In an earlier article (hope, you’ve read it), we took a look at the CircleCI deployment system, which integrates perfectly with GitHub. Why then would we want to look any further? Well, GitHub has its own CI/CD platform called GitHub Actions, which is worth exploring. With GitHub Actions, you don’t need to rely on some external, albeit cool, service.

In this article we’re going to try using GitHub Actions to deploy the server part of InterSystems Package Manager, ZPM-registry, on Google Kubernetes Engine (GKE).

Last time we deployed a simple IRIS application to the Google Cloud. Now we’re going to deploy the same project to Amazon Web Services using its Elastic Kubernetes Service (EKS).

We assume you’ve already forked the IRIS project to your own private repository. It’s called <username>/my-objectscript-rest-docker-template in this article. <root_repo_dir> is its root directory.

Before getting started, install the AWS command-line interface and, for Kubernetes cluster creation, eksctl, a simple CLI utility. For AWS you can try to use aws2, but you’ll need to set aws2 usage in kube config file as described here.

Introduction and Motivation

A unit of ObjectScript code (a ClassMethod, say) may produce a variety of unexpected side effects by interacting with parts of the system outside of its own scope and not properly cleaning up. As a non-exhaustive list, these include:

Most of us are more or less familiar with Docker. Those who use it like it for the way it lets us easily deploy almost any application, play with it, break something and then restore the application with a simple restart of the Docker container.

Previously I showed you how to run pButtons to start collecting performance metrics that we are looking at in this series of posts.

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's an example of making the connection:

This is the first in a pair of articles on SQL indices.

Part 1 - Know your indices

Introduction

The common requirement in many applications is logging of data changes in a database - which data has changed, who changed them and when (audit logging). There are many articles about this question and there are different approaches on how to do that in Caché.

If a picture is worth a thousand words, what's a video worth? Certainly more than typing a post.

Please check out my "Coding talks" on InterSystems Developers YouTube:

1. Analysing InterSystems IRIS System Performance with Yape. Part 1: Installing Yape

https://www.youtube.com/embed/3KClL5zT6MY
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Running Yape in a container.

2. Yape Container SQLite iostat InterSystems

https://www.youtube.com/embed/cuMLSO9NQCM
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Extracting and plotting pButtons data including timeframes and iostat.

Loading your IRIS Data to your Google Cloud Big Query Data Warehouse and keeping it current can be a hassle with bulky Commercial Third Party Off The Shelf ETL platforms, but made dead simple using the iris2bq utility.

Let's say IRIS is contributing to workload for a Hospital system, routing DICOM images, ingesting HL7 messages, posting FHIR resources, or pushing CCDA's to next provider in a transition of care. Natively, IRIS persists these objects in various stages of the pipeline via the nature of the business processes and anything you included along the way. Lets send that up to Google Big Query to augment and compliment the rest of our Data Warehouse data and ETL (Extract Transform Load) or ELT (Extract Load Transform) to our hearts desire.

A reference architecture diagram may be worth a thousand words, but 3 bullet points may work out a little bit better:

• It exports the data from IRIS into DataFrames
• It saves them into GCS as .avro to keep the schema along the data: this will avoid to specify/create the BigQuery table schema beforehands.
• It starts BigQuery jobs to import those .avro into the respective BigQuery tables you specify.

AnalyzeThis is a tool for getting a personalized preview of your own data inside of InterSystems BI. This allows you to get first hand experience with InterSystems BI and understand the power and value it can bring to your organization. In addition to getting a personalized preview of InterSystems BI through an import of a CSV file with your data, Classes and SQL Queries are now supported as Data Sources in v1.1.0!

Intro

For many in today's interoperability landscape, REST reigns supreme. With the overabundance of tools and approaches to REST API development, what tools do you choose and what do you need to plan for before writing any code?
This article focuses on design patterns and considerations that allow you to build highly robust, adaptive, and consistent REST APIs. Viable approaches to challenges of CORS support and authentication management will be discussed, along with various tips and tricks and best tools for all stages of REST API development. Learn about the open-source REST APIs available for InterSystems IRIS Data Platform and how they tackle the challenge of ever-increasing API complexity.
The article is a write-up for a recent webinar on the same topic.

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.

Here are my tips...

1. Write your own COS cheat-sheet.

This is a basic JavaScript Vue.js example how you can use REST calls using plain HTML.