This post is intended to guide you through the new JSON capabilities that we introduced in Caché 2016.1. JSON has emerged to a serialization format used in many places. The web started it, but nowadays it is utilized everywhere. We've got plenty to cover, so let's get started.
The InterSystems Learning Website has many important iterative courses. So if you want to learn about InterSystems and start to work with InterSystems this is the path:
I was first introduced to TDD almost 9 year ago, and I immediately fell in love with it. Nowadays it's become very popular but, unfortunately, I see that many companies don't use it. Moreover, many developers don't even know what it is exactly or how to use it, mainly beginners.
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).
Recently I was fielding some questions that someone had about some bugs that crop up on Docker for Mac, and it reminded me of what Shakespeare wrote in his famous tragedy about large-scale software orchestration, Kubelet: the Prince of Benchmark.
InterSystems IRIS 2019.1 has been out for a while and I would like to cover some enhancements for handling JSON which might have gone unnoticed. Dealing with JSON as a serialization format is an important part of building modern applications, especially when you interact with REST endpoints.
In this article, we’ll build a highly available IRIS configuration using Kubernetes Deployments with distributed persistent storage instead of the “traditional” IRIS mirror pair. This deployment would be able to tolerate infrastructure-related failures, such as node, storage and Availability Zone failures. The described approach greatly reduces the complexity of the deployment at the expense of slightly extended RTO.
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?
This is a rather personal view on the history before Caché. It is in no sense meant to compete with the excellent books from Mike Kadow discussed in an earlier article. We have different history and so this is meant to create a different prospective of the past.
Not so while ago GitHub introduced, ability to very quickly run VSCode in the browser for any repository hosted there. Press the . key on any repository or pull request, or swap .com with .dev in the URL, to go directly to a VS Code environment in your browser.
This VSCode is a light version of the Desktop version but works entirely in Browser. And due to this, it has a limitation for extensions which was allowed to work this way. And let me introduce the new version 1.2.1 of VSCode-ObjectScript extension which now supports running in Browser mode.
When using Studio, ODBC or a terminal connection to Caché or Ensemble, you may have wondered how to secure the connection. One option is to add TLS (aka SSL) to your connection. The Caché client applications - TELNET, ODBC and Studio - all understand how to add TLS to the connection. They just need to be configured to do it.
Configuring these clients is easier in 2015.1 and later. I'm going to be discussing this new method. If you're already using the old, legacy method, it will continue to work, but I would recommend you consider switching to the new one.
The topic of for/while loop performance in Caché ObjectScript came up in discussion recently, and I'd like to share some thoughts/best practices with the rest of the community. While this is a basic topic in itself, it's easy to overlook the performance implications of otherwise-reasonable approaches.
Have some free text fields in your application that you wish you could search efficiently? Tried using some methods before but found out that they just cannot match the performance needs of your customers? Do I have one weird trick that will solve all your problems? Don’t you already know!? All I do is bring great solutions to your performance pitfalls!
As usual, if you want the TL;DR (too long; didn’t read) version, skip to the end. Just know you are hurting my feelings.
ObjectScript has at least three ways of handling errors (status codes, exceptions, SQLCODE, etc.). Most of the system code uses statuses but exceptions are easier to handle for a number of reasons. Working with legacy code you spend some time translating between the different techniques. I use these snippets a lot for reference. Hopefully they're useful to others as well.
Finding errors in your code or examining unexpected behavior is the main purpose of Debugging I will try to refresh the traditional tools away from the helpers you have in Studio, VScode, Serenji, .... to the basics which have been there before your preferred EDI used it in the background.
This article is a small overview of a tool that helps to understand classes and their structure inside the InterSystems products: from IRIS to Caché, Ensemble, HealthShare.
In short, it visualizes a class or an entire package, shows the relations between classes and provides all the possible information to developers and team leads without making them go to Studio and examine the code there.
If you are learning InterSystems products, reviewing projects a lot or just interested in something new in InterSystems Technology solutions — you are more than welcome to read the overview of ObjectScript Class Explorer!
As a developer, you have probably spent at least some time writing repetetive code. You may have even found yourself wishing you could generate the code programmatically. If this sounds familiar, this article is for you!
We'll start with an example. Note: the following examples use the %DynamicObject interface, which requires Caché 2016.2 or later. If you are unfamiliar with this class, check out the documentation here: Using JSON in Caché. It's really cool!
Every day Johns Hopkins University publishes new data on coronavirus COVID-19 pandemic status.
I built a simple InterSystems IRIS Analytics dashboard using InterSystems IRIS Community Edition in docker deployed on GCP Kubernetes which shows key measures of the disease outbreak.
This dashboard is an example of how information from CSV could be analyzed with IRIS Analytics and deployed to GCP Kubernetes in a form of InterSystems IRIS Community Edition.
Looking to breathe new life into an old MUMPS application? Follow these steps to map your existing globals to classes and expose all that beautiful data to Objects and SQL.
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.
Does anyone NOT use a debugger? I can't remember the last time I did. It's not because I don't dislike them, I just don't need to use them. The main reason for this is because I have a certain development methodology that either produces less bugs, catches them at a unit test level, or makes tracking them down much easier.
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