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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Loading your IRIS Data to your Google Cloud Big Query Data Warehouse and keeping it current can be a hassle with bulky Commercial Third Party Off The Shelf ETL platforms, but made dead simple using the iris2bq utility.

Let's say IRIS is contributing to workload for a Hospital system, routing DICOM images, ingesting HL7 messages, posting FHIR resources, or pushing CCDA's to next provider in a transition of care. Natively, IRIS persists these objects in various stages of the pipeline via the nature of the business processes and anything you included along the way. Lets send that up to Google Big Query to augment and compliment the rest of our Data Warehouse data and ETL (Extract Transform Load) or ELT (Extract Load Transform) to our hearts desire.

A reference architecture diagram may be worth a thousand words, but 3 bullet points may work out a little bit better:

  • It exports the data from IRIS into DataFrames
  • It saves them into GCS as .avro to keep the schema along the data: this will avoid to specify/create the BigQuery table schema beforehands.
  • It starts BigQuery jobs to import those .avro into the respective BigQuery tables you specify.

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Database systems have very specific backup requirements that in enterprise deployments require forethought and planning. For database systems, the operational goal of a backup solution is to create a copy of the data in a state that is equivalent to when application is shut down gracefully. Application consistent backups meet these requirements and Caché provides a set of APIs that facilitate the integration with external solutions to achieve this level of backup consistency.

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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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Article
David Reche · Jan 18, 2019 2m read
Free IRIS Community Edition in AWS

Good News!! You can use now the Free InterSystems IRIS Community Edition in the AWS Cloud

Hello,

It's very common that people new in InterSystems IRIS want to start to work in a personal project in a full free environment. If you are one of this, Good News!! You can use now the Free InterSystems IRIS Community Edition in the AWS Cloud.

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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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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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For Global Summit 2016, I set out to showcase a Reference Architecture I had been working on for a National Provider Directory solution with State Level Instances and a National Instance all running HealthShare Provider Directory and all running on AWS Infrastructure.

In short, I wanted to highlight:

  • The implementation of Amazon Web Services to provision the infrastructure, including the auto-creation of the state level instances through Cloud Formation.
  • The use of the HSPD Broadcast functionality to Notify Upstream Systems Changes in Master Provider Data.
  • The implementation of a transformation of the standard Broadcast Object to HL7 MFN for interoperability.
  • The principals of Master Data Management applied to the Provider Directory.

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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
  • CD using ICM

In this article, we'll build Continuous Delivery with InterSystems Cloud Manager. ICM is a cloud provisioning and deployment solution for applications based on InterSystems IRIS. It allows you to define the desired deployment configuration and ICM would provision it automatically. For more information take a look at First Look: ICM.

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++ Update: August 1, 2018

The use of the InterSystems Virtual IP (VIP) address built-in to Caché database mirroring has certain limitations. In particular, it can only be used when mirror members reside the same network subnet. When multiple data centers are used, network subnets are not often “stretched” beyond the physical data center due to added network complexity (more detailed discussion here). For similar reasons, Virtual IP is often not usable when the database is hosted in the cloud.

Network traffic management appliances such as load balancers (physical or virtual) can be used to achieve the same level of transparency, presenting a single address to the client applications or devices. The network traffic manager automatically redirects clients to the current mirror primary’s real IP address. The automation is intended to meet the needs of both HA failover and DR promotion following a disaster.

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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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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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This summer the Database Platforms department here at InterSystems tried out a new approach to our internship program. We hired 10 bright students from some of the top colleges in the US and gave them the autonomy to create their own projects which would show off some of the new features of the InterSystems IRIS Data Platform. The team consisting of Ruchi Asthana, Nathaniel Brennan, and Zhe “Lily” Wang used this opportunity to develop a smart review analysis engine, which they named Lumière. As they explain:

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Enterprises need to grow and manage their global computing infrastructures rapidly and efficiently while simultaneously optimizing and managing capital costs and expenses. Amazon Web Services (AWS) and Elastic Compute Cloud (EC2) computing and storage services meet the needs of the most demanding Caché based application by providing
 a highly robust global computing infrastructure.

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++Update: August 2, 2018

This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.

Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).

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Presenter: Tony Pepper
Task: Host an application based on InterSystems’ technology in a public cloud environment
Approach: Provide a checklist of things to think about before you deploy

Are you looking at hosting your applications in the public cloud? This talk will highlight what you need to think about when deploying InterSystems technology in any public cloud environment.

Content related to this session, including slides, video and additional learning content can be found here.

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Presenter: Mark Bolinsky
Task: Provide failover for distributed systems without using a VIP
Approach: Demonstrate using InterSystems’ database mirroring with external traffic managers such as F5 LTM/GTM

With distributed environments and even public cloud environments, the use of a VIP sometimes is not desirable or even possible given network topology or deployment. The session will demonstrate integrating database mirroring with external traffic managers such F5 LTM/GTM using API based triggers in InterSystems products to interface with the F5 appliances. This not only presents automated redirection for the local mirror members, but also provided automated client redirection to asynchronous DR mirror members.

Content related to this session, including slides, video and additional learning content can be found here.

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Presenter: Luca Ravazzolo
Task: Define, provision, and configure a cloud infrastructure
Approach: Use open-source tools for DevOps automation

This session demonstrates how a cloud infrastructure of clustered servers can be defined, provisioned and configured efficiently with a simple yet powerful provisioning technology.

Content related to this session, including slides, video and additional learning content can be found here.

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RESTful API Call From Cache to Particle.io Electron

Tom Fitzgibbon | Multidata | 212-967-6700 x537 | tom@mul.com

Summary: Simple Blink Tutorial for Particle.io Electron Device from Cache

Electron device is a tiny ARM processor ($40-$60) that connects to Particle’s world wide leased 2G/3G network (about $3/mo) and runs off an included LiPo battery. Using Cache’s %Net.HttpRequest you can send/receive data, control hardware and read sensors.

Step by Step (about 1 hour)

1) Get the Electron from store.particle.io.

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