DevOps

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InterSystems Official
Steven LeBlanc · Aug 21, 2020
Introducing InterSystems Container Registry

I am pleased to announce the availability of InterSystems Container Registry. This provides a new distribution channel for customers to access container-based releases and previews. All Community Edition images are available in a public repository with no login required. All full released images (IRIS, IRIS for Health, Health Connect, System Alerting and Monitoring, InterSystems Cloud Manager) and utility images (such as arbiter, Web Gateway, and PasswordHash) require a login token, generated from your WRC account credentials.

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Hey Developers,

We're pleased to invite you to join the next InterSystems IRIS 2020.1 Tech Talk: DevOps on June 2nd  at 10:00 AM EDT! 

In this InterSystems IRIS 2020.1 Tech Talk, we focus on DevOps. We'll talk about InterSystems System Alerting and Monitoring, which offers unified cluster monitoring in a single pane for all your InterSystems IRIS instances. It is built on Prometheus and Grafana, two of the most respected open source offerings available.

Next, we'll dive into the InterSystems Kubernetes Operator, a special controller for Kubernetes that streamlines InterSystems IRIS deployments and management. It's the easiest way to deploy an InterSystems IRIS cluster on-prem or in the Cloud, and we'll show how you can configure mirroring, ECP, sharding and compute nodes, and automate it all.

Finally, we'll discuss how to speed test InterSystems IRIS using the open source Ingestion Speed Test. This tool is available on InterSystems Open Exchange for your own testing and benchmarking. 

   

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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.

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Hi Everyone,

I've been working on deploying an IRIS for Health environment in EKS. There is a video session in the InterSystems learning portal about this feature but I have not succeeded in finding the proper documentation and resources to use this in my Kubernetes cluster.

Has this been deprecated/discontinued? Any idea where can I find the resources? Should I stick to StatefulSets instead of using the IrisCluster resource type provided by this operator?

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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

 

Running Yape in a container.

2. Yape Container SQLite iostat InterSystems

Extracting and plotting pButtons data including timeframes and iostat.

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Question
Sylvie Greverend · Aug 25, 2019
Automation with Ansible

Trying to modernize tasks I have to do on cache like change global variables on different servers, different namespaces....

Actually, I have a bash script  doing ssh on each server and running bash  script on each server like this

echo "zn \"namespace\"
s ^Var=1
"|csession ensapp

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As we all well know, InterSystems IRIS has an extensive range of tools for improving the scalability of application systems. In particular, much has been done to facilitate the parallel processing of data, including the use of parallelism in SQL query processing and the most attention-grabbing feature of IRIS: sharding. However, many mature developments that started back in Caché and have been carried over into IRIS actively use the multi-model features of this DBMS, which are understood as allowing the coexistence of different data models within a single database. For example, the HIS qMS database contains both semantic relational (electronic medical records) as well as traditional relational (interaction with PACS) and hierarchical data models (laboratory data and integration with other systems). Most of the listed models are implemented using SP.ARM's qWORD tool (a mini-DBMS that is based on direct access to globals). Therefore, unfortunately, it is not possible to use the new capabilities of parallel query processing for scaling, since these queries do not use IRIS SQL access.

Meanwhile, as the size of the database grows, most of the problems inherent to large relational databases become right for non-relational ones. So, this is a major reason why we are interested in parallel data processing as one of the tools that can be used for scaling.

In this article, I would like to discuss those aspects of parallel data processing that I have been dealing with over the years when solving tasks that are rarely mentioned in discussions of Big Data. I am going to be focusing on the technological transformation of databases, or, rather, technologies for transforming databases.

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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:

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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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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.

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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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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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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:

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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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An exciting position has arisen for a Junior Application Support Analyst in an established support team. The role will suit candidates looking to enter, or are at the start of their career in, the software industry who want to provide good customer service, enjoy finding solutions for problems and are enthusiastic about software and technology. http://codas.com

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An exciting position has arisen for an Application Support Analyst 3rd Line, in an established support team. The role will suit candidates looking to work in the software industry who want to provide good customer service, enjoy finding solutions for problems and are enthusiastic about software and technology.  http://codas.com

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Released with no formal announcement in IRIS preview release 2019.4 is the /api/monitor service exposing IRIS metrics in Prometheus format. Big news for anyone wanting to use IRIS metrics as part of their monitoring and alerting solution. The API is a component of the new IRIS System Alerting and Monitoring (SAM) solution that will be released in an upcoming version of IRIS.

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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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