This post will show you an approach to size shared memory requirements for database applications running on InterSystems data platforms including global and routine buffers, gmheap, and locksize as well as some performance tips you should consider when configuring servers and when virtualizing Caché applications. As ever when I talk about Caché I mean all the data platform (Ensemble, HealthShare, iKnow and Caché).


A list of other posts in this series is here

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Your application is deployed and everything is running fine. Great, hi-five! Then out of the blue the phone starts to ring off the hook – it’s users complaining that the application is sometimes ‘slow’. But what does that mean? Sometimes? What tools do you have and what statistics should you be looking at to find and resolve this slowness? Is your system infrastructure up to the task of the user load? What infrastructure design questions should you have asked before you went into production? How can you capacity plan for new hardware with confidence and without over-spec'ing? How can you stop the phone ringing? How could you have stopped it ringing in the first place?

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In the last post we scheduled 24-hour collections of performance metrics using pButtons. In this post we are going to be looking at a few of the key metrics that are being collected and how they relate to the underlying system hardware. We will also start to explore the relationship between Caché (or any of the InterSystems Data Platforms) metrics and system metrics. And how you can use these metrics to understand the daily beat rate of your systems and diagnose performance problems.

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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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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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Article
· Jan 22 2m read
Getting JSON from SQL

Did you know that you can get JSON data directly from your SQL tables?

Let me introduce you to 2 useful SQL functions that are used to retrieve JSON data from SQL queries - JSON_ARRAY and JSON_OBJECT.
You can use those functions in the SELECT statement with other types of select items, and they can be specified in other locations where an SQL function can be used, such as in a WHERE clause

The JSON_ARRAY function takes a comma-separated list of expressions and returns a JSON array containing those values.

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The Amazon Web Services (AWS) Cloud provides a broad set of infrastructure services, such as compute resources, storage options, and networking that are delivered as a utility: on-demand, available in seconds, with pay-as-you-go pricing. New services can be provisioned quickly, without upfront capital expense. This allows enterprises, start-ups, small and medium-sized businesses, and customers in the public sector to access the building blocks they need to respond quickly to changing business requirements.

Updated: 10-Jan, 2023

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I have attached a document that describes the product I have developed called NiPaRobotica Pharmacy. This is an interface I developed that accepts Pharmacy Dispense Requests and converts the line items on the order into dispense dialogues which it sends to pharmacy robots. I deployed the interface into 3 Hospital pharmacies two of which had 6 robots that were arranged in such a way that the dispense chutes channelled medications to desks by the pharmacists sitting in windows serving 1200 patients a day. The robots cut the average waiting time from 2 hours down to one hour.

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Python has become the most used programming language in the world (source: https://www.tiobe.com/tiobe-index/) and SQL continues to lead the way as a database language. Wouldn't it be great for Python and SQL to work together to deliver new functionality that SQL alone cannot? After all, Python has more than 380,000 published libraries (source: https://pypi.org/) with very interesting capabilities to extend your SQL queries within Python.

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What is Web Scraping:

In simple terms, Web scraping, web harvesting, or web data extraction is an automated process of collecting large data(unstructured) from websites. The user can extract all the data on particular sites or the specific data as per the requirement. The data collected can be stored in a structured format for further analysis.

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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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Article
· Jul 8, 2020 7m read
Tips for debugging with %Status

Introduction

If you're solving complex problems in ObjectScript, you probably have a lot of code that works with %Status values. If you have interacted with persistent classes from an object perspective (%Save, %OpenId, etc.), you have almost certainly seen them. A %Status provides a wrapper around a localizable error message in InterSystems' platforms. An OK status ($$$OK) is just equal to 1, whereas a bad status ($$$ERROR(errorcode,arguments...)) is represented as a 0 followed by a space followed by a $ListBuild list with structured information about the error. $System.Status (see class reference) provides several handy APIs for working with %Status values; the class reference is helpful and I won't bother duplicating it here. There have been a few other useful articles/questions on the topic as well (see links at the end). My focus in this article will be on a few debugging tricks techniques rather than coding best practices (again, if you're looking for those, see links at the end).

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There are many ways to generate excel files using Intersystems, some of them are ZEN reports, IRIS reports ( Logi reports or formally known as JReports), or we can use third party Java libraries, the possibilities are almost endless.

But, what if you want to create a simple spreadsheet with only Caché ObjectScript? (no third party applications)

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This week I am going to look at CPU, one of the primary hardware food groups :) A customer asked me to advise on the following scenario; Their production servers are approaching end of life and its time for a hardware refresh. They are also thinking of consolidating servers by virtualising and want to right-size capacity either bare-metal or virtualized. Today we will look at CPU, in later posts I will explain the approach for right-sizing other key food groups - memory and IO.

So the questions are:

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In this article we are going to see how we can use the WhatsApp instant messaging service from InterSystems IRIS to send messages to different recipients. To do this we must create and configure an account in Meta and configure a Business Operation to send the messages we want.

Let's look at each of these steps in more detail.

Setting up an account on Meta

This is possibly the most complicated point of the entire configuration, since we will have to configure a series of accounts until we can have the messaging functionality.

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Index

This is a list of all the posts in the Data Platforms’ capacity planning and performance series in order. Also a general list of my other posts. I will update as new posts in the series are added.


You will notice that I wrote some posts before IRIS was released and refer to Caché. I will revisit the posts over time, but in the meantime, Generally, the advice for configuration is the same for Caché and IRIS. Some command names may have changed; the most obvious example is that anywhere you see the ^pButtons command, you can replace it with ^SystemPerformance.


While some posts are updated to preserve links, others will be marked as strikethrough to indicate that the post is legacy. Generally, I will say, "See: some other post" if it is appropriate.


Capacity Planning and Performance Series

Generally, posts build on previous ones, but you can also just dive into subjects that look interesting.


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Over the past year or so, my team (Application Services at InterSystems - tasked with building and maintaining many of our internal applications, and providing tools and best practices for other departmental applications) has embarked on a journey toward building Angular/REST-based user interfaces to existing applications originally built using CSP and/or Zen. This has presented an interesting challenge that may be familiar to many of you - building out new REST APIs to existing data models and business logic.

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Healthcare interoperability is instrumental in improving patient care, decreasing healthcare provider costs, and providing a more accurate picture to providers. However, with so many different systems, data is formatted in many different ways. There are many standards that have been created to try to solve this problem, including HL7v2, HL7v3, and CDA but each one has its drawbacks.

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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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Article
· Nov 29, 2022 6m read
What's HL7v2?!

HL7 (Health Level 7) is a set of technical specifications for computerized exchanges of clinical, financial and administrative data between hospital information systems (HIS). These specifications are variously integrated into the corpus of formal American (ANSI) and international (ISO) standards.

The L7 of HL7 indicates that it is a standard that operates at layer 7, in other words at the application layer, of the OSI model. This means that HL7 does not have to take into account exchange security considerations, or those of message transport (this being ensured by lower-level layers such as SSL/TLS for security or TCP for the transport of data for example). To be more precise, layer 7 supports communications for end-user processes and applications and the presentation of data for user-facing software applications. As the highest layer of the OSI model, and the closest to the end user, layer 7 provides application-specific functions such as identifying communication partners and the quality of service between them, determining resource availability, considering privacy and user authentication, and synchronizing communication, as well as connecting the application to the lower levels of the OSI model.

Returning to the HL7 standard, the HL7 version 2 standard (also known as Pipehat) was originally created in 1989 but is still being used and updated regularly, resulting in versions 2.1, 2.2, 2.3, 2.3.1, 2.4, 2.5, 2.5.1, 2.6, 2.7, 2.7.1, 2.8, 2.8.1, 2.8.2 and 2.9. The v2.x standards are backward compatible (e.g., a message based on version 2.3 will be understood by an application that supports version 2.6) and in higher versions, you will see some fields are left just for it.

Despite it being more than 30 years old, HL7v2 remains the most widely used healthcare interface standard by a large margin according to the HL7.org portal that tells that:

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Hi folks!

Recently I was in need to setup a local FHIR server using IRIS For Health and I think I found the easiest and simplest way ever.

Just run in terminal these two lines below :

docker run --rm --name my-iris -d --publish 9091:1972 --publish 9092:52773 intersystemsdc/irishealth-community

and

docker exec -it my-iris iris session iris -U "USER" '##class(%ZPM.PackageManager).Shell("install fhir-server")'

And you'll have FHIR server running locally at http://localhost:9092/fhir/r4.

That's it!

The FHIR server will use the latest build of InterSystems IRIS for Health Community Edition and will deploy FHIR server from this app via IPM package in FHIRSERVER namespace.

This is for Mac, so please add in comments how it works in Windows.

This is a very short article as it is really easy to setup a local FHIR server with InterSystems IRIS for Health and IPM Package Manager.

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