#Containerization

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.

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

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.

Hi, everyone!

I want to share a personal project that started with a simple request at work:

Is it's possible to know how many Caché licenses we are using?

Reading other articles here in the community, I found this excellent article by David Loveluck

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.

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.

In my previous article, I gave an example of how to get the own image with InterSystems Caché. Now it's time to launch a project with container.

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.

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.

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.

Sometimes customers need a small IRIS instance to do something in the cloud and shut it down, or they need hundreds of containers (i.e. one per end user or one per interface) with small workloads. This exercise came about to see how small an IRIS instance could be. For this exercise we focused on what is the smallest amount of memory we can configure for an IRIS instance. Do you know all the parameters that affect the memory allocated by IRIS ?

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.

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!

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.

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.