When there's a performance issue, whether for all users on the system or a single process, the shortest path to understanding the root cause is usually to understand what the processes in question are spending their time doing. Are they mostly using CPU to dutifully march through their algorithm (for better or worse); or are they mostly reading database blocks from disk; or mostly waiting for something else, like LOCKs, ECP or database block collisions?

Hi Developers,

The annual competition for InterSystems IRIS developers is fast approaching!

We're super excited to invite you all to join the Grand Prix contest for building open-source solutions using InterSystems IRIS data platform!

🏆 InterSystems Grand Prix Contest 2023 🏆

Duration: June 12th - July 9th, 2023

Prize pool: $26,000

In this article I'll show you how you can easily convert between many different document formats, these to be precise:

• in: html, odt, doc, docx, rtf, sdw, txt...
• out: html, odt, docx, rtf, pdf, txt, tex, xhtml...

and many more, check out this table. We'll use LibreOffice as a conversion engine.

This example is extracted from a long-running installation.
The purpose is to have simple monitoring of several servers at a rather primitive level.
Just slightly more intelligent than a raw PING. But still easy to integrate.
It avoids the overkill of information you are often confronted with while you are just
interested in the number of active processes or similar basic figures.
The example shows a basic skeleton that might be easily filled by your real needs.

It consists of 3 sections:

I wanted to provide a heads up of an improvement in how we generate and call method code in IRIS 2023.1.

A class in IRIS is composed of two main runtime components:

This short article was motivated by a problem of one of my customers. They use Ensemble to integrate many systems, some of them use just plain files.

So they naturally selected File Outbound Adapter to write into target file. Things were running smoothly for years, until recently, when the volume of data being written to the file reached large size of tens of megabytes. The operation took around half an hour to complete, causing timing problems where subsequent operations within the process had to wait, and third party system was not happy to wait so long.

In a single server environment, it is rather easy to create a transaction consistent backup.

Simplified:
You find (or force a specific point in time with no open transactions.
Freeze your server, take a snapshot and you are done.

If you have worked with Caché Objects,
You know already all about Relationships (one:many , parent:child) ...
But you will not find a word on many:many relationships in the docs.

But I met the question quite often from new adopters of Caché objects:
"Is it possible to implement many:many relationships ?" YES - of course !

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:

In the good old days (tm) determining the size of the data, streams, and indices for a class/table was easy - you just ran %GSIZE and check D, S, and I globals respectively.

However, nowadays sharding, optimized global names, and indices in separate globals produce %GSIZE output looking like this:

InterSystems Data Platform includes utilities and tools for system monitoring and alerting, however System Administrators new to solutions built on the InterSystems Data Platform (a.k.a Caché) need to know where to start and what to configure.

This guide shows the path to a minimum monitoring and alerting solution using references from online documentation and developer community posts to show you how to enable and configure the following;

1. Caché Monitor: Scans the console log and sends emails alerts.

2. System Monitor: Monitors system status and resources, generating notifications (alerts and warnings) based on fixed parameters and also tracks overall system health.

3. Health Monitor: Samples key system and user-defined metrics and compares them to user-configurable parameters and established normal values, generating notifications when samples exceed applicable or learned thresholds.

4. History Monitor: Maintains a historical database of performance and system usage metrics.

5. pButtons: Operating system and Caché metrics collection scheduled daily.

Remember this guide is a minimum configuration, the included tools are flexible and extensible so more functionality is available when needed. This guide skips through the documentation to get you up and going. You will need to dive deeper into the documentation to get the most out of the monitoring tools, in the meantime, think of this as a set of cheat sheets to get up and running.

Hello DC members,

Considering the unparalleled success of last year's activity, we've decided to prepare it for you once more. So, without further ado, welcome

🔥 YOUR 2023 RECAP 🔥

By now it's a commonplace how to implement a basic REST API in Caché and there is good documentation about it here: REST in Caché

A question that comes up from time to time is:

How can I make a parameter in my REST url optional?

Simply put, is it possible to create a URL map in Caché that maps a URL like this: