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#Best Practices

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Best Practices recommendations on how to develop, test, deploy and manage solutions on InterSystems Data Platforms better. 

Hi, this post was initially written for Caché. In June 2023, I finally updated it for IRIS. If you are revisiting the post since then, the only real change is substituting Caché for IRIS! I also updated the links for IRIS documentation and fixed a few typos and grammatical errors. Enjoy :)

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Here you'll find a simple program that uses Python in an IRIS environment and another simple program that uses ObjectScript in a Python environment. Also, I'd like to share a few of the troubles I went trough while learning to implement this.

Python in IRIS environment

Let's say, for example, you're in an IRIS environment and you want to solve a problem that you find easy, or more efficient with Python.

You can simply change the environment: create your method as any other, and in the end of it's name and specifications, you add [ Language = python ]:

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image

This article will cover turning over control of provisioning the InterSystems Kubernetes Operator, and starting your journey managing your own "Cloud" of InterSystems Solutions through Git Ops practices. This deployment pattern is also the fulfillment path for the PID^TOO||| FHIR Breathing Identity Resolution Engine.

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Article
· Aug 16, 2023 11m read
Http request response time monitoring

Hi developers!

Today I would like to address a subject that has given me a hard time. I am sure this must have been the case for quite a number of you already (so-called “the bottleneck”). Since this is a broad topic, this article will only focus on identifying incoming HTTP requests that could be causing slowness issues. I will also provide you with a small tool I have developed to help identify them.

Our software is becoming more and more complex, processing a large number of requests from different sources, be it front-end or third-party back-end applications. To ensure optimal performance, it is essential to have a logging system capable of taking a few key measurements, such as the response time, the number of global references and the number of lines of code executed for each HTTP response. As part of my work, I get involved in the development of EMR software as well as incident analysis. Since user load comes mostly from HTTP requests (REST API or CSP application), the need to have this type of measurement when generalized slowness issues occur has become obvious.

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I am often asked by customers, vendors or internal teams to explain CPU capacity planning for large production databases running on VMware vSphere.

In summary there are a few simple best practices to follow for sizing CPU for large production databases:

  • Plan for one vCPU per physical CPU core.
  • Consider NUMA and ideally size VMs to keep CPU and memory local to a NUMA node.
  • Right-size virtual machines. Add vCPUs only when needed.

Generally this leads to a couple of common questions:

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Case description

Let’s imagine that you are a Python developer or have a well-trained team specialized in Python, but the deadline you got to analyze some data in IRIS is tight. Of course, InterSystems offers many tools for all kinds of analyses and treatments. However, in the given scenario, it is better to get the job done using the good old Pandas and leave the IRIS for another time.

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While starting the development with IRIS we have a distribution kit or in case of Docker we are pulling the docker image and then often we need to initialize it and setup the development environment. We might need to create databases, namespaces, turn on/off some services, create resources. We often need to import code and data into IRIS instance and run some custom code to init the solution.

And there plenty of templates on Open Exchange where we suggest how to init REST, Interoperability, Analytics, Fullstack and many other templates with ObjectScript. What if we want to use only Python to setup the development environment for Embedded Python project with IRIS?

So, the recent release of Embedded Python template is the pure python boilerplate that could be a starting point for developers that build python projects with no need to use and learn ObjectScript. This article expresses how this template could be used to initialize IRIS. Here we go!

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Article
· Jun 1, 2023 1m read
How to shrink the IRISTemp database

InterSystems FAQ rubric

You can set the maximum size of the IRISTemp database at IRIS startup by setting a configuration parameter called MaxIRISTempSizeAtStart.

After setting, the system will truncate IRISTemp to the set value (MB) at the next IRIS startup. If the current size is less than the specified MaxIRISTempSizeAtStart, no truncation will occur. Also, if 0 is specified, truncation will not be performed, so the size will start without changing. (Default) Settings are made from the menu below.

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Article
· Jun 12, 2023 3m read
LangChain fixed the SQL for me

This article is a simple quick starter (what I did was) with SqlDatabaseChain.

Hope this ignites some interest.

Many thanks to:

sqlalchemy-iris author @Dmitry Maslennikov

Your project made this possible today.

The article script uses openai API so caution not to share table information and records externally, that you didn't intend to.

A local model could be plugged in , instead if needed.

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Article
· Mar 31, 2023 3m read
Using JSON in IRIS

Saw the other day an article with the usage of the %ZEN package when working with JSON and decided to write an article describing a more modern approach. At some recent point, there was a big switch from using %ZEN.Auxiliary.* to dedicated JSON classes. This allowed to work with JSONs more organically.

Thus, at this point there are basically 3 main classes to work with JSON:

  • %Library.DynamicObject - provides a simple and efficient way to encapsulate and work with standard JSON documents. Also, there is a possibility instead of writing the usual code for creating an instance of a class like
set obj = ##class(%Library.DynamicObject).%New()

it is possible to use the following syntax

set obj = {}
  • %Library.DynamicArray - provides a simple yet efficient way to encapsulate and work with standard JSON arrays. With arrays you can use the same approach as with objects, meaning that yu can either create an instance of the class
set array = ##class(%DynamicArray).%New()

or you can do it by using brackets []

set array = []
  • %JSON.Adaptor is a means for mapping ObjectScript objects (registered, serial or persistent) to JSON text or dynamic entities.
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Introduction

Data analytics is a crucial aspect of business decision-making in today's fast-paced world. Organizations rely heavily on data analysis to make informed decisions and stay ahead of the competition. In this article, we will explore how data analytics can be performed using Pandas and Intersystems Embedded Python. We will discuss the basics of Pandas, the benefits of using Intersystems Embedded Python, and how they can be used together to perform efficient data analytics.

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In this article I will explain how to Authenticate, Authorize and Audit by code by using CSP Web Application along with Enabling /Disabling and Authenticate/Unauthenticate any Web Application.

Application Layout

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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab Workflow
  • Continuous Delivery
  • GitLab installation and configuration
  • GitLab CI/CD
  • Why containers?
  • Containers infrastructure
  • CD using containers

In the first article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software.

In the second article, we covered GitLab Workflow - a complete software life cycle process and Continuous Delivery.

In the third article, we covered GitLab installation and configuration and connecting your environments to GitLab

In the fourth article, we wrote a CD configuration.

In the fifth article, we talked about containers and how (and why) they can be used.

In the sixth article let's discuss main components you'll need to run a continuous delivery pipeline with containers and how they all work together.

In this article, we'll build Continuous Delivery configuration discussed in the previous articles.

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Article
· Aug 2, 2022 8m read
Data models in InterSystems IRIS

Before we start talking about databases and different data models that exist, first we'd better talk about what a database is and how to use it.

A database is an organized collection of data stored and accessed electronically. It is used to store and retrieve structured, semi-structured, or raw data which is often related to a theme or activity.

At the heart of every database lies at least one model used to describe its data. And depending on the model it is based on, a database may have slightly different characteristics and store different types of data.

To write, retrieve, modify, sort, transform or print the information from the database, a software called Database Management System (DBMS) is used.

The size, capacity, and performance of databases and their respective DBMS have increased by several orders of magnitude. It has been made possible by technological advances in various areas, such as processors, computer memory, computer storage, and computer networks. In general, the development of database technology can be divided into four generations based on the data models or structure: navigational, relational, object and post-relational.

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Overview

We often run into connectivity problems with HealthShare (HS) deployments in Microsoft Azure that have multiple HealthShare components (instances or namespaces) installed on the same VM, especially when needing to communicate to other HS components while using the Azure Load Balancer (ILB) to provide mirror VIP functionality. Details on how and why a load balancer is used with database mirroring can be found this community article.

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   _________ ___ ____  
  |__  /  _ \_ _|  _ \ 
    / /| |_) | || |_) |
   / /_|  __/| ||  __/ 
  /____|_|  |___|_|

Starting in version 2021.1, InterSystems IRIS began shipping with a python runtime in the engine's kernel. However, there was no way to install packages from within the instance. The main draw of python is its enormous package ecosystem. With that in mind, I introduce my side project zpip, a pip wrapper that is callable from the iris terminal.

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csp-log-tutorial

Prerequisites

Make sure you have git installed.

I created a git folder inside the IRIS mgr directory. I right clicked the git folder and chose Git Bash Here from the context menu.

git clone https://github.com/oliverwilms/csp-log-tutorial.git

Clone my csp-log-tutorial GitHub repo if you like to try it out for yourself.

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Article
· Oct 11, 2022 2m read
ZPM Simple Implementation Cookbook

ZPM is designed to work with applications and modules for InterSystems IRIS Data Platform. It consists of two components, the ZPN Client which is a CLI to manage modules, and The Registry which is a database of modules and meta-information. We can use ZPM to search, install, upgrade, remove and publish modules. With ZPM you can install ObjectScript classes, Frontend applications, Interoperability productions, IRIS BI solutions, IRIS Datasets or any files such as Embedded Python wheels.

Today this cookbook will go through 3 sections:

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