InterSystems IRIS family has a nice utility ^SystemPerformance (as known as ^pButtons in Caché and Ensemble) which outputs the database performance information into a readable HTML file. When you run ^SystemPerformance on IRIS for Windows, a HTML file is created where both our own performance log mgstat and Windows performance log are included.
Over the years, I have found myself needing to create multiple HL7 messages based on a single inbound message. Usually these take the form of an order or result from a lab. Each time I have approached it, I have tried to start from scratch under the belief that the previous attempt could have been done better.
This article will describe and include an example of how to embed an external PDF file into an HL7 segment, specifically ADT_A01:2.3.1 OBX(). This can be useful when attempting to insert pictures or other external data into an HL7 message. In this example, the name of the PDF file to be embedded is provided in the incoming HL7 message in OBX(1):ObservationValue field.
As we all know, Caché is a great database that accomplishes lots of tasks within itself. However, what do you do when you need to access an external database? One way is to use the Caché SQL Gateway via JDBC. In this article, my goal is to answer the following questions to help you familiarize yourself with the technology and debug some common problems.
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.
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.
InterSystems supports use of the InterSystems IRIS Docker images it provides on Linux only. Rather than executing containers as native processes, as on Linux platforms, Docker for Windows creates a Linux VM running under Hyper-V, the Windows virtualizer, to host containers. These additional layers add complexity that prevents InterSystems from supporting Docker for Windows at this time.
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;
Caché Monitor: Scans the console log and sends emails alerts.
System Monitor: Monitors system status and resources, generating notifications (alerts and warnings) based on fixed parameters and also tracks overall system health.
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.
History Monitor: Maintains a historical database of performance and system usage metrics.
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.
This is a quick tutorial how to install and use TFS in Atelier. It is based on my self experience and some tricks that I 've noted.
If you are used to using visual studio maybe you feel that is a bit slow and heavy, but you have the same TFS panel as you have in Visual Studio, so don't need any special "training" to use it
In this article I would like to present the RESTForms project - generic REST API backend for modern web applications.
The idea behind the project is simple -after I wrote several REST APIs I realized that generally, REST API consists of two parts:
Work with persistent classes
Custom business logic
And, while you'll have to write your own custom business logic, RESTForms provides all things related to working with persistent classes right out of the box. Use cases
You already have a data model in Caché and you want to expose some (or all) of the information in a form of REST API
You are developing a new Caché application and you want to provide a REST API
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).
The object and relational data models of the Caché database support three types of indexes, which are standard, bitmap, and bitslice. In addition to these three native types, developers can declare their own custom types of indexes and use them in any classes since version 2013.1. For example, iFind text indexes use that mechanism.
In today's data landscape, businesses encounter a number of different challenges. One of them is to do analytics on top of unified and harmonized data layer available to all the consumers. A layer that can deliver the same answers to the same questions irrelative to the dialect or tool being used.
Suppose you have an application that allows users to write posts and comment on them. (Wait... that sounds familiar...)
For a given user, you want to be able to list all of the published posts with which that user has interacted - that is, either authored or commented on. How do you make this as fast as possible?
Here's what our %Persistent class definitions might look like as a starting point (storage definitions are important, but omitted for brevity):
The %Net.SSH.Session class lets you connect to servers using SSH. It's most commonly used with SFTP, especially in the FTP inbound and outbound adaptors.
In this article, I'm going to give a quick example of how to connect to an SSH server using the class, describe your options for authenticating, and how to debug when things go wrong.
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 ]:
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.
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.
One of the easiest ways to setup repeatable development environments is to spin up containers for them. I find that when iterating quickly, it was very convenient to host a vscode instance within my development container. Thus, I have created a quick container script to add a browser-based vscode into an IRIS container. This should work for most 2021.1+ containers. My code repository can be found here
During a major version upgrade it is advisable to recompile the classes and routines of all your namespaces (see Major Version Post-Installation Tasks).
It is becoming more and more common to see beautiful badges in the README.MD file with useful information about the current project in the repositories of GitHub, GitLab and others.
For instance:
This post provides guidelines for configuration, system sizing and capacity planning when deploying Caché 2015 and later on a VMware ESXi 5.5 and later environment.
Over the last couple of weeks the Solution Architecture team has been working to finish off our 2019 workload: this included open-sourcing the Readmission Demo that was brought to HIMSS last year, so we could make it available to anyone looking for an interactive-way of exploring the tooling provided by IRIS.
$LIST string format and %DynamicArray and %DynamicObject classes
IRIS, and previously Cache, contain several different ways to create a sequence containing a mixture of data values. A data sequence that has been available for many years is the $LIST string. Another more recent data sequence is the %DynamicArray class, which along with the %DynamicObject class, is part of the IRIS support for JSON string representation. These two sequences involve very different tradeoffs.
This post is dedicated to the task of monitoring a Caché instance using SNMP. Some users of Caché are probably doing it already in some way or another. Monitoring via SNMP has been supported by the standard Caché package for a long time now, but not all the necessary parameters are available “out of the box”. For example, it would be nice to monitor the number of CSP sessions, get detailed information about the use of the license, particular KPI’s of the system being used and such. After reading this article, you will know how to add your parameters to Caché monitoring using SNMP.
One of the great features in InterSystems IRIS is Monitoring InterSystems IRIS using REST API. This enables every InterSystems HealthShare instance with the ability to use a REST interface to provide statistics about the InterSystems HealthShare instance. This feature includes information about the In