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#API

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Application Programming Interface (API) is a set of subroutine definitions, protocols, and tools for building application software. In general terms, it is a set of clearly defined methods of communication between various software components.

Learn more.

The following steps show you how to display a sample list of metrics available from the /api/monitor service.

In the last post, I gave an overview of the service that exposes IRIS metrics in Prometheus format. The post shows how to set up and run IRIS preview release 2019.4 in a container and then list the metrics.

This post assumes you have Docker installed. If not, go and do that now for your platform :)

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This formation, accessible on my GitHub, will cover, in half a hour, how to read and write in csv and txt files, insert and get inside the IRIS database and a distant database using Postgres or how to use a FLASK API, all of that using the Interoperability framework using ONLY Python following the PEP8 convention.

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Released with no formal announcement in IRIS preview release 2019.4 is the /api/monitor service exposing IRIS metrics in Prometheus format. Big news for anyone wanting to use IRIS metrics as part of their monitoring and alerting solution. The API is a component of the new IRIS System Alerting and Monitoring (SAM) solution that will be released in an upcoming version of IRIS.

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ObjectScript Kernel Logo
Jupyter Notebook is an interactive environment consisting of cells that allow executing code in a great number of different markup and programming languages.

To do this Jupyter has to connect to an appropriate kernel. There was no ObjectScript Kernel, that is why I decided to create one.

You can try it out here.

Here's a sneak peek of the results:

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Article
· Sep 14, 2020 3m read
IRIS Native API for ObjectScript

It seems to me that for some reason this didn't make its way to the official documentation
and seems to be rather unknown though implemented already in IRIS 2020.1

Thanks to @Dan Pasco I got a hint on the classes involved.
I used the recommended sequence of how to use it.
it is all directly taken from Class Reference and I just collected it to create a first overview.

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Article
· Feb 15, 2021 17m read
Four Database APIs

A concurrent session in IRIS:
SQL, Objects, REST, and GraphQL

Kazimir Malevich, "Athletes" (1932)

"But of course you don't understand! How can a person who has always traveled in a horse-drawn carriage understand the feelings and impressions of the express traveler or the pilot in the air?"

Kazimir Malevich (1916)

Introduction

We’ve already addressed the topic of why object/type representation is superior to SQL for implementing subject area models. And those conclusions and facts are as true now as they have ever been. So why should we take a step back and discuss technologies that drag abstractions back to the global level, where they had been in the pre-object and pre-type era? Why should we encourage the use of spaghetti code, which results in bugs that are hard to track down, and which relies only on virtuoso developer skills?

There are several arguments in favor of transmitting data via SQL/REST/GraphQL-based APIs as opposed to representing them as types/objects:

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InterSystems API Management (IAM) - a new feature of the InterSystems IRIS Data Platform, enables you to monitor, control and govern traffic to and from web-based APIs within your IT infrastructure. In case you missed it, here is the link to the announcement. And here's an article explaining how to start working with IAM.

In this article, we would use InterSystems API Management to Load Balance an API.

In our case, we have 2 InterSystems IRIS instances with /api/atelier REST API that we want to publish for our clients.

There are many different reasons why we might want to do that, such as:

  • Load balancing to spread the workload across servers
  • Blue-green deployment: we have two servers, one "prod", other "dev" and we might want to switch between them
  • Canary deployment: we might publish the new version only on one server and move 1% of clients there
  • High availability configuration
  • etc.
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I already talked about GraphQL and the ways of using it in this article. Now I am going to tell you about the tasks I was facing and the results that I managed to achieve in the process of implementing GraphQL for InterSystems platforms.

What this article is about

  • Generation of an AST for a GraphQL request and its validation
  • Generation of documentation
  • Generation of a response in the JSON format
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Introduction

We are in the age of the multiplatform economy and APIs are the "glue" in this digital scenario. Since they are so important, they are seen by developers as a service or product to be consumed. Therefore, usage experience is a crucial factor for its success.

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Article
· Mar 14, 2018 10m read
REST Design and Development

Intro

For many in today's interoperability landscape, REST reigns supreme. With the overabundance of tools and approaches to REST API development, what tools do you choose and what do you need to plan for before writing any code?
This article focuses on design patterns and considerations that allow you to build highly robust, adaptive, and consistent REST APIs. Viable approaches to challenges of CORS support and authentication management will be discussed, along with various tips and tricks and best tools for all stages of REST API development. Learn about the open-source REST APIs available for InterSystems IRIS Data Platform and how they tackle the challenge of ever-increasing API complexity.
The article is a write-up for a recent webinar on the same topic.

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Article
· Jul 27, 2018 4m read
Load a ML model into InterSystems IRIS

Hi all. Today we are going to upload a ML model into IRIS Manager and test it.

Note: I have done the following on Ubuntu 18.04, Apache Zeppelin 0.8.0, Python 3.6.5.

Introduction

These days many available different tools for Data Mining enable you to develop predictive models and analyze the data you have with unprecedented ease. InterSystems IRIS Data Platform provide a stable foundation for your big data and fast data applications, providing interoperability with modern DataMining tools.

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On this GitHub you can find all the information on how to use a HuggingFace machine learning / AI model on the IRIS Framework using python.

1. iris-huggingface

Usage of Machine Learning models in IRIS using Python; For text-to-text, text-to-image or image-to-image models.

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Introduction

Nowadays, there is a lot of applications that are using Open Authorization framework (OAuth) to access resources from all kinds of services in a secure, reliable and efficient manner. InterSystems IRIS is already compatible with OAuth 2.0 framework, in fact, there is a great article in the community regarding OAuth 2.0 and InterSystems IRIS in the following link here.

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In this 3-part series of articles, is shown how you can use IAM to simply add security, according to OAuth 2.0 standards, to a previously unauthenticated service deployed in IRIS.

In the first part, was provided some OAuth 2.0 background together with some IRIS and IAM initial definitions and configurations in order to facilitate the understanding of the whole process of securing your services.

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Hi Community!

You're very welcome to watch a new video on InterSystems Developers YouTube, recorded by @Stefan Wittmann, InterSystems Product Manager:

InterSystems API Manager Introduction

https://www.youtube.com/embed/vO6kz1G4eVg
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Hi Developers,

Please welcome the new video on InterSystems Developers YouTube:

⏯ Building REST API with InterSystems IRIS Docker Container in 5 Minutes

https://www.youtube.com/embed/VVpIE1jfi1M
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