Everybody has a testing environment.

Some people are lucky enough to have a totally separate environment to run production in.

-- Unknown

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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab WorkFlow
  • GitLab CI/CD
  • CI/CD with containers

This first part deals with the cornerstone of modern software development - Git version control system and various Git flows.

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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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The InterSystems Iris Fhirserver running on a Raspberry Pi Raspberry running as a FHIRserver

Raspberry running as FHIRserver

About a year ago I wrote some articles about the installation of the HAPI FHIRserver on a Raspberry Pi. At that time, I only knew the basics of the FHIR standard, little about the technology behind FHIR-servers and not much more about the Raspberry. By trying, failing, giving up and trying again I learned a lot.

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Article
Luca Ravazzolo · Jan 31, 2018 3m read
Container - What is a Container?

Containers

With the launch of InterSystems IRIS Data Platform, we provide our product even in a Docker container. But what is a container?

The fundamental container definition is that of a sandbox for a process.

Containers are software-defined packages that have some similarities to virtual machines (VM) like for example they can be executed.

Containers provide isolation without a full OS emulation. Containers are therefore much lighter than a VM.

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Hi folks,
It's time now for a Micro Service Demo with a total fresh IRIS Image and an image that you both PULL with
docker and run with only 4 lines of docker commands.
June 1st, 2020 - rcc

There is now a compact All-in-1 version available that combines all parts in a single container image.
For details see: IRIS-NativeAPI-Nodejs-compact
May 24, 2020 - rcc

I have added a simplified installation using Docker, see context
May 25, 2020 - rcc

There are enhanced scripts suitable & tested for Linux & Windows available here
https://github.com/rcemper/WSockClientMicroSV/blob/master/READMEwindows.MD
May 26, 2020 - rcc

This demo is a redesign of the WebSocket Client based on Node.js existing already for Caché. The major changes:

  • use of the new IRIS Native API for Node.js especially Working with Global Arrays
  • change from a directly triggered client to a server design
  • put the result into a separate docker image as an example for a MicroService / MicroServer
  • add a simple interface in IRIS to control the MicroService execution.

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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.

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Article
Oliver Wilms · Aug 4, 2021 3m read
IRIS Mirror in the cloud (AWS)

I have been working on redesigning a Health Connect production which runs on a mirrored instance of Healthshare 2019. We were told to take advantage of containers. We got to work on IRIS 2020.1 and split the database part from the Interoperability part. We had the IRIS mirror running on EC2 instances and used containers to run IRIS interoperability application. Eventually we decided to run the data tier in containers as well.

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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.

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Last week saw the launch of the InterSystems IRIS Data Platform in sunny California.

For the engaging eXPerience Labs (XP-Labs) training sessions, my first customer and favourite department (Learning Services), was working hard assisting and supporting us all behind the scene.

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I have just created a new Global Master Topic, "IRIS Cheatsheets". IRIS has introduced a lot of new functionality, especially in scripting languages, FHIR R4 support, enhanced Interoperability Tools, and IRIS Analytics. Having spent 35 years working on Windows-based PC's and Laptops, I have surprisingly little knowledge of Linux, Docker and Git. Furthermore, I have written almost every application and Interface in ObjectScript with splatterings of SQL, .Net, and Java Gateways and the most basic knowledge of WinSCP, Putty, SSH. All that changed when I received my first Raspberry Pi.

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The last time that I created a playground for experimenting with machine learning using Apache Spark and an InterSystems data platform, see Machine Learning with Spark and Caché, I installed and configured everything directly on my laptop: Caché, Python, Apache Spark, Java, some Hadoop libraries, to name a few. It required some effort, but eventually it worked.

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Article
Robert Cemper · Jul 20, 2020 1m read
IRIS-NativeAPI-Nodejs-compact

This is a follow-up to my previous article WebSocket Client JS with IRIS Native API as Docker Micro Server

Installation is now much simpler as all pieces are now assembled in a single Docker image.
That makes life easier. But of course, the principle of the Micro Service is not so obvious anymore.
An All-in-1 bundled package. Therefore compact.

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Google Cloud Platform (GCP) provides a feature rich environment for Infrastructure-as-a-Service (IaaS) as a cloud offering fully capable of supporting all of InterSystems products including the latest InterSystems IRIS Data Platform. Care must be taken, as with any platform or deployment model, to ensure all aspects of an environment are considered such as performance, availability, operations, and management procedures. Specifics of each of those areas will be covered in this article.

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Hi Community!

I think everyone keeps the source code of the project in the repository nowadays: Github, GitLab, bitbucket, etc. Same for InterSystems IRIS projects check any on Open Exchange.

What do we do every time when start or continue working with a certain repository with InterSystems Data Platform?

We need a local InterSystems IRIS machine, have the environment for the project set up and the source code imported.

So every developer performs the following:

  1. Check out the code from repo
  2. Install/Run local IRIS installation
  3. Create a new namespace/database for a project
  4. Import the code into this new namespace
  5. Setup all the rest environment
  6. Start/continue coding the project

If you dockerize your repository this steps line could be shortened to this 3 steps:

  1. Check out the code from repo
  2. Run docker-compose build
  3. Start/continue coding the project

Profit - no any hands-on for 3-4-5 steps which could take minutes and bring head ache sometime.

You can dockerize (almost) any your InterSystems repo with a few following steps. Let’s go!

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Container Images

In this second post on containers fundamentals, we take a look at what container images are.

What is a container image?

A container image is merely a binary representation of a container.

A running container or simply a container is the runtime state of the related container image.

Please see the first post that explains what a container is.

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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab Workflow
  • Continuous Delivery
  • GitLab installation and configuration
  • GitLab CI/CD

In the previous article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software. Still, our focus was on the implementation part of software development, but this part presents:

  • GitLab Workflow - a complete software life cycle process - from idea to user feedback
  • Continuous Delivery - software engineering approach in which teams produce software in short cycles, ensuring that the software can be reliably released at any time. It aims at building, testing, and releasing software faster and more frequently.

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In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:

  • Git 101
  • Git flow (development process)
  • GitLab installation
  • GitLab Workflow
  • Continuous Delivery
  • GitLab installation and configuration
  • GitLab CI/CD
  • Why containers?
  • Containers infrastructure
  • CD using containers

In the first article, we covered Git basics, why a high-level understanding of Git concepts is important for modern software development, and how Git can be used to develop software.

In the second article, we covered GitLab Workflow - a complete software life cycle process and Continuous Delivery.

In the third article, we covered GitLab installation and configuration and connecting your environments to GitLab

In the fourth article, we wrote a CD configuration.

In the fifth article, we talked about containers and how (and why) they can be used.

In the sixth article let's discuss main components you'll need to run a continuous delivery pipeline with containers and how they all work together.

In this article, we'll build Continuous Delivery configuration discussed in the previous articles.

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Last time we launched an IRIS application in the Google Cloud using its GKE service.

And, although creating a cluster manually (or through gcloud) is easy, the modern Infrastructure-as-Code (IaC) approach advises that the description of the Kubernetes cluster should be stored in the repository as code as well. How to write this code is determined by the tool that’s used for IaC.

In the case of Google Cloud, there are several options, among them Deployment Manager and Terraform. Opinions are divided as to which is better: if you want to learn more, read this Reddit thread Opinions on Terraform vs. Deployment Manager? and the Medium article Comparing GCP Deployment Manager and Terraform.

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I wanted to write it as a comment to article of @Evgeny Shvarov . But it happens to be so long, so, decided to post it separately.

Image result for docker clean all images

I would like to add a bit of clarification about how docker uses disk space and how to clean it. I use macOS, so, everything below, is mostly for macOS, but docker commands suit any platform.

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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.

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