was updated because many features are added to IRIS in last 3 years (thanks @Kristina Lauer)
An experiment on how to use the LangChain framework, IRIS Vector Search, and LLMs to generate IRIS-compatible SQL from user prompts.
This article was based in this notebook. You can run it with a ready to use environment with this application in OpenExchange.
First, we need to install the necessary libraries:
!pip install --upgrade --quiet langchain langchain-openai langchain-iris pandas
Next, we import the required modules and set up the environment:
One of the pain points for maintaining HL7 interfaces is the need to run a reliable regression test upon deployment to new environments and after upgrades. The %UnitTest class allows unit tests to be created and packaged alongside interface code. Test data can also be maintained within the unit test class, allowing for quick and easily repeatable smoke-testing and regression testing.
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What I find really useful about IRIS when teaching my subject of Postrelational databases is the fact that it is a multi model database. Which means that I can actually go into architecture and structure and all that only once but then show the usage of different models (like object, document, hierarchy) using the same language and approach. And it is not a huge leap to go from an object oriented programming language (like C#, Java etc) to an object oriented database.
As an IT and cloud team manager with 18 years of experience with InterSystems technologies, I recently led our team in the transformation of our traditional on-premises ERP system to a cloud-based solution. We embarked on deploying InterSystems IRIS within a Kubernetes environment on AWS EKS, aiming to achieve a scalable, performant, and secure system. Central to this endeavor was the utilization of the AWS Application Load Balancer (ALB) as our ingress controller.
Introduction
This is a quickstart guide to IRIS for Linux systems administrators who need to be able to support the IRIS DB as well as other normal infrastructure tasks.
IRIS is a DB system from Intersystems. An IRIS DB can hold code (in the form of a Class) or data (in the form of Globals). IRIS DB are Linux files called IRIS.DAT.
Have you ever been editing files in VS Code, but needed to check a global value or run a few ObjectScript commands? Now you can, with no setup required! If you have vscode-objectscript extension version 2.10.0 or later and are connected to InterSystems IRIS 2023.2 or later, you can now open a terminal connection to your server, regardless of where it's located.
There are three ways to open this new terminal:
Recently, the question came up while discussing the access to the data stored in IRIS from different languages with my students if it was possible to initiate the connection and get data from Cloud solution (InterSystems IRIS CloudSQL) from Microsoft Excel, not the other way around. Considering the many varied ways one can get data in Excel (import data from external sources, connecting to databases using ODBC drivers, using power queries and web queries etc.) the obvious choice was to try ODBC driver. The only task left was to try to connect to the database in the cloud using the ODBC driver.
As the health interoperability landscape expands to include data exchange across on-premise as well as hosted solutions, we are seeing an increased need to integrate with services such as cloud storage. One of the most prolifically used and well supported tools is the NoSQL database DynamoDB (Dynamo), provided by Amazon Web Services (AWS).