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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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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Docker 20.10.14 (released March 23, 2022) changes the Linux capabilities given to containers in a manner that is incompatible with the Linux capability checker in InterSystems IRIS 2021.1 (and up) containers.

Users running Docker 20.10.14 on Linux will find that IRIS 2021.1+ containers will fail to start and the logs will incorrectly report that required Linux capabilities are missing. For example:

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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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Hi Community!

We're pleased to announce that that InterSystems IRIS Community Edition is available on the Docker Store! InterSystems IRIS Community Edition is the no-cost developer edition designed to lower the barriers to entry to get started with IRIS. Now that it is listed on the Docker Store, running an IRIS Community instance is as easy as -

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I would say it is a post of pain after years of using InterrSystems IRIS Docker images in many projects.

And I hope InterSystems will hear me and do something with it.

We have a lot of issues with Docker images, but I see no progress in solving them.

  • containers.intersystems.com - any new releases substitute previous versions, makes build useless
    • ARM64 images have separate names, and it makes a pain to use them
  • flags in iris-main, appears and disappears from version to version, which may fail the start the container
  • healthcheck does not work as expected

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Hi everyone,

I am very pleased to announce that the Readmission Demo has been released as open source. Many thanks to the Solution Factory team that worked hard on making this possible.

Here are the changes:

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InterSystems Official
· Nov 12, 2018
New release cadence for InterSystems IRIS

Note: there are more recent updates, see https://community.intersystems.com/post/updates-our-release-cadence

InterSystems is adopting a new approach to releasing InterSystems IRIS. This blog explains the new release model and what customers should expect to see. We laid this out at Global Summit at the end of the InterSystems IRIS roadmap session and have received a lot of positive feedback from customers.

With this new model we offer two release streams:

1) An annual traditional release that we call EM (for Extended Maintenance)

2) A quarterly release that is tagged CD (for Continuous Delivery) and will be available only in a container format.

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IRIS offers Durable %SYS Directory as a highly useful feature for working with containers.

Before inventing the wheel once more I'd like to know if a similar feature also exists for Caché / Ensemble.
Official documentation is quite silent about.
Though I have some names in mind that might know more about ( @Luca Ravazzolo ? @Dmitry Maslennikov ? @Eduard Lebedyuk ? )

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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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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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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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Preview releases are now available for the 2019.3 version of InterSystems IRIS and IRIS for Health!

Container images are available via the WRC's preview download site.

The version number for these releases is 2019.3.0.302.0

Public announcements will be made shortly, with separate announcements for each product.

InterSystems IRIS Data Platform 2019.3 is a CD (continuous delivery) release of InterSystems IRIS. It has many new capabilities including:

Continuous Delivery Releases of InterSystems IRIS

InterSystems API Manager

Node-level Architecture for Sharding and SQL Support

Infrastructure and Cloud Deployment Improvements

Port Authority for Monitoring Port Usage in Interoperability Productions

X12 Element Validation in Interoperability Productions

New Framework for Coding Business Hosts in Java

Java and .NET Gateway Reentrancy

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Hi Community!

You're very welcome to watch a new video on InterSystems Developers YouTube, recorded by @Stefan Wittmann, InterSystems Product Manager:

InterSystems API Manager Introduction

https://www.youtube.com/embed/vO6kz1G4eVg
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Hey Community,

Learn about the changes we've made to InterSystems IRIS Containers, including security updates and the new web gateway container:

InterSystems IRIS Container Updates

https://www.youtube.com/embed/u5ccd1kifwQ
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InterSystems has also released IRIS as containerized deployments. This post is to demonstrate how InterSystems IRIS and applications those rely on IRIS a backend can be packaged into an image and be run in other machines in containers and how simple it is to do that.

A container runs image/s which have all the necessary executables, binary code, libraries, and configuration files. And the images can be moved from one machine to another, and an images repository like Docker Hub can simplify that process.

I have used an application from Open Exchange for this demo.

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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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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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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).

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Hi Community!

Enjoy watching the new video on InterSystems Developers YouTube, recorded by @Thomas Carroll, Cloud Market Technical Specialist at InterSystems.

How Are Containers Different From Virtual Machines?

https://www.youtube.com/embed/rXFvhDBzY8o
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Imagine you want to see what InterSystems can give you in terms of data analytics. You studied the theory and now you want some practice. Fortunately, InterSystems provides a project that contains some good examples: Samples BI. Start with the README file, skipping anything associated with Docker, and go straight to the step-by-step installation. Launch a virtual instance, install IRIS there, follow the instructions for installing Samples BI, and then impress the boss with beautiful charts and tables. So far so good.

Inevitably, though, you’ll need to make changes.

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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?
  • GitLab CI/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 this article, let's talk about containers and how (and why) they can be used.

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