Hi Community,

Please welcome the new video on InterSystems Developers YouTube:

⏯ Extending Interoperability with PEX & Containers

https://www.youtube.com/embed/JoSS4QYaELc
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Hello community,

Our organization is looking to expand our Coding Standards to be more in alignment with best practices.

I was wondering if the there are developers here that would not mind sharing any existing documents. Our scope would be this document be applicable to new hires learning Cache all the way up the chain.

Thanks in advance,

-SH

This article is a continuation of Deploying InterSystems IRIS solution on GKE Using GitHub Actions, in which, with the help of GitHub Actions pipeline, our zpm-registry was deployed in a Google Kubernetes cluster created by Terraform. In order not to repeat, we’ll take as a starting point that:

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.

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.

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.

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.

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.

We are currently implementing the Data Innovations Instrument Manager product. In setting up our backup process we are wanting to use Veam snapshots. The application runs in a Caché 2016.1/Windows Server 2016 instance. We are running an HA primary/secondary/arbiter config. The statement below is from DI. I am curious to see what others that have implemented the DI Instrument Manager in the same or similar config have in place for backup.

"DI recommends is recommending that we not perform snapshots, but if you do choose to do so, here is some important information to consider.

Hi Everyone!

One more session recording from Global Summit 2018 is available on InterSystems Developers YouTube Channel:

InterSystems IRIS in a Container

https://www.youtube.com/embed/gaZfBdQYnVE
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This is a continuation of my story about the development of my project isc-tar started in the first part.

Just having tests is not enough, it does not mean that you will run tests after all changes. Running tests should be automated, and when you cover all your functionality with tests, everything should work well after any change in any place. And Continuous Integration (CI) helps to keep the code and deployment procedure with as fewer bugs as possible and automates the routine procedures, like publishing releases.

I use GitHub to store the source code. And some time ago GitHub started to work on its own CI/CD platform and named it GitHub Actions. It is not widely available, yet. You have to be signed as a beta tester for this feature, as I did. GitHub Actions uses quite a different way how to deal with a build workflow. What is important that Github Actions allows to use Docker, and it’s quite easy to customize available actions. And interesting that GitHub Actions is really much bigger than any classic CI like we have in Travis, Circle or Gitlab CI and so on. You can find more in the official documentation.

Hi Everyone!

New session recording from Global Summit 2018 is already on InterSystems Developers YouTube Channel:

Advanced Cloud Provisioning & Deployment

https://www.youtube.com/embed/BAN-l4nagxI
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Hi Community!

Please welcome a new video on InterSystems Developers YouTube Channel:

Continuous Delivery with Containers

https://www.youtube.com/embed/QyE7sF86eMk
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Let's say I want to execute this cache script (saved as test.txt) from OS terminal:

zn "USER"
write 1
zn "%SYS"
write 2
halt

Executing the following command in a terminal:

csession cache < test.txt

Would yield this output:

$ csession cache < script.txt

Node: gitlab-test, Instance: CACHE

USER>

USER>
1
USER>

%SYS>
2
%SYS>
Job succeeded

Is there a better way to run these scripts?

Currently I have two problems: