Configuring an Ensemble production can be a challenging task involving a thorough understanding of the system and production functionality and a detailed understanding towards each configuration item. After successfully configured an Ensemble production, you might need to set up an identical production on the mirror environment, or deploy the production on a development system to a live system, or send a copy for diagnostic/debug purposes. Other times you might have spent some time designing a BPL/DTL and some other productions can use the same logic.

Your application is deployed and everything is running fine. Great, hi-five! Then out of the blue the phone starts to ring off the hook – it’s users complaining that the application is sometimes ‘slow’. But what does that mean? Sometimes? What tools do you have and what statistics should you be looking at to find and resolve this slowness? Is your system infrastructure up to the task of the user load? What infrastructure design questions should you have asked before you went into production? How can you capacity plan for new hardware with confidence and without over-spec'ing? How can you stop the phone ringing? How could you have stopped it ringing in the first place?

This post provides useful links and an overview of best practice configuration for low latency storage IO by creating LVM Physical Extent (PE) stripes for database disks on InterSystems Data Platforms; InterSystems IRIS, Caché, and Ensemble.

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.

1. Fhir-client-java

This is a simple fhir client in java to practice with fhir resources and CRUD requests to a fhir server.

Note that for the most part auto-completion is activated.

GitHub

As we all know, Caché is a great database that accomplishes lots of tasks within itself. However, what do you do when you need to access an external database? One way is to use the Caché SQL Gateway via JDBC. In this article, my goal is to answer the following questions to help you familiarize yourself with the technology and debug some common problems.

This article gives a brief introduction how a RESTful service consumer and a RESTful service provider exchange data. It is a beginner’s guide. Data is transferred from a consumer to a provider as parameters of the service. Parameters are part of a service request. The result of the service action a response is returned from a provider to a consumer. Both the service request and response are standard HTTP messages. Since HTTP is a flexible standard regarding to the message contents, RESTful services also enjoy the versatility of data transfer methods.

Prometheus is one of the monitoring systems adapted for collecting time series data.

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.

Where did the RemoteSystemsTempFiles project come from?

If you're using Atelier, you may have noticed a project called "RemoteSystemsTempFiles" in the Atelier Explorer and Project Explorer views. This project is automatically created by the Eclipse Remote Systems Explorer (RSE) on start-up. The RSE allows you to connect to and work with a variety of remote systems.

You can either hide this project within your views, or remove it completely by following the steps below.

Introduction.

Have you ever felt like your PDF files take up too much space on your server? As you collect more and more of these files, you might run into storage issues that can be costly to solve. But what if there was a way to shrink the size of these PDFs by 50% to 70% without compromising the document's visual clarity.

Today, we're going to explore a solution for this problem that I really like: GhostScript.

New Tool Available

Please see PerfTools IO Test Suite for a later version of the Random Read IO tool.

Purpose

This tool is used to generate random read Input/Output (IO) from within the database. The goal of this tool is to drive as many jobs as possible to achieve target IOPS and ensure acceptable disk response times are sustained. Results gathered from the IO tests will vary from configuration to configuration based on the IO sub-system. Before running these tests ensure corresponding operating system and storage level monitoring are configured to capture IO performance metrics for later analysis.

In this article, we’ll build a highly available IRIS configuration using Kubernetes Deployments with distributed persistent storage instead of the “traditional” IRIS mirror pair. This deployment would be able to tolerate infrastructure-related failures, such as node, storage and Availability Zone failures. The described approach greatly reduces the complexity of the deployment at the expense of slightly extended RTO.