Brainstorming the project we would build to showcase in the current female health themed InterSystems FHIR Contest, our girl band decided that we need to do something practical for the ordinary user and to solve some burning issues of the modern life. This discussion led to the idea of creating a project that will help women not to forget their health in daily grind - FemTech Reminder.

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:

IRIS BI

We offer you to embed business intelligence into your applications in order to give your users an opportunity to ask and answer sophisticated questions about their data. Typically, your application will include customizable dashboards that can provide insight into data from Business Intelligence models known as cubes.

In contrast with traditional BI systems that use static data warehouses, Business Intelligence keeps being constantly synchronized with the live transactional data.

If you're running IRIS in a mirrored configuration for HA in AWS, the question of providing a Mirror VIP (Virtual IP) becomes relevant. Virtual IP offers a way for downstream systems to interact with IRIS using one IP address. Even when a failover event happens, downstream systems can reconnect to the same IP address and continue working.

The main issue, when deploying to AWS, is that an IRIS VIP has a requirement of both mirror members being in the same subnet, from the docs:

To use a mirror VIP, both failover members must be configured in the same subnet, and the VIP must belong to the same subnet as the network interface that is selected on each system

However, to get HA, IRIS mirror members must be deployed to different availability zones, which means different subnets (as subnets can be in only one az). One of the solutions might be load balancers, but they (A) cost money, and (B) if you need to route non-HTTP traffic (think TCP for HL7), you'll have to use Network Load Balancers which have a limit of 50 ports total.

In this article, I would like to provide a way to configure a Mirror VIP without the use of Network Load Balancing suggested in most other AWS reference architectures. In production, we have found limitations that impeded solutions with cost, 50 listener limits, DNS dependencies, and the dynamic nature of the two IP addresses AWS provides across the availability zones.

VR ICU®

In this article, we will discuss about Orphaned Messages.

Overview

Predictable storage IO performance with low latency is vital to provide scalability and reliability for your applications. This set of benchmarks is to inform users of IRIS considering deploying applications in AWS about EBS gp3 volume performance.

Summary

• An LVM stripe can increase IOPS and throughput beyond single EBS volume performance limits.
• An LVM stripe lowers read latency.

REST API for Security Package

Hi community,

In this article, we will learn how to set up a REST API for the IRIS Security Package. We will be able to create users, roles, add applications, etc... by simple HTTP requests as well as generate a client application in ObjectScript.

Requirements

We need :

Recently there was an internal email thread on which SMTP server to use in demos. I thought I'd share the comments from that thread:

• Person 1: I tried gmail (smtp.gmail.com, port 465) this morning, it works fine.
  To use gmail, you must enable 2-step verification for your google account and generate App password. https://support.google.com/mail/answer/185833?hl=en

• Person 2: I use https://www.hmailserver.com

** Revised Feb-12, 2018

While this article is about InterSystems IRIS, it also applies to Caché, Ensemble, and HealthShare distributions.

Introduction

Memory is managed in pages. The default page size is 4KB on Linux systems. Red Hat Enterprise Linux 6, SUSE Linux Enterprise Server 11, and Oracle Linux 6 introduced a method to provide an increased page size in 2MB or 1GB sizes depending on system configuration know as HugePages.

At first HugePages required to be assigned at boot time, and if not managed or calculated appropriately could result in wasted resources. As a result various Linux distributions introduced Transparent HugePages with the 2.6.38 kernel as enabled by default. This was meant as a means to automate creating, managing, and using HugePages. Prior kernel versions may have this feature as well however may not be marked as [always] and potentially set to [madvise].

Transparent Huge Pages (THP) is a Linux memory management system that reduces the overhead of Translation Lookaside Buffer (TLB) lookups on machines with large amounts of memory by using larger memory pages. However in current Linux releases THP can only map individual process heap and stack space.

Today we will talk about Adaptive Analytics. This is a system that allows you to receive data from various sources with a relativistic data structure and create OLAP cubes based on this data. This system also provides the ability to filter and aggregate data and has mechanisms to speed up the work of analytical queries.

With IRIS 2021.1, we released a significant revision our SQL utilities API at %SYSTEM.SQL. Yes, that's a while ago now, but last week a customer asked a few questions about this and then @Tom Woodfin applied gentle mental pressure ;-) to make me describe the rationale of these changes in a little more detail on the Developer Community. So here we go!

In the vast and varied SQL database market, InterSystems IRIS stands out as a platform that goes way beyond just SQL, offering a seamless multimodel experience and supporting a rich set of development paradigms. Especially the advanced Object-Relational engine has helped organizations use the best-fit development approach for each facet of their data-intensive workloads, for example ingesting data through Objects and simultaneously querying it through SQL. Persistent Classes correspond to SQL tables, their properties to table columns and business logic is easily accessed using User-Defined Functions or Stored Procedures. In this article, we'll zoom in on a little bit of the magic just below the surface, and discuss how it may affect your development and deployment practices. This is an area of the product where we have plans to evolve and improve, so please don't hesitate to share your views and experiences using the comments section below.

1. iris-dollar-list

Interpretor of $list for python named DollarList.

This interpretor was made because :

• I wanted to use $list in python.
• Embedded Python do not support $list.
• The native API version do not support embedded $list in $list.

This is a work in progress. For now, it only support embedded $list in $list, int and string.

WIP float,decimal,double

This module is available on Pypi :

pip3 install iris-dollar-list

It is compatible with embedded python and native api.